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War of Colony – Halo tutorial: Tips and tricks to optimize your halo formation and strategy



As long as you have Colonial Affairs unlocked, you will be able to start colonizing - targets for colonization must be decentralized nations. The list of decentralized nations is set at the beginning of the game - once they are all colonized, there will be no more ways to establish a colony.




War of Colony – Halo tutorial



Establishing a colony is a simple task of clicking the Establish Colony button from the Diplomatic Lens at the bottom of the screen. A menu will show up, showing you all the possible targets for colonization available to you. Click one to begin colonizing, immediately getting a single province in the region. Slowly but surely, the rest of the region will start to get colonized, with the rate dictated by your colonial growth, which can be increased by leveling up your Colonial Affairs Institution.


Despite initial difficulties at contact due to the Lekgolo's alien methods of communication,[2] the Covenant incorporated the Lekgolo into their ranks in 784 BCE.[5] The Mgalekgolo gestalts, armed with thick armor plates and assault cannons, would come to serve the Covenant as shock troops. Even larger Lekgolo colony assemblages were weaponized as Covenant assault platforms, Scarab and the Harvester, the latter of which is operated by a meta-colony referred to as a Sbaolekgolo.[9] Individual Lekgolo worms, specifically conditioned not to ingest Forerunner alloys, were employed by the ascetic priests studying the Forerunner Dreadnought in High Charity.[8] A number of these Lekgolo stopped Mendicant Bias from taking off in the Forerunner Dreadnought by short circuiting the ship's systems, themselves dying in the process.[10]


The Lekgolo are characterized by their ability to form bonds with one another both physically and neurologically to form gestalt colonies with a singular personality; these communities, rather than individual Lekgolo eels, are considered the closest thing to a sapient Lekgolo "individual" that can be named.[14] Lekgolo are relatively unintelligent at the most basic level, but can form complex thoughts and emerge as a conscious individual when they combine into larger masses that communicate through chemical and electrical means. A colony's level of intelligence is generally dependent on the amount of neural mass present,[1] and can be scaled upward to a certain extent for increased intelligence. The neural net that Lekgolo colonies develop enables them to be incredibly strong and very sensitive to their surroundings.[2] These gestalts are capable of manifesting in several different forms according to what goal they are striving to achieve and the amount of Lekgolo worms that are present. The Covenant was aware of six different forms of Lekgolo colonies: Dipholekgolo, Mgalekgolo, Rhulolekgolo, Sbaolekgolo, Khantolekgolo, and Thanolekgolo. Each of these gestalts differs in size, mass, and complexity.[1] Because of the nature of the Lekgolo's compound intelligence and consciousness, they cannot be easily assimilated by the Flood, for while each individual worm may have its own central nervous system, the subsistence gestalts do not, and co-opted worms were never able to be used by the Flood to form the gestalts they would otherwise have. The Flood can still certainly use Lekgolo for their biomass, however.[15]


Subsistence gestalts arise from the aggregation of many individual Lekgolo. Distinct Mgalekgolo specifically form from a single large colony splitting in two, with their dorsal spikes containing the remnants of the last connections between the two parts of the colony.It takes 1 to 2 weeks for the Lekgolo to reproduce offspring.


After the following cutscene, you'll be guided through a brief tutorial where you'll learn about Classes, how they can be switched, and how you can set up Master Arts and Master Skills.


The Pursuer has decent health, and the speed of this robot is really quick. You usually see pursuer capturing a beacon, or somehow it's in your base equipped with gust and/or halo. When you see it capturing a beacon, fire at it before it enters the beacon, so it will activate stealth for 10 seconds. Capturing beacon needs 10 seconds to turn the color completely. So when it come out of stealth, shoot all you've got to him, try to kill it before it captures the beacon. If you find in your base, try to get a teammate to kill it. In a one on one, even you have Quantum Radar, the risk is pretty high. You and your teammate fire at it when it's coming, if he activates stealth, then hide behind cover. Walk around to try not to let him get you. After stealth gone, rush him as hard as you can, to not let it activate stealth again.


Citation: Bhoyar S, Godet I, DiGiacomo JW, Gilkes DM (2018) A software tool for the quantification of metastatic colony growth dynamics and size distributions in vitro and in vivo. PLoS ONE 13(12): e0209591.


Data Availability: All relevant data are within the paper and its Supporting Information files. The Matlab source code, instructions, a tutorial and image files can be freely downloaded at: We encourage the use and modification of the code and tailoring for unique assays.


