Eco friendly management of fungal seed borne pathogens through bio-agentsAnkit Chaudhari
Seed borne diseases causes heavy losses in the crops at all stages of growth like seed germination, seedling and maturity of plants.
Bio-control technologies have gained momentum in disease control of crop plants, in recent times as these technologies not only minimize or replace the usage of harmful chemical pesticides, but also found to be ecofriendly, environmentally safe, cheaper and efficient in certain disease control programmes.
Fungal bio-control agents like Trichoderma spp. successfully used for the control of many seed borne diseases caused by Aspergillus spp., Alternaria spp., Curvularia spp., Colletotrichum spp., Fusarium spp., Pyricularia spp., Helminthosporium spp. etc. in several crops.
Importance of non wood forest based industry in indianParvati Tamrakar
non- wood forest products, economic importance, socioeconomic benefits, tribal community, production and trade of nwfp- national and international, recent economic patterns of nwfp, india's noteworthy produce
This presentation is prepared for continuous evaluation for the subject Theories of Agricultural Resource Management -Bsc in Export Agriculture -Uva Wellassa University of Sri Lanka
Successful case studies of national as well as international IPM programmessharanabasapppa
Discovery of synthetic pesticides in 1940, the whole scenario of pest management has changed.
From late 1940 to mid 1960 has been called “the dark ages” of pest control.
The insecticidal properties of DDT (dichloro diphenyl trichlorethane) discovered by Paul Muller in 1939 triggered this “dark age” of pest control.
Resistance of pests to pesticides was observed, the minor pests to major pests due to killing beneficial insects.
Eco friendly management of fungal seed borne pathogens through bio-agentsAnkit Chaudhari
Seed borne diseases causes heavy losses in the crops at all stages of growth like seed germination, seedling and maturity of plants.
Bio-control technologies have gained momentum in disease control of crop plants, in recent times as these technologies not only minimize or replace the usage of harmful chemical pesticides, but also found to be ecofriendly, environmentally safe, cheaper and efficient in certain disease control programmes.
Fungal bio-control agents like Trichoderma spp. successfully used for the control of many seed borne diseases caused by Aspergillus spp., Alternaria spp., Curvularia spp., Colletotrichum spp., Fusarium spp., Pyricularia spp., Helminthosporium spp. etc. in several crops.
Importance of non wood forest based industry in indianParvati Tamrakar
non- wood forest products, economic importance, socioeconomic benefits, tribal community, production and trade of nwfp- national and international, recent economic patterns of nwfp, india's noteworthy produce
This presentation is prepared for continuous evaluation for the subject Theories of Agricultural Resource Management -Bsc in Export Agriculture -Uva Wellassa University of Sri Lanka
Successful case studies of national as well as international IPM programmessharanabasapppa
Discovery of synthetic pesticides in 1940, the whole scenario of pest management has changed.
From late 1940 to mid 1960 has been called “the dark ages” of pest control.
The insecticidal properties of DDT (dichloro diphenyl trichlorethane) discovered by Paul Muller in 1939 triggered this “dark age” of pest control.
Resistance of pests to pesticides was observed, the minor pests to major pests due to killing beneficial insects.
This lecture covers some nice stories about the origins of the words "genome" and the derived word "genomics". the lecture also introduces viral, bacterial, and eukaryotic genomes.
CAPFITOGEN Programme for the Strengthening of Capabilities in National Plant Genetic Resources Programmes, International Treaty on Plant Genetic Resources for Food and Agriculture - FAO
Dealing with the forest field study data Finding the data .docxrandyburney60861
Dealing with the forest
field study data
Finding the data for your focal species
1. Go on Canvas, Lab 10 folder, and download the spreadsheet with the data for your field
study time period (e.g. if you are in a B section, you will download the spreadsheet
Forest data - B sections - Monday 2pm).
2. The data for your focal species (in this example, R. ursinus) are in one of the
columns with the yellow label. E.g., R. ursinus (let’s assume that this is your group’s focal
species) is in column C. Data on abundance in the deciduous forest is in rows 11 - 71.
BIOL140 2019 - LABS 10+11 �1
If you scroll down, you’ll find data for the coniferous forest (here, rows 76 - 136).
Preparing the graphs for the presentation (with appropriately sized labels)
3. You will need to first get Excel to calculate the mean abundance for your focal
species (and it’s a good idea to also get the standard deviation) for the 60 quadrats
sampled. To do so, below quadrat #60 add a row for the mean and one for the SD. In the
appropriate cells (in your focal species column) have Excel calculate the mean and the
SD.
4. Do the same for the coniferous forest data (your mean and SD will be just below
the data in the last quadrat).
5. Find a clear space on the spreadsheet and set up a little ‘table’, similar to the one
shown in the figure below, where you’ll record the mean abundance for each of the two
sites and where you’ll have Excel calculate the standard deviation
BIOL140 2019- LABS 10+11 �2
6. To make your graph, proceed as you did for your Lab experiment results, but this
time we will use a ‘bar graph’ (known in Excel as ‘Column’ ‘Clustered column’. The error
bars should be the standard deviation. A few things to remember (that many groups missed
in their oral presentation:
❖ no title for the graphs (Excel will likely include a ‘Chart Title’; remove it)
❖ no ‘Excel legend’ (this is different from a figure legend…check the Conventions)
❖ yes proper axes labels! (If you have selected a graph style that does not give you
labels, you can add them in when you copy-paste your graph into your presentation
❖ A figure legend is optional.
