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Also had this pissvideo saved for quite a while might aswell post it too. 😈 #piss #peeplay #peepants #peekink #peeholding #pee #omo #malewetting #maleomorashi #maleomo #maledesperation #holding #fullbladder #burstingtopee #omokink #omorashi #bwc #cock #watersports
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2:06
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Kinda realised I hadn't posted for a while, and also realised I had to pee. I think you can guess where that lead to 😂 #maleomo #malewetting #maledesperation #peepants #wettingpants #omorashi #peeingpants #wetsocks
ShinyVolcarona
16,630 views • 3 years ago
0:57
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I did a hold for someone yesterday and I was about to break at this point... I couldn't stop some big leaks breaking out 😭😭 #peepants #wettingpants #omorashi #wetsocks #malewetting #maledesperation #maleomo #maleomorashi #peedesperation #peeholding #gayomo #gayomorashi
ShinyVolcarona
57,695 views • 3 years ago
1:40
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So it took a while for my bladder to fill up yesterday, but I think the three ciders did the trick 😁😁 #peepants #wettingpants #omorashi #wetsocks #maledesperation #maleomo #maleomorashi #malewetting #peedesperation #gayomo #gayomorashi
ShinyVolcarona
37,141 views • 2 years ago
![[trans JPN/ENG] Post-match interview with Yuki Ishikawa for BS-TBS. -First of all, since this was the first match, there may have been different atmospheres, but what do you think about the fact that you won this first match in straight sets? Yuki: Well, as a win, I think it's fantastic that we managed to win 3-0, so I consider that positive. As for the content, there are still some things that aren't quite right, and also, I think there were too many aces on return today, so I think that's something we need to improve in the future. Masa: It's quite unusual for Ishikawa to join the Nation League in the first round and play, so what are your thoughts or feelings about it? Yuki: It's been a while since I joined the team in the first round, and even though the time to practice has been short, I'm happy to be able to play matches right from the first round like this. I haven't had many opportunities to play matches with my club this season, so I was looking forward to it. However, my performance today was only good in the first set, and then it dropped off a bit after that, so I hope to improve in matches and throughout the Nation League. Masa: You mentioned your performance earlier, but since today was the first match, were there any problems you noticed in this first match? Yuki: Yes, in addition to what I said before, I think we did a lot of trial and error. Our reception, so I think it's something we need to improve on. Even so, we managed not to lose a set, and although we were helped by our opponents' mistakes, I think we deserve credit for winning 3-0. -Captain, the next match is against Poland. Could you tell us about your aspirations for that match? Yuki: Poland is very tall and has many young players on the rise, so we'll keep that in mind, and we've identified areas where we can improve further compared to today. We'll approach the match against Poland by working on those aspects.](https://image.24vids.com/tw-2064710947537575940/ext_tw_video_thumb/2064710801433219072/pu/img/0NNaWZgzTdUTt0G0.jpg)
![⃤ Video of a Black Triangle - What's the Frequency, Gerry? ⃤ "A very clear visual representation of what was on the radar. It resembled a very black, triangular or delta shape to it" "It was always slightly out of focus for some reason." "Garry Nolan told us to watch for the cloud formations." (If you scroll down to the bottom, I'll tell you the exact time stamps for each the UAP videos that were shown.) "We believe [it's NHI]. Either that or some very sophisticated technology that maybe we're reverse engineering." "There was a specific electronic signature (frequency) emanating from them when they were going into or coming out of the water, so they were easy to track." ~Bob Fish ~ Gerry Tedesco: August 29th, "we were in the RV, running tests on our equipment because we was planning on going out that weekend." John Tedesco: "And we noticed that we had a signature (on their spectrum analyzer) there that was well presented, very unusual for the area. And we kind of collaborated that with some radar data. Radar seemed to align with what we had on the spectrum analyzer. The object, we believe, was over the water at that point, simply because of the distance that we were able to capture it on the radar. It presented in a cloud layer, exited a cloud layer, produced a signature." Gerry; "This was a single thunderstorm cloud in the sky and the weather was great. We had cumulous clouds out there, mostly clear. And this was a dark, cumulonimbus cloud. It was a very dark thunderstorm cloud, and it looked out a place. " Ross Coulthart: "Do you think that that cloud might have been a fake cloud?" Donna Lee Nardo: "So Garry P. Nolan, he came out with us for our field study one night. He told us, Watch