Blob Body Type Explanations
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When the mesh body type is set to 'blob', nodal points are treated as a spherical data set with an estimated center point. During interpolation, the length of radius vectors to unknown points are calculated using different algorithms like Inverse Distance Weighting or iterative algorithms. Adaptation of these algorithms to the spherical coordinate system involves first mapping points to Cartesian coordinates before processing them as usual.
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than a grid space areproved in calculations.
O026084087
This document analyzes node localization in wireless sensor networks. It compares three range-based localization algorithms (TOA, AOA, RSSI) based on their standard deviation of localization error under varying network parameters. Through simulations, it finds that the TOA algorithm generally provides the lowest error compared to the other two algorithms. Specifically, it finds that standard deviation decreases with increasing network density and anchor node density, but first decreases and then increases with network size. It concludes that the TOA algorithm provides the best accuracy for localization based on its analysis of parameter effects.
Localization with mobile anchor points in wireless sensor networks
The document describes a range-free localization scheme that uses mobile anchor points equipped with GPS to periodically broadcast their positions. Sensor nodes calculate their own positions based on the localization information from at least three mobile anchors without needing additional interactions. Simulation results showed the approach achieved fine-grained accuracy and was distributed, scalable, effective and power efficient. It performed better than other range-free localization mechanisms.
Iaetsd improving the location of nodes in wireless ad
The document proposes an Improvised LAL approach to localize nodes in wireless ad hoc and sensor networks. It aims to identify and convert non-localizable nodes to localizable nodes in a single round. The approach has three main modules: 1) Identifying localizable and non-localizable nodes, 2) Analyzing the network structure using a distance graph, and 3) Making adjustments to distinctively convert non-localizable nodes. Additional techniques like add-heuristic and geographical routing are used. The approach decomposes the distance graph and manages components as a tree to efficiently make adjustments along paths from roots to leaves. This allows all nodes to be localized using standard localization algorithms.
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Q026201030106
This document summarizes a distributed localization algorithm for wireless sensor networks. It begins by introducing the problem of localizing unknown sensor nodes in a wireless network. It then describes a discrete model that partitions the sensor field into cells and restricts communication to a set number of neighboring cells. The core of the document presents a simple distributed localization algorithm where unknown nodes estimate their position based on information received from neighboring nodes that know their position. It analyzes the performance of the algorithm through simulations with varying numbers of total nodes and beacon nodes. The error of the algorithm's position estimates increases as the number of nodes grows but does not change significantly when the number of beacon nodes is over 10.
Q026201030106
This document summarizes a distributed localization algorithm for wireless sensor networks. It begins by introducing wireless sensor networks and noting that localization of sensor nodes is an important first task. It then discusses the benefits of distributed algorithms over centralized algorithms for localization, including scalability, reliability, and energy efficiency. The document goes on to describe a basic distributed localization algorithm that works in a discrete model where the operating region is divided into cells and nodes can communicate with others within a certain number of cells. The goals are to design a distributed algorithm, analyze its complexity and errors, and determine an optimal number of "known nodes" to minimize errors.
A Novel Range-Free Localization Scheme for Wireless Sensor Networks
This paper present a low-cost yet effective localization scheme for the wireless sensor networks. There are many studies in the literature of locating the sensors in the wireless sensor networks. Most of them require either installing extra hardware or having a certain amount of sensor nodes with known positions. The localization scheme we propose in this paper is range-free, i.e., not requiring extra hardware devices, and meanwhile it only needs two anchor nodes with known position. Firstly, we install the first anchor node at the lower left corner (Sink X) and the other anchor node at the lower right corner (Sink Y). Then we calculate the minimum hop counts for each unknown node to both Sink X and Sink Y. According to the minimum hop count pair to Sink X and Sink Y of each node, we can virtually divide the monitored region into zones. We then estimate the coordinate of each sensor depending on its located zone. Finally, we adjust the location estimation of each sensor according to its relative position in the zone. We simulate our proposed scheme and the well-known DV-Hop method. The simulation results show that our proposed scheme is superior to the DV-Hop method under both low density and high density sensor deployments.
