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References ...

Updated: Jan 28, 2024


“You can't connect the dots looking forward; you can only connect them looking backwards" Steve Jobs (Dots are what you are putting effort and learning differently today) - That connect tomorrow

All in Learning Context & Suggestion to try (As reference) for learning purpose



Simulations





IT Coding (Python +DSA+SQL+AI Advance) IT (In future will use as just for reference) ..Just sharing with all students


https://quizlet.com/25549586/genetics-flash-cards/ (better for image , concept +click Point)



https://visualgo.net/en (NUS Singapore -DSA)

Scientific Knowledge Based

https://www.youtube.com/c/Lesics Physics and Basic Engineerings



http://www.ilectureonline.com/ (Advance Numerical -All Science +Maths)

https://www.learncbse.in/ (All basic subjects QA practices)













https://www.youtube.com/@Alilamedicalmedia (Important medical -Biology science simulations)




Demand Supply Markets : Educational purpose only








(As I am constantly trying to make things better and effective from the current Benchmark in Anthus and to make sure I - Not behind the world that is tending for tomorrow too ). Will explain more on -Saturday Morning session - How to Implement too

Latest - News can write from (here) -Suggested Links from onwards.


https://www.sciencedaily.com/ (Science News) - 4 news

https://techcrunch.com/ (Technology and Start-Up news) - 3 news


1)Mark possible keywords (and find meaning) Dictionary

2) Any new word / some complex world (seen earlier but not known well enough)

Mark and write about it

Can use Chat GPT (If parents allow) only for finding meanings and relevance, else can you use Dictionary (Any from google)

https://www.oxfordlearnersdictionaries.com/ (in context for wordings ) + Picture relevance (Google images associated with keywords)




Additional (in case no new different news can able to find ) & Writing parts

Speaking Tree -

https://www.ft.com/ (Financial Times)


Sample (for Reference)


Just Suggestion (If wish to ..)


Pin Interest

G-Images

Chat GPT

Youtubes (Multiple Free sources)

Slide Share +PPT

Kindle Books (+)

Mentor Resources -G Books + I Books (Around 3000+)


New Updates in Process : Lead with Time

Simulations +Observation

Practicals +Real Life case study

Scientific Mathematical Calculations

Integrations

Multi Dimension Image

Technology Advancements Nested thinking (TRIZ Thinking ways)

Competitiveness Analysis

Here's a curated list of open-source resources for experiments, simulations, and research across various fields, along with their potential usage: -If any place link is not there -then type on google and search (put little effort please)


1. ChemCollective Virtual Labs (chemcollective.org): Offers a range of virtual chemistry labs, including activities like textbook-style limiting reagents problems, DNA concentration predictions, thermochemistry exercises, and equilibrium calculations. Ideal for chemistry students and educators for simulation-based learning.

2. Virtual Fetal Pig Dissection (whitman.edu): A supplementary tool for exploring introductory mammalian anatomy and physiology. Useful for biology students and teachers as an alternative to physical dissection.

3. Whole Frog Project (froggy.lbl.gov): Utilizes high-resolution MRI imaging for exploring frog anatomy through 3D rendering software. It's beneficial for biology education, especially in studying amphibian anatomy.

4. ActivEpi (activepi.com): An electronic textbook for teaching epidemiology, suitable for students and educators in public health and related fields.

5. Modular Digital Course in Undergraduate Neuroscience Education (MDCUNE) (mdcune.psych.ucla.edu): Provides digital laboratory modules in neuroscience, which are great for neuroscience educators and students.

6. Algodoo (algodoo.com): A physics simulation software that allows users to design, construct, and explore the world of physics. It's a versatile tool for both education and entertainment in physics.

7. Open Simulation Interface (opensimulationinterface.github.io): A generic interface for environmental perception in automated driving functions in virtual scenarios, useful in engineering and autonomous driving research.

8. Flowsquare (flowsquare.com): A two-dimensional computational fluid dynamics (CFD) software for simulating non-reactive/reactive flows, ideal for engineering students and professionals.

9. NASA Open Science Data Repository (osdr.nasa.gov): Consists of integrated biological databases like Ames Life Sciences Data Archive and GeneLab. It's a valuable resource for space-related biological research.

10. Web Application for Simulation of Experimental Data (pablobernabeu.github.io): Developed in R, this application allows the creation of varied data sets for experimental sciences. It's useful for researchers in need of simulating data for multi-factor designs.

These resources span a wide range of disciplines and offer a variety of tools for virtual experimentation, simulation, and data analysis, catering to students, educators, and researchers in various fields.


:

1. Kaggle (kaggle.com): A platform offering diverse datasets for data science, with a variety of file types like SQLite, BigQuery, and CSVs, making it easy to use for many different industry areas.

2. Pew Research Center (pewresearch.org): Offers a large repository of high-caliber survey data covering a wide range of topics. Access to their datasets requires a free account.

3. Yelp (yelp.com): Provides open access to a substantial portion of their user-created business reviews, which is valuable for exploring data about businesses and customers.

4. Google Trends (trends.google.com): A great resource for data pertaining to internet search trends, especially useful for marketers, businesses, and data analysts.

5. Fedora Scientific (fedoraproject.org): A Linux distribution designed for enabling open science, ideal for science enthusiasts and researchers who prefer Linux environments.

6. F1000Research (f1000research.com): A scientific journal with a focus on open access and life sciences, operating differently than the average open access journal.

7. Open Source Malaria (opensourcemalaria.org): An international team of scientists working on open-source research for finding a malaria cure.

8. Mozilla's Science Lab: A hub for the open research community, addressing the bottlenecks slowing down scientific research.

9. Nature Methods (nature.com): A respected scientific journal that has transitioned to open science practices, enabling true reproducible research.