Apart from in vivo analyses, this methodology can be applied to in vitro systems as well. Clonogenic assays are a widely-used tool for cancer biologists and are used to obtain the growth potential of cells and to quantify differences in sensitivity to cytotoxic agents [31]. However, clonogenic assays are not suitable for co-culturing different cell lines and are unable to visualize proteins of interest, and unable to accurately segment individual cells or colonies when they are close together. The assay described in this paper provides confluence, colony cell-count and size distributions, and reveals synergistic and co-culture effects in fluorescently labeled cells. Furthermore, the tool is able to quantify expression of immunofluorescently labeled proteins at the colony level. To demonstrate this, we used the proliferation marker Ki-67 as our protein of interest. The methods described here are especially relevant for lineage tracing in populations of cells labeled with a reporter construct [32,33].


Differences in median colony sizes were verified through a Wilcoxon Rank Sum test, and distributions were analyzed by the Kruskal-Wallis test. Ki-67 expression was analyzed using an unpaired t-test. All tests were evaluated through functions available in MATLAB (Mathworks, Natick, MA, USA) or GraphPad Prism (GraphPad Software, Inc., San Diego, CA, USA).


We developed a ready-to-use MATLAB script (available from GitHub: ) to determine colony size distributions, proliferation and to analyze protein expression at the colony level. To demonstrate the utility of the algorithm, we prepared fixed and stained colonies of GFP-expressing (GFP+) and DsRed-expressing (DsRed+) MCF7 cells. We introduced differences in growth rates and colony sizes between the GFP+ and DsRed+ cell lines by preculturing GFP+ cells in 2 nM Paclitaxel for 48 hours. DsRed+ cells were pre-cultured in drug-free media. Next, we mixed 2000 of each GFP+ and DsRed+ cells and plated them in 6-well plates. On day 2 and 4, cells were fixed, stained and imaged. Nuclei were stained with DAPI and the proliferation marker, Ki-67 (CY5). Images were taken in the DAPI, CY5, GFP and RFP channels. We observed that the GFP+ cells (which were pre-treated with Paclitaxel) formed smaller colonies with a lower proportion of Ki-67 expressing cells (Fig 1). Each image was analyzed using the following image-processing scheme. The image processing steps involved in segmenting fixed and immunostained colonies in vitro are given in Fig 2 and described below.


A: Nuclear staining (DAPI channel). B: Preprocessing steps and distance transform identifies watersheds. C: Segmentation of colonies by watershed algorithm. D: Individual colonies analyzed. E: DsRed and GFP signal captured in RFP and GFP channels respectively. F: DsRed+/GFP+ regions obtained by preprocessing steps and binarization. G: Segmented colonies classified as DsRed+/ GFP+ based on input from images F1 and F2. G: Cell count and area of individual colonies obtained from colony-level DAPI image. I: Ki-67 staining imaged in the CY5 channel. J: Regions of MCF7 cells expressing Ki-67 obtained by binarization. Scale bars: 5 mm (A, E, I, J), 1 mm (G, D).


A distance transform is then performed on the complement of the binarized image (Fig 2B), which effectively replaces the value of each pixel within a colony with the Euclidean distance to the nearest boundary. The image shown is inverted, and the intensity of the background pixels was raised to saturation (S2C and S2D Fig) The dark regions at the center of each colony function as catchment regions for a watershed segmentation step. This method takes advantage of the fact that the colonies are roughly circular. The top-hat filter applied in the preprocessing stage mitigates uneven illumination, which otherwise leads to a variation in greyscale intensity values and affects segmentation accuracy. This, and the smoothening effect of the Gaussian blur is sufficient to eliminate noise, which eliminates the need for a median filtering step, and ensures that the subsequent watershed segmentation step successfully identifies colony regions. Finally, we use an h-minima transform to suppress small minima which would otherwise lead to over-segmentation.


The watershed transform is a commonly used method for image segmentation. The algorithm views the subject image as a topographical map, viewing bright pixels as `high' and dark ones as `low'. It segments the image into catchment areas based on dark 'basins', which are then used as foci for segmenting objects corresponding to each basin [34,35]. In our application, we use a distance transform to obtain 'high' or bright regions, invert them so that they become 'basins', and subsequently use them as foci for segmenting colonies in vitro (Fig 2C). An example of the segmentation step is provided in S3 Fig, where a large group of connected colonies is accurately segmented into individual colonies. While the script works well with clustered or partially overlapping colonies, it cannot distinguish sheet-like areas or areas where multiple colonies may have fused into a `super-colony'. 2ff7e9595c


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