Optimum Sensor Node Localization in Wireless Sensor Networks
Abstract: Scientists, engineers, and researchers use wireless sensor networks (WSN) for a wide array of applications. Many of these applications rely on knowledge of the precise position of each node. An optimum localization algorithm can be used for determining the position of nodes in a wireless sensor network. This paper provides an overview of different approach of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Experiments were performed in a testbed area containing anchor and blind nodes deployed in it to characterize the pathloss exponent and to determine the localization error of the algorithm. Details regarding the implementation of new algorithm are also discussed in this paper.
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications.
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks
In recent years, the Mobile Wireless Sensor Network
is the emerging solution for monitoring of a specified region of
interest. Several anomalies can occur in WSNs that impair their
desired functionalities resulting in the formation of different
kinds of holes, namely: coverage holes, routing holes. Our
ultimate aim is to cover total area without coverage hole in
wireless sensor networks. We propose a comprehensive solution,
called holes detection and healing. We divided our proposed
work into two phases. The first phase consists of three sub- tasks;
Hole-identification, Hole-discovery and border detection. The
second phase treats the Hole-healing with novel concept, hole
healing area. It consists of two sub-tasks; Hole healing area
determination and node relocation.
TARGET LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON RECEIVED SIGNAL STRE...
We consider the problem of localizing a target taking the help of a set of anchor beacon nodes. A small
number of beacon nodes are deployed at known locations in the area. The target can detect a beacon
provided it happens to lie within the beacon’s transmission range. Thus, the target obtains a measurement
vector containing the readings of the beacons: ‘1’ corresponding to a beacon if it is able to detect the
target, and ‘0’ if the beacon is not able to detect the target. The goal is twofold: to determine the location
of the target based on the binary measurement vector at the target; and to study the behaviour of the
localization uncertainty as a function of the beacon transmission range (sensing radius) and the number of
beacons deployed. Beacon transmission range means signal strength of the beacon to transmit and receive
the signals which is called as Received Signal Strength (RSS). To localize the target, we propose a gridmapping
based approach, where the readings corresponding to locations on a grid overlaid on the region
of interest are used to localize the target. To study the behaviour of the localization uncertainty as a
function of the sensing radius and number of beacons, extensive simulations and numerical experiments
are carried out. The results provide insights into the importance of optimally setting the sensing radius and
the improvement obtainable with increasing number of beacons.
Similar to Blob Body Type Explanations (20)
Comparison of different neural networks for iris recognition
Comparison of different neural networks for iris recognition
Artificial Bee Colony algorithm for Localization in Wireless Sensor Networks
Artificial Bee Colony algorithm for Localization in Wireless Sensor Networks
IRJET- Clustering the Real Time Moving Object Adjacent Tracking
IRJET- Clustering the Real Time Moving Object Adjacent Tracking
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
Performance Analysis of DV-Hop Localization Using Voronoi Approach
Performance Analysis of DV-Hop Localization Using Voronoi Approach
Virtual 2 d positioning system by using wireless sensors in indoor environment
Virtual 2 d positioning system by using wireless sensors in indoor environment
Localization with mobile anchor points in wireless sensor networks
Localization with mobile anchor points in wireless sensor networks
Iaetsd improving the location of nodes in wireless ad
Iaetsd improving the location of nodes in wireless ad
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
A Novel Range-Free Localization Scheme for Wireless Sensor Networks
A Novel Range-Free Localization Scheme for Wireless Sensor Networks
Optimum Sensor Node Localization in Wireless Sensor Networks
Optimum Sensor Node Localization in Wireless Sensor Networks
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks
Redundant Actor Based Multi-Hole Healing System for Mobile Sensor Networks
TARGET LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON RECEIVED SIGNAL STRE...
TARGET LOCALIZATION IN WIRELESS SENSOR NETWORKS BASED ON RECEIVED SIGNAL STRE...