for the cloud formations.' And John, Gerry, and I saw one really nasty-looking...it looked like 10 motherships situated...oriented north to south, one night when we were doing the field study. And I believe this was early on in 2022. And it also was a clear night, but it just looked out of place. It was dark, yet there were lighted portions. But it was just so humongous. And we always remember that Garry had said, look at the cloud formations." Gerry: "Yeah, we definitely had some oddities out there." Coulthart: "I've had people, multiple people have sent me imagery. There's quite famous ones on YouTube where you see what looks like a cloud, and it's shaped just ever so slightly like a disc or a craft. And it's got the fluffy edges of a cloud, and then it suddenly maneuvers and just moves away. And I sometimes wonder whether something or someone is using clouds as a form of stealth or signature management." Gerry: "That's a possibility. We look at that, we look to see if it is a cloud. We use shortwave infrared, which does pick up moisture. And it'll actually differentiate the precipitation in a cloud, or moisture in a cloud, so we know it is a real cloud." Coulhart: "Did you do that with this cloud that night?" John: "Exactly, exactly. And this is something that we could determine that there wasn't moisture content." Coulthart: "So you were able to show it wasn't a classic cumulonimbus cloud, even though it looked like one." John: "No, no. Yeah, and the object was well hidden for a short period of time. Actually, relatively long period of time before it emerged from the cloud body." Coulthart: "So Donna is probably right: This is probably some kind of intelligent stealth management by something." Gerry: "It's a possibility." Donna: "Possibly." John: "It could very well be." (I like how all three will only go as far as, Possible and Could be.) Coulthart: "This is where it gets really interesting. Talk me through what happens next. " Gerry: "Okay, so we watched an object emerge from the cloud on radar. John and I quickly went to get our binoculars, we have what's called Vortex binoculars. These are high-end binoculars, great optical glass. John had began looking at the cloud with those, and he told me, we both went outside. I was trying to find one of the other cameras, scrambling, trying to get one of the other cameras going. "And John said, 'There's a black object moving between the cloud.' And then it was emerging from the cloud. So I grabbed my cell phone and videotaped it. While John was looking at them, we switched. And what we saw was something...originally it resembled a very black, triangular or delta shape to it, or bell shape to it. It had that Delta shape, or triangular shape." Coulthart: "And was this showing up on radar at this stage, that delta shape?" Gerry: "Yes." John: "Yes." Coulthart: "Wow!" John: "Yes, we did have a radar target." Gerry: "We tracked it on radar. On radar, it appears to separate into two more objects, which is quite interesting." Coulthart: "You found something interesting in the frequency, and you can't talk about it, can you? Has the FBI asked you, not to talk about it?" Gerry: "Yes, that's the sensitive part. There was quite a bit of interesting signals, but that goes into signals intelligence, which we can't talk about." Coulthart: "Just let me guess. 1.6 by any chance?" (They all laugh) Donna: "You've been talking to people." Gerry: "No comment." Coulthart: "No, it just fascinates me. Is it 1.6 gigahertz, or megahertz? I'm trying to remember." John: "It's gigahertz. Yeah, I know with Skinwalker Ranch, I know the one, 1.6 seems to come up quite a bit. There's also a three-gigahertz signal, supposedly." Gerry: "There's a few others, too. We'll leave it at that." Coulthart: "No, but it's interesting. It's such a consistent thing, and I'm really interested because all around the world, people are contacting me, talking about 1.6, in particular, but also about three gigahertz. And nobody's explaining it. But often it's an indicator." ~~~From My Bob Fish Blog~~~ Bob Fish: "In that same TS/SCI building cafeteria in El Segundo, I had lunch with a senior USAF NCO who had worked for Project Blue Book in the 1970s (after it had been 'officially disbanded'). He was an ELINT technician (electronic intelligence) who flew in RC-135s from MacDill AFB in Florida. The 'normal' target was Cuba where they did lots of snooping and sometimes challenging the Cubans to turn on radar and other systems. "He said there were times when they were diverted from these missions to track UFOs off the east coast of Florida. His claim was that UFOs had a landing and takeoff spot in the ocean east of Miami, north of Bermuda. He also claimed there was a specific electronic signature (frequency) emanating from them when they were going into or coming out of the water, so they were easy to track. On several occasions they filmed the UFO as it transitioned from water to air or vice versa. High quality film of UFOs is 'out there' somewhere!" (What was the signature? 1.6 gigahertz? 