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@.18_jr: انا الله وانا اليه راجعون🖤😔. #صۆفَيَ #استشهاد_النبي_الأعظم #ياصاحب_الزمان_ادركنا #اكسبلورexplore #fapyシ

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صۆفَيَ ☪︎
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Tuesday 11 August 2026 18:35:20 GMT
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يارسول الله 💔
2026-08-11 19:13:25
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Obito Uchiha dreamed of becoming Hokage and admired Minato Namikaze as the greatest ninja he had ever known. His cheerful personality inspired everyone around him. Minato recognized Obito's potential and believed that kindness was his greatest strength. He treated every student with patience and respect, encouraging them to protect others. A tragic mission changed Obito's life forever. Believing he had been abandoned, he fell into darkness and embraced Madara Uchiha's vision of a false peace. Despite becoming one of the greatest threats to the shinobi world, a part of Obito always remembered the values Minato had taught him. His heart was never completely consumed by hatred. Minato never stopped believing that Obito could return to the right path. Even after discovering the masked enemy was his former student, he felt sorrow more than anger. Their battle during the Fourth Great Ninja War was deeply emotional because it was not only a fight between enemies but also between a teacher and the student he had lost. Sasuke Uchiha grew up carrying the burden of his clan's destruction. His desire for revenge drove him to seek greater power at any cost. Obito saw his own pain reflected in Sasuke. He revealed the truth about Itachi Uchiha, knowing it would completely change Sasuke's view of the Hidden Leaf Village. After learning the truth, Sasuke turned his hatred toward Konoha. Obito took advantage of that anger to move his own plans forward. Although Obito influenced Sasuke's choices, Sasuke always made his own decisions. His strong will prevented anyone from controlling him completely. Minato believed that true strength came from protecting precious people rather than living for revenge. This belief stood in complete contrast to Obito's ideals at the time. During the Fourth Great Ninja War, Minato fought alongside the Allied Shinobi Forces to stop Obito and protect the future of the ninja world. Obito eventually realized that Naruto represented the person he had once dreamed of becoming. Naruto's determination slowly shattered the darkness in Obito's heart. Sasuke also witnessed Naruto's unwavering faith in friendship and perseverance. Those experiences gradually changed the direction of his life. Obito sacrificed himself to protect Naruto and Kakashi, proving that the goodness within him had finally returned after years of regret. Minato remained a symbol of hope, wisdom, and selflessness until the very end. His legacy continued to inspire Naruto and countless shinobi. Sasuke accepted his past instead of being controlled by it. He chose the difficult path of redemption and dedicated himself to protecting the world from the shadows. The stories of Obito, Minato, and Sasuke show that even those consumed by pain can find redemption through hope, sacrifice, and the bonds they share with others.#obito #minato #naruto #sasuke #animeedit
Obito Uchiha dreamed of becoming Hokage and admired Minato Namikaze as the greatest ninja he had ever known. His cheerful personality inspired everyone around him. Minato recognized Obito's potential and believed that kindness was his greatest strength. He treated every student with patience and respect, encouraging them to protect others. A tragic mission changed Obito's life forever. Believing he had been abandoned, he fell into darkness and embraced Madara Uchiha's vision of a false peace. Despite becoming one of the greatest threats to the shinobi world, a part of Obito always remembered the values Minato had taught him. His heart was never completely consumed by hatred. Minato never stopped believing that Obito could return to the right path. Even after discovering the masked enemy was his former student, he felt sorrow more than anger. Their battle during the Fourth Great Ninja War was deeply emotional because it was not only a fight between enemies but also between a teacher and the student he had lost. Sasuke Uchiha grew up carrying the burden of his clan's destruction. His desire for revenge drove him to seek greater power at any cost. Obito saw his own pain reflected in Sasuke. He revealed the truth about Itachi Uchiha, knowing it would completely change Sasuke's view of the Hidden Leaf Village. After learning the truth, Sasuke turned his hatred toward Konoha. Obito took advantage of that anger to move his own plans forward. Although Obito influenced Sasuke's choices, Sasuke always made his own decisions. His strong will prevented anyone from controlling him completely. Minato believed that true strength came from protecting precious people rather than living for revenge. This belief stood in complete contrast to Obito's ideals at the time. During the Fourth Great Ninja War, Minato fought alongside the Allied Shinobi Forces to stop Obito and protect the future of the ninja world. Obito eventually realized that Naruto represented the person he had once dreamed of becoming. Naruto's determination slowly shattered the darkness in Obito's heart. Sasuke also witnessed Naruto's unwavering faith in friendship and perseverance. Those experiences gradually changed the direction of his life. Obito sacrificed himself to protect Naruto and Kakashi, proving that the goodness within him had finally returned after years of regret. Minato remained a symbol of hope, wisdom, and selflessness until the very end. His legacy continued to inspire Naruto and countless shinobi. Sasuke accepted his past instead of being controlled by it. He chose the difficult path of redemption and dedicated himself to protecting the world from the shadows. The stories of Obito, Minato, and Sasuke show that even those consumed by pain can find redemption through hope, sacrifice, and the bonds they share with others.