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LSS Arch 1.6
The document discusses new features in LSS ARCH 1.6 including creating floor levels and drawing on multiple levels simultaneously, creating plan scenes of master levels, adjusting settings for filled section objects using the properties dialog, creating filled sections using the LSS ARCH extension, updating filled sections by right clicking, interacting with openings that contain dynamic components using the dynamic components toolbar, and adjusting settings for dynamic component stuffing using the component options dialog.
Lss Arch 1.5.x
This document provides an overview of new features in LSS ARCH 1.5.X, including support for high DPI monitors, direction locking while drawing or dragging, automatic minimization of tool dialogs when drawing starts, automatic erasing of sub-objects, improved texture alignment and positioning options using functions, and enhanced explode reveals of openings to help third party extensions. Contact information is also provided for the LSS ARCH website, help system, extension warehouse page, YouTube channel, and blog.
LSS Arch 1.5 Overview
This document provides an overview of new features in LSS ARCH 1.5, including the ability to toggle level locking, select wall alignment, offset segments and contours, merge and join walls, add profile offsets, adjust sill heights, add 2D opening symbols, load point clouds from files, and access additional resources through a new About window. It also provides links to the LSS ARCH website, help system, Extension Warehouse page, YouTube channel, and blog for additional information.
LSS Arch 1.4
The document summarizes new features in LSS ARCH 1.4, including a "Layers" dialog to adjust visibility of objects, differentiating floors, custom layers, locking object levels while drawing, shape and tool presets to choose existing profiles and openings instead of editing parameters, isolines contour tool to use mesh horizontals as contour lines, utilities to make backup copies of objects and restore from backups, convert imported IFC objects to LSS ARCH objects, attach IFC attributes to objects in batch, and explode complex nested structures to simple entities located in the model's root.
Lss arch 1.3
LSS ARCH 1.3 is an update to 3D modeling software that includes new tools for surface modeling, contour modeling, and modeling linear structures. It introduces a blob body type, contour tool, meta-object capabilities for contours and beams, and a divided segment type for segments in addition to arcs and curves. The update also provides links to the software's website, extension warehouse, YouTube channel, and blog for additional information.
Lss arch 1.2
Overview of features introduced in version 1.2 of LSS Arch extension for SketchUp.
First version allowed modeling of basic structural elements such as columns, beams, walls etc. New version provides tools for advanced geometry modeling and introduces grid 'meta-object'.
Lss arch 1.0
'LSS Arch' is a commercial extension for SketchUp, which allows to draw, edit and list basic building elements, such as walls, columns, beams, slabs etc.
Lss zone
'LSS Zone' is an extension for Sketchup, which allows to create, store and manage information about rooms.
For more information visit: https://sites.google.com/site/lssoft2011/home/lss-zone
Lss chronolux 1.2 features overview
The document describes new features in Chronolux software version 1.2, including colored representations of insolation test results, gradient maps, and labeling of test points to improve visualization. It also details a new method to copy lists of processed test points between the Chronolux and LayOut programs for further analysis.
Projects 2009-2013
The document outlines various real estate projects completed by Kirill Bannov between 2009-2013, including residential complexes, retail stores, and commercial offices. It provides details on each project such as location, client, total area, status (concept, under construction, built). The projects span cities in Russia like Chelyabinsk, Orsk and involve large clients such as X5 Retail Group and Metchelstroy Ltd.
Lss Matrix Usage Overview
This document provides an overview and instructions for using the LSS Matrix plugin in SketchUp. It describes how to install the plugin by unpacking files into the Plugins and Resources folders. It explains how to enable the LSS Matrix toolbar and make an initial copy and controlling copies before launching the plugin dialog. The dialog is used to pick instances, adjust settings, and apply the array. Post processing capabilities allow editing properties, refreshing arrays manually or automatically on changes. Feedback can be provided on listed websites and blogs.
Chronolux 1.1 Updates Overview
Updates overview of Chronolux for Sketchup plugin.
Version 1.1 updates.