3.0?) ~~~End Bob Fish Excerpt~~~ Coulthart: "And as you say - without giving away the frequency that you detected - you detected a frequency anomaly on your spectrum analyzer. You saw it there. Then you got it on your radar. And then when you visually observed it with the binoculars, the vortex binoculars, you then corroborated that object on the radar as well. So you've got four separate data points to corroborate something anomalous." John: "And a very, very clear visual representation of what was on the radar. The interesting thing I will say that we had observed flights of commercial aircraft at the same time through these lenses, these very clear lenses that we use. The commercial aircraft was extremely detailed, in focus. You can even make out the writing on the on the aircraft. The object itself? No." Gerry: "It was always slightly out of focus for some reason." John: "It was poorly presented." Coulthart: "And you gents would understand, and I'm sure Donna as well, that the Alcubierre-drive principles. That, essentially, if something is coming, if it's warping space time, there's allegedly some kind of plasma or some kind of distortion field around the object. Do you think that might explain what you were seeing? Gerry: That's a possibility." John: "That's a very strong possibility." Gerry: "It's something we're looking into. There was also, there was a shimmer around it. Definitely a possibility of some kind of field effect around it." ~~~ Time Stamps Extremely bright, luminous sphere over the ocean. Not visible to the naked eye. - 13:33 The Black Triangle - 33:31 Orb-Like Object Over Land in Farmingville, N.Y. (Where my sister lives) ~ 58:18 Similar to what @MeaganOurada saw - 1:14:05](https://image.24vids.com/tw-1988506241199731054/amplify_video_thumb/1988454282111459329/img/hi9V9iZ2y1Z8QcTG.jpg)
![I think I can finally report some success training a quite accurate IDM capable of recovering keystrokes from Minecraft gameplay, even in quite PvP-heavy situations. At this point the model does not only know what keys are pressed to the extent reasonably discernible, it also knows how fast it is moving in 3D space at all times, even when knockback is mixing with the self-move impulse. Now, recovering keystrokes from normal external capture footage is just about impossible. E.g. W/A/S/D does exactly nothing during partial tick frames and jumping mid-air is also equally useless, so asking the model to recover key down states is inherently unreasoanble. Mouse deltas are also completely arbitrary units, as game mouse sensitivity introduces an arbitrary scale factor into the equation. The only good option is to think carefully about your model-environment contract, and only record "logical actions", not raw keystrokes. So here's a few unfortunate lessons I had to learn in roughly this order. - Choose good units. (bad: mouse deltas, good: delta radians [yes, you will need game-internal state]) - Capture from inside the main game loop and read the game fbo to get consistent frame-action pairing. Doing post-mortem pairing is hopeless. - Carefully define when you think keystrokes actually have an effect. (jump only works on ground, when flying or in water etc.) More subtle: The key may already be down, but no tick has happened yet to actually use the value. Hence: ignore Seperate gamestate into "fast and slow-moving" components. E.g. movement is likely tick based, camera rotation is very likely updated every frame in essentially every game ever. - Think about your frame-action correspondance contract (How old is the frame in relation to the inputs you capture? Will double or tripple buffering affect you?) Think about the game loop timeline, where you are sampling, how old the data you are reading is, and where the ticks are happening around you. Language models used to simply not have a model-environment contract, but even now with the model "living" in a designated harness, the contract still boils down to formatting, and tool implementation intrinsics. While also important, it is still quite a bit more obvious because the violations are in some way shape or form reflected as text you can actually see. - ffmpeg dropping frames cummulatively screws the model the further you get into the sequence because your targets are now shifted. If you can't encode the video in real-time, too bad. - Sodium has a frames in flight system different from vanilla Minecraft, which will also offset your targets from your frames. (there goes that data...) - Models are succeptible to latency. If there is too big of a delay between action and on-screen reflection, your performance degrades. At this point I realize ~100hours of gameplay is essentially no longer usable as a dataset. You can train on this data, but all you'll get is a mushy mess. However, some good news: - Making the model predict physics gamestate scalars helps the model generalize. For instantaneous events like jump, it's unreasonable to ask the model emit a short burst of jump=true at exactly the right time, however if you also predict your current y-velocity, the model has supervision signal for the "latent" from which that onground jump becomes apparent. Recovering x/z motion is also somewhat