BIOL140 2019 - LABS 10+11 �3
7. To format your graph such that it is suitable for the presentation, copy and paste it
into PowerPoint, ‘stretch it’ (to make it as large as possible), and don’t forget to make the
font size larger too! (It does not automatically get bigger as you ‘stretch’ the graph).
8. To change the font size you need to work in PowerPoint and:
❖ click on an axis label
❖ go to font>size and change the size to what you want it to be (recommended is 24, if
this looks really to big go with 20 — smaller fonts are very difficult to see from the back of
the room with the lighting available in the labs!)
❖ repeat with each axis label and with each axis.
It is also suggested that you change the colour of the bar graph to something very
visible that however does not mask the erro.
Introduction to 16S rRNA gene multivariate analysisJosh Neufeld
Short introductory talk on multivariate statistics for 16S rRNA gene analysis given at the 2nd Soil Metagenomics conference in Braunschweig Germany, December 2013. A previous talk had discussed quality filtering, chimera detection, and clustering algorithms.
So we were tasked to write scientific papers about the five ecosystems which we have sampled namely: Forest, Grassland, Stream, Coastal Marine, and Mangrove Ecosystems. But then since it was such a handful assignment, our teacher agreed that we can pick only two of these ecosystems that we'll make a scientific paper about and I chose Grassland and Coastal Marine Ecosystems.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
1. Plant Ecology
PBIO-425/525
Plant Ecology Laboratory
Forest Vegetation Sampling &
Point-centered Quarter Sampling Method
Introduction
The point-centered quarter (PCQ) method is one of the most frequently used distance methods
employed to sample plant communities (particularly forests). After a random point has been
located, the area around each point is split into four 90° quarters (quadrantsNOTE the "n"),
and the nearest tree (DBH ≥ 10 cm) sought in each quarter. Each tree is identified to species,
the distance from the point to the tree is recorded, and the DBH is recorded. To gain insight into
overstory/understory relations, one can also seek out the nearest sapling (DBH > 2.5 & < 10 cm)
in each quarter and record the same information as for trees.
For the purposes of this lab, we will address two questions: (1) Is the upper slope forest
community different than the lower slope forest community? (2) In the future, when the
overstory finally senesces or is disturbed, will the subsequent community at each slope position
be similar in composition to the present community or different?
Field Methods
1) Establish a 100 m transect along the elevational contour. There will be two or three
(depending upon the number of field teams) parallel transects, spaced 25m apart, on the
upper slope and two or three transects on the lower slope (4-6 transects total).
2) Place a PCQ sample unit 5 m out from the transect line at 0, 20, 40, 60, 80 and 100 m. To
enter an element of randomness into your sampling, flip a coin to determine whether you go
5 m to the left or 5 m to the right of the transect to establish each point.
3) Identify and measure the distance & DBH of the 4 nearest trees and 4 nearest saplings as
described above (use data sheets provided).
Analytical Methods
1) Provide and interpret various estimates of diversity (methods of your choice).
2) From the summarized raw data, determine the absolute and relative values for density,
dominance, and frequency, together with the importance value for each species, using the
equations shown on the next page of this handout.
Results
Provide separate tables summarizing vegetation data for the upper and lower slope. Provide a
nested bar graph with 2 bars per species depicting abundance at upper and lower slope
positions. Include any other tables or figures that you deem appropriate. Briefly survey the
eastern North America hardwood forest literature for papers you think are relevant to forest
structure and dynamics, effects of topography on species distribution, and forest succession.
3lab.doc
2. Plant Ecology
PBIO-425/525
To summarize your PCQ data proceed as follows (do separate analyses for trees and saplings):
1. Calculate the mean point-to-plant distance for the entire sample, regardless of species,
and record the value.
This value squared gives the mean area per plant. The density of plants in the area sampled is
then obtained by dividing the mean area per plant into the unit area on the basis of which
density is to be expressed (e.g., 1 ha). Since the same units must be used in both the
numerator and denominator, change 1 ha to 10,000 m².
Thus, the Average Density (AVGDEN) = 10,000 / (mean distance in m)².
2. Determine density by species. Count the number of individuals in your sample for each
species and record. Determine the total number of individuals counted (4 times the number of
points sampled). Thus, for each species,
Relative density (RELDEN) = (no. of indiv. of a sp. / total no. of indiv.) x 100
and
Density (DEN) = (RELDEN/100) x AVGDEN
3. Determine basal area by species. Start by converting diameter measures into basal areas
(BA = π r2). Calculate the mean basal area for each species (AVGBA). Thus, for each species,
Basal area (BA) = DEN x AVGBA
and Relative basal area (RELBA) = (BA / TOTBA) x 100
where TOTBA is the total basal area for all species (sum all BAs).
4. Determine frequency. For each species,
Frequency (FREQ) = (no. of points at which sp. occurs / total no. of pts. sampled)
and
Relative frequency (RELFREQ) = (FREQ / total FREQ for all spp.) x 100
5. Calculate an importance value (IV) and relative importance value (RIV) for each species.
Where IV = RELDEN + RELFRQ + RELBA;
RIV = (RELDEN + RELFRQ + RELBA)/3
Caution:
1) The number of quarters sampled is not important for calculations, only the number of points.
2) Round all calculated values to 2 decimal places. Round all relativized values to the nearest
whole number. Check that columns with relativized numbers sum to ca. 100.
3lab.doc