New features:
- Interactive Resize Tool
- Pick Test Surface Tool
- Pick Window Face Tool
Updates:
- Global Settings dialog
- Time Settings dialog
Chronolux 1 0_for_sketchup_8_m1
Chronolux 1.0 is a Sketchup extension that allows users to test solar insolation and sky view factor (SVF) within a 3D model. It provides interactive tools to calculate duration of insolation and SVF at any pointer position. It can also test duration of insolation over an area defined by a face. Results can be presented graphically or in a report of processed test points. Settings like time period and accuracy can be customized. The extension includes help documentation and an instructor to guide use of the tools.
Chronolux 1 0_for_sketchup_8_m1_ru
Презентация расширения Chronolux 1.0. для Google Sketchup. Обзор возможностей программы по расчету инсоляции и геометрического КЕО
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Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Wereport the study of a huge optical intraday flare on 2021 November 12 at 2 a.m. UT in the blazar OJ287. In the binary black hole model, it is associated with an impact of the secondary black hole on the accretion disk of the primary. Our multifrequency observing campaign was set up to search for such a signature of the impact based on a prediction made 8 yr earlier. The first I-band results of the flare have already been reported by Kishore et al. (2024). Here we combine these data with our monitoring in the R-band. There is a big change in the R–I spectral index by 1.0 ±0.1 between the normal background and the flare, suggesting a new component of radiation. The polarization variation during the rise of the flare suggests the same. The limits on the source size place it most reasonably in the jet of the secondary BH. We then ask why we have not seen this phenomenon before. We show that OJ287 was never before observed with sufficient sensitivity on the night when the flare should have happened according to the binary model. We also study the probability that this flare is just an oversized example of intraday variability using the Krakow data set of intense monitoring between 2015 and 2023. We find that the occurrence of a flare of this size and rapidity is unlikely. In machine-readable Tables 1 and 2, we give the full orbit-linked historical light curve of OJ287 as well as the dense monitoring sample of Krakow.
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureInternational Food Policy Research Institute- South Asia Office
PPT on Alternate Wetting and Drying presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024. ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
SDSS1335+0728: The awakening of a ∼ 106M⊙ black hole⋆
Context. The early-type galaxy SDSS J133519.91+072807.4 (hereafter SDSS1335+0728), which had exhibited no prior optical variations during the preceding two decades, began showing significant nuclear variability in the Zwicky Transient Facility (ZTF) alert stream from December 2019 (as ZTF19acnskyy). This variability behaviour, coupled with the host-galaxy properties, suggests that SDSS1335+0728 hosts a ∼ 106M⊙ black hole (BH) that is currently in the process of ‘turning on’. Aims. We present a multi-wavelength photometric analysis and spectroscopic follow-up performed with the aim of better understanding the origin of the nuclear variations detected in SDSS1335+0728. Methods. We used archival photometry (from WISE, 2MASS, SDSS, GALEX, eROSITA) and spectroscopic data (from SDSS and LAMOST) to study the state of SDSS1335+0728 prior to December 2019, and new observations from Swift, SOAR/Goodman, VLT/X-shooter, and Keck/LRIS taken after its turn-on to characterise its current state. We analysed the variability of SDSS1335+0728 in the X-ray/UV/optical/mid-infrared range, modelled its spectral energy distribution prior to and after December 2019, and studied the evolution of its UV/optical spectra. Results. From our multi-wavelength photometric analysis, we find that: (a) since 2021, the UV flux (from Swift/UVOT observations) is four times brighter than the flux reported by GALEX in 2004; (b) since June 2022, the mid-infrared flux has risen more than two times, and the W1−W2 WISE colour has become redder; and (c) since February 2024, the source has begun showing X-ray emission. From our spectroscopic follow-up, we see that (i) the narrow emission line ratios are now consistent with a more energetic ionising continuum; (ii) broad emission lines are not detected; and (iii) the [OIII] line increased its flux ∼ 3.6 years after the first ZTF alert, which implies a relatively compact narrow-line-emitting region. Conclusions. We conclude that the variations observed in SDSS1335+0728 could be either explained by a ∼ 106M⊙ AGN that is just turning on or by an exotic tidal disruption event (TDE). If the former is true, SDSS1335+0728 is one of the strongest cases of an AGNobserved in the process of activating. If the latter were found to be the case, it would correspond to the longest and faintest TDE ever observed (or another class of still unknown nuclear transient). Future observations of SDSS1335+0728 are crucial to further understand its behaviour. Key words. galaxies: active– accretion, accretion discs– galaxies: individual: SDSS J133519.91+072807.4
Male reproduction physiology by Suyash Garg .pptx
Physiology of Male reproduction.