#obito #minato #naruto #sasuke #animeedit
Alice you've been through so much... #IdentityV #idv #第五人格 #creatorsearchinsights #idvedit @Kami Hearts ♥️
Alice you've been through so much... #IdentityV #idv #第五人格 #creatorsearchinsights #idvedit @Kami Hearts ♥️
#vise #prt #fyp #barca #N
#vise #prt #fyp #barca #N
i loveeeee
i loveeeee
Title: Watch real 5-axis linkage machining process on site One-time clamping forming avoids repeated positioning deviation. Strict mid-process inspection controls tiny dimension changes. Various alloy materials can be processed according to your drawings. #FiveAxisWorkshop #MetalProcessing #EngineeringParts #PrecisionMachining #industrialcnc
Title: Watch real 5-axis linkage machining process on site One-time clamping forming avoids repeated positioning deviation. Strict mid-process inspection controls tiny dimension changes. Various alloy materials can be processed according to your drawings. #FiveAxisWorkshop #MetalProcessing #EngineeringParts #PrecisionMachining #industrialcnc
Why are quants cautious about Monte Carlo simulations? 1. It samples your assumptions, it cannot check them. A wrong model produces ten thousand wrong paths. 2. Many risk simulations still assume Gaussian returns, and many empirical return series show power-law tails. Under a Gaussian, the 1987 crash was a roughly 20 sigma event with tail probability around 10^-89. Reality is clearly heavier-tailed than that. 3. Sampling error shrinks as sigma over root N, but parameter error shrinks as sigma over root T, where T is the length of your data, not the number of runs. A million paths give a very precise answer to an assumed question. 4. The ensemble mean is nobody's path. For multiplicative wealth, the ensemble mean grows like e^(mu t) while the typical path grows at rate mu minus sigma squared over two, so the ensemble mean can rise while the typical path declines. 5. Independent draws have no memory. Real returns show volatility clustering, so iid simulations understate how long and how violent crises are. 6. In low dimension many problems have closed forms or efficient deterministic methods. Monte Carlo earns its keep in high dimension, where classical grid schemes blow up and its standard error stays O(sigma/root N) regardless of dimension. -> Monte Carlo is a valid numerical integrator under the model you feed it; the failures here are failures of inputs and interpretation, not of the method itself. The ergodicity-economics reading of point 4 is debated among economists, the math itself is standard. References: Peters, Nature Physics (2019); Gabaix, Gopikrishnan, Plerou and Stanley, Nature (2003); Mandelbrot, Journal of Business (1963); Merton, JFE (1980); Cont, Quantitative Finance (2001). #finance #quant #trading #algotrading #stocks
Why are quants cautious about Monte Carlo simulations? 1. It samples your assumptions, it cannot check them. A wrong model produces ten thousand wrong paths. 2. Many risk simulations still assume Gaussian returns, and many empirical return series show power-law tails. Under a Gaussian, the 1987 crash was a roughly 20 sigma event with tail probability around 10^-89. Reality is clearly heavier-tailed than that. 3. Sampling error shrinks as sigma over root N, but parameter error shrinks as sigma over root T, where T is the length of your data, not the number of runs. A million paths give a very precise answer to an assumed question. 4. The ensemble mean is nobody's path. For multiplicative wealth, the ensemble mean grows like e^(mu t) while the typical path grows at rate mu minus sigma squared over two, so the ensemble mean can rise while the typical path declines. 5. Independent draws have no memory. Real returns show volatility clustering, so iid simulations understate how long and how violent crises are. 6. In low dimension many problems have closed forms or efficient deterministic methods. Monte Carlo earns its keep in high dimension, where classical grid schemes blow up and its standard error stays O(sigma/root N) regardless of dimension. -> Monte Carlo is a valid numerical integrator under the model you feed it; the failures here are failures of inputs and interpretation, not of the method itself. The ergodicity-economics reading of point 4 is debated among economists, the math itself is standard. References: Peters, Nature Physics (2019); Gabaix, Gopikrishnan, Plerou and Stanley, Nature (2003); Mandelbrot, Journal of Business (1963); Merton, JFE (1980); Cont, Quantitative Finance (2001). #finance #quant #trading #algotrading #stocks

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