10. Apache Open Climate Workbench (climate.apache.org): A software library for climate model evaluation using model and observational datasets, aiding in Earth science research.

These resources span a wide range of disciplines and offer tools for data analysis, scientific computing, and research in fields like life sciences, earth sciences, and data science. They are valuable for researchers, educators, and students who are looking for open-source options for their projects and studies


1. Esri’s ArcGIS API for Python: Useful for geospatial data analysis, visualization, and space-time analysis. It integrates with Python for efficient data handling and analysis (Esri).

2. PsychoPy: A free package for behavioral science research, offering a wide range of functionality for different types of experiments (CELSS Lab at Columbia University).

3. LabVanced: An experiment builder that allows users to create experiments with a graphical interface. It's useful for those looking to collect data through online experiments (CELSS Lab at Columbia University).

4. Gorilla: Another experiment builder with a graphical interface, allowing for the easy creation of experiments and collection of data (CELSS Lab at Columbia University).

5. PsyToolkit: Offers tools for cognitive-psychological experiments and surveys, including personality tests, making it ideal for academic studies and teaching (CELSS Lab at Columbia University).

6. OpenSesame: A powerful, free experimental builder with a graphical interface, suitable for building a variety of studies (Open Science Knowledge Base).

7. Streamlit: An open-source Python library that allows for the easy creation of web apps for machine learning and data science. It's especially useful for rapid prototyping of Python modeling scripts (Towards AI).

8. Flask: A lightweight Python web application framework, perfect for creating more complex and production-friendly web applications (Towards AI).

9. Docker: A tool for creating, deploying, and running applications using containers. It ensures that applications are reproducible, which is crucial for research and development projects (Towards AI).

10. Spring Framework: An application development framework used for creating, testing, and deploying code. It is known for being powerful, lightweight, and flexible, making it a valuable tool for developers in various research fields (Rocket.Chat).

These resources span a range of disciplines from behavioral sciences to software development and data science, offering valuable tools for researchers, educators, and students.


1. GanttPRO: A project management tool ideal for researchers working in teams. It provides detailed collaboration features like task assignment, file attachment, and real-time notifications (Wordtune).

2. ResearchGate: This platform is a professional network for scientists and researchers, offering a space to connect with peers, share papers, and find collaborators (Octoparse).

3. CiteSeerx: A digital library and search engine primarily for computer and information science. It's useful for finding scientific and academic papers (Octoparse).

4. Scopus: Known as the largest abstract and citation database of peer-reviewed literature, Scopus is invaluable for literature searches across a wide range of subjects (Octoparse).

5. Emerald Group Publishing: Manages a portfolio of nearly 300 journals and more than 2,500 books, particularly useful in fields like management, business, education, and health care (Octoparse).

6. Web of Science: An online scientific citation indexing service, crucial for researchers who need to track citations and academic papers in various disciplines (Octoparse).

7. Zotero: A tool for collecting, organizing, annotating, and sharing research. It integrates with internet browsers for easy saving of articles and publications (Dovetail).

8. Paperpile: A reference management tool that integrates with Google Docs, streamlining the process of managing and citing papers (Dovetail).

9. Dovetail: Acts as a single source of truth for research, allowing users to collate and store data from various sources such as interviews, surveys, and focus groups (Dovetail).

10. Statcheck: A tool for automatically scanning manuscripts for statistical errors, particularly useful for recalculating p-values and ensuring statistical accuracy in manuscripts (Nature Index).


1. LabArchives: A leading electronic lab notebook that allows researchers to store, organize, and publish their research data. [LabArchives](https://www.labarchives.com/)

2. Open Science Framework (OSF): A free, open platform for managing and documenting various stages of research projects. [OSF](https://osf.io/)

3. Mendeley: A reference manager and academic social network that helps researchers organize their research, collaborate with others online, and discover the latest research. [Mendeley](https://www.mendeley.com/)

4. R and RStudio: R is a free software environment for statistical computing and graphics, while RStudio provides an integrated development environment for R. [R](https://www.r-project.org/) and [RStudio](https://www.rstudio.com/)

5. Overleaf: An online LaTeX editor that's easy to use, allowing for collaborative writing and publishing of scientific documents. [Overleaf](https://www.overleaf.com/)

6. Bioconductor: Provides tools for the analysis and comprehension of high-throughput genomic data in the R statistical programming environment. [Bioconductor](https://www.bioconductor.org/)

7. Git and GitHub: Git is a free and open-source distributed version control system, and GitHub is a web-based hosting service for version control using Git, which is particularly useful for source code management. [Git](https://git-scm.com/) and [GitHub](https://github.com/)

8. KNIME: An open-source data analytics, reporting, and integration platform, which integrates various components for machine learning and data mining. [KNIME](https://www.knime.com/)

9. Jupyter Notebook: An open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text. [Jupyter Notebook](https://jupyter.org/)

10. SciPy: An open-source Python library used for scientific and technical computing. [SciPy](https://www.scipy.org/)

These tools cover a range of functionalities from data analysis and management to collaboration and documentation, catering to various needs in the research process.


WRITING Reference :



“It is not because things are difficult that we do not dare; it is because we do not dare that things are difficult.”

Seneca

“It’s not how good you are. It’s how good you want to be.”

Paul Arden


 
 
 

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🌟 The Power of Asking the Right Questions 🌟
 

  • Know the right questions 🌱 to ask.

  • Ask them in the right order 📊 for clarity.

  • Don’t skip any ❓ to avoid blind spots.

  • Ask at the right time ⏱️ for maximum impact.
     

If not, you risk missing opportunities and being misguided by assumptions—don’t let a lack of questions make you a fool. 🙈

When your purpose is clear and focused 💪, the right questions will always guide you toward success 🎯.

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