Video mentioned at page no. 23 as summary for better understanding
JAMES WEBB STUDY THE MASSIVE BLACK HOLE SEEDS
The pathway(s) to seeding the massive black holes (MBHs) that exist at the heart of galaxies in the present and distant Universe remains an unsolved problem. Here we categorise, describe and quantitatively discuss the formation pathways of both light and heavy seeds. We emphasise that the most recent computational models suggest that rather than a bimodal-like mass spectrum between light and heavy seeds with light at one end and heavy at the other that instead a continuum exists. Light seeds being more ubiquitous and the heavier seeds becoming less and less abundant due the rarer environmental conditions required for their formation. We therefore examine the different mechanisms that give rise to different seed mass spectrums. We show how and why the mechanisms that produce the heaviest seeds are also among the rarest events in the Universe and are hence extremely unlikely to be the seeds for the vast majority of the MBH population. We quantify, within the limits of the current large uncertainties in the seeding processes, the expected number densities of the seed mass spectrum. We argue that light seeds must be at least 103 to 105 times more numerous than heavy seeds to explain the MBH population as a whole. Based on our current understanding of the seed population this makes heavy seeds (Mseed > 103 M⊙) a significantly more likely pathway given that heavy seeds have an abundance pattern than is close to and likely in excess of 10−4 compared to light seeds. Finally, we examine the current state-of-the-art in numerical calculations and recent observations and plot a path forward for near-future advances in both domains.
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
学校原件一模一样【微信：741003700 】《(salfor毕业证书)索尔福德大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
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◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
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Pests of Storage_Identification_Dr.UPR.pdf
InIndia-post-harvestlosses-unscientificstorage,insects,rodents,micro-organismsetc.,accountforabout10percentoftotalfoodgrains
Graininfestation
Directdamage
Indirectly
•theexuviae,skin,deadinsects
•theirexcretawhichmakefoodunfitforhumanconsumption
About600speciesofinsectshavebeenassociatedwithstoredgrainproducts
100speciesofinsectpestsofstoredproductscauseeconomiclosses
Sustainable Land Management - Climate Smart Agriculture
Sustainable Land Management - Climate Smart AgricultureInternational Food Policy Research Institute- South Asia Office
PPT on Sustainable Land Management presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...
MICROBIAL INTERACTION PPT/ MICROBIAL INTERACTION AND THEIR TYPES // PLANT MIC...ABHISHEK SONI NIMT INSTITUTE OF MEDICAL AND PARAMEDCIAL SCIENCES , GOVT PG COLLEGE NOIDA
Microbial interaction
Microorganisms interacts with each other and can be physically associated with another organisms in a variety of ways.
One organism can be located on the surface of another organism as an ectobiont or located within another organism as endobiont.
Microbial interaction may be positive such as mutualism, proto-cooperation, commensalism or may be negative such as parasitism, predation or competition
Types of microbial interaction
Positive interaction: mutualism, proto-cooperation, commensalism
Negative interaction: Ammensalism (antagonism), parasitism, predation, competition
I. Mutualism:
It is defined as the relationship in which each organism in interaction gets benefits from association. It is an obligatory relationship in which mutualist and host are metabolically dependent on each other.
Mutualistic relationship is very specific where one member of association cannot be replaced by another species.
Mutualism require close physical contact between interacting organisms.
Relationship of mutualism allows organisms to exist in habitat that could not occupied by either species alone.
Mutualistic relationship between organisms allows them to act as a single organism.
Examples of mutualism:
i. Lichens:
Lichens are excellent example of mutualism.
They are the association of specific fungi and certain genus of algae. In lichen, fungal partner is called mycobiont and algal partner is called
II. Syntrophism:
It is an association in which the growth of one organism either depends on or improved by the substrate provided by another organism.
In syntrophism both organism in association gets benefits.
Compound A
Utilized by population 1
Compound B
Utilized by population 2
Compound C
utilized by both Population 1+2
Products
In this theoretical example of syntrophism, population 1 is able to utilize and metabolize compound A, forming compound B but cannot metabolize beyond compound B without co-operation of population 2. Population 2is unable to utilize compound A but it can metabolize compound B forming compound C. Then both population 1 and 2 are able to carry out metabolic reaction which leads to formation of end product that neither population could produce alone.
Examples of syntrophism:
i. Methanogenic ecosystem in sludge digester
Methane produced by methanogenic bacteria depends upon interspecies hydrogen transfer by other fermentative bacteria.
Anaerobic fermentative bacteria generate CO2 and H2 utilizing carbohydrates which is then utilized by methanogenic bacteria (Methanobacter) to produce methane.
ii. Lactobacillus arobinosus and Enterococcus faecalis:
In the minimal media, Lactobacillus arobinosus and Enterococcus faecalis are able to grow together but not alone.
The synergistic relationship between E. faecalis and L. arobinosus occurs in which E. faecalis require folic acid
Summary Of transcription and Translation.pdf
Hello Everyone Here We are Sharing You with The process of protien Synthesis in very short points you will be Able to understand It Very well
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Storagedeteriorationisanyformoflossinquantityandqualityofbio-materials.
Themajorcausesofdeteriorationinstorage
•Physical
•Biological
•Mechanical
•Chemical
Storageonlypreservesquality.Itneverimprovesquality.
Itisadvisabletostartstoragewithqualityfoodproduct.Productwithinitialpoorqualityquicklydepreciates
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Clinical periodontology and implant dentistry 2003.pdf
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Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Evidence of Jet Activity from the Secondary Black Hole in the OJ 287 Binary S...
Alternate Wetting and Drying - Climate Smart Agriculture
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ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
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Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
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Immersive Learning That Works: Research Grounding and Paths Forward
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Introduction_Ch_01_Biotech Biotechnology course .pptx
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11.1 Role of physical biological in deterioration of grains.pdf
Blob Body Type Explanations
- 2. BASIC IDEA When mesh body type is set to 'blob', extension treats nodal points as a spherical data set.
- 3. Extension estimates position of an average point from given nodal points and places center of a spherical data set at it. BASIC IDEA
- 4. During interpolation length of radius vectors to unknown points are calculated according to selected interpolation algorithm. BASIC IDEA
- 5. Inverse Distance Weighting IDW ALGORITHM
- 6. IDW ALGORITHM Inverse Angle Weighting (IAW) would be a more accurate name because algorithm actually uses angle to measure 'amount of proximity'
- 7. 'Average' and 'minimize' algorithms ITERATIVE ALGORITHMS
- 8. First stage is a preliminary calculation, which sets the same length to a radius vector to a point being calculated as a length of a vector to a closest* known nodal point. ITERATIVE ALGORITHMS * - «closest» in terms of spherical coordinate system here
- 9. The second stage is an iterative smoothing itself: points within a cell size angle from known points stay where they are, others gradually move along their radius vectors. ITERATIVE ALGORITHMS
- 10. So the process is similar to the one that takes place during conventional 'terrain-like' mesh processing. It is just adapted a bit for spherical coordinate system. ITERATIVE ALGORITHMS
- 11. TREND AND PREDICT Mapped surface
- 12. Adaptation of these algorithms for spherical coordinate system is a bit more tricky. Extension maps given points to Cartesian coordinate system at first... TREND AND PREDICT
- 13. TREND AND PREDICT ...then processes mapped set as usual.
- 14. IDW VS PREDICT Radius vector to each given nodal point is normal to a surface tangent plane at this point, when algorithm is set to IDW. So known points are local extrema. IDW
- 15. IDW VS PREDICT The idea of 'predict' algorithm is to estimate surface tangent planes at given nodal points. 'Predict'
- 16. IDW VS PREDICT Known points are not necessarily local extrema in case when 'predict' algorithm is chosen so result of interpolation can be more convincing.