easier than unmixing it into plausible keystrokes for inertia-heavy player controller logic. - Regressing physics gamestate scalars also seems to make your dataset "bigger". While pure keystroke classification will overfit quickly, predicting exact physics gamestate scalars forces the model to generalize more and you can tolerate far more epochs before validation loss starts to stall out. This is the only reason why it was bearable to dump 100h+ of dataset hours and replace it with ~3 hours of gameplay after the 4th revision of the file format (yeah...) and somehow still have better performance. Now, you might be asking, "isn't this brittle?" and the answer is yesn't. Frame-action correspondance matters for training, but not so much during inference. So as long as you are sampling in roughly the same interval as your training data, you aren't violating any hard contract per-se. Somewhere around the frames ticks are happening, and during training you capture various tick-capture offset relations per random chance, so nothing is too obviously wrong here. HOWEVER, you will get screwed by gui scale, shaders, resource packs, "shit that recording is 1920x1040 because somebody doesn't know fullscreen exists" and other unfortunate edge cases of reality. But I suppose this is the role of dataset size. If all those "contract violations" that a youtube video has compared to the training data are addressed, I think this is a way to turn Youtube into a labeled dataset. I could never shake the feeling that VPT is a sound idea in practice, while never having been properly executed, and I think one reason why it hasn't is because that label boostrapping part is just a pain in the butt to get right. Now, what the player is doing is of course not the only label you can extract from video, but it has to be one of the targets predicted during pretraining to "align" the pretraining objective. Some notes on the video here, the colored dots on the analog visualizer are the ground truth, while the gray dot is the model prediction. Green means correct prediction, red means incorrect prediction at that frame. Model P(key) reports how wrong the prediction is from green (0.0) to red (1.0). You will also notice that during periods of rapid slow down, left and right actions become close to irrecoverable, because there is just that little motion. And some jump actions are not predicted correctly because I got the detection condition for jump events wrong... (duh) LMB/RMB for other than sustained events (like item-consume and block break) also seem to be hopelessly irrecoverable for now. Swing was supposed to do the same thing as motion y did for jump, but its too well behaved as an increasing counter. Maybe partial-tick interpolated values work better (v5 file format then... ugh..)](https://image.24vids.com/tw-2042731804780826849/amplify_video_thumb/2042721691844120576/img/yugYQfuXXQmJpdVp.jpg)
![Post-COVID Canada shows excess deaths continue to surge The ongoing surge in unexplained and excess deaths follows unprecedented pandemic response measures, yet health and government officials continue to ignore these alarming trends. The Justice Centre for Constitutional Freedoms (JCCF) has released a meticulously sourced 54-page report titled "Post-COVID Canada: The Rise in Unexpected Deaths.” This explosive document depicts Canada’s post-pandemic landscape where excess deaths have skyrocketed since the era of draconian lockdowns, mask mandates, and vaccine coercion. Yet, health bureaucrats and politicians remain eerily silent, content to pat themselves on the back while burying inconvenient data. President of the Justice Centre for Constitutional Freedoms, John Carpay, dissects this crisis and highlights how many continue to cling to a flawed narrative. "Well, thus far we're not really seeing much interest yet on the part of public health officials and politicians," Carpay said. "They seem to be quite happy with the narrative that COVID was not just a bad annual flu, but it was an unusually deadly killer, and it killed lots of people, and now COVID is over. Lockdowns were wonderful. Vaccines are still safe and effective, and ‘nothing to see here, folks. Let's just move on.’" The report draws on official government data from Statistics Canada to reveal these shocking trends. COVID deaths, for instance, actually increased post-vaccination instead of declining. "In 2020, in the first year of COVID, we had about 16,000 COVID deaths in 2020, according to Statistics Canada," Carpay explained. "And this jumped up to 20,000 COVID deaths in 2022, after everybody got vaccinated." This 20% spike raises glaring questions about vaccine efficacy, especially as mandates fueled division and discrimination. Even more alarming is the surge in non-COVID deaths among younger demographics. "We also had a startling and unexplained rise in deaths from Canadians under the age of 45," Carpay noted. "The death rates went up for Canadians under age 45, jumped by more than a third." Tens of thousands more young Canadians perished in 2022 and 2023 compared to pre-COVID years. Drug overdoses soared by 55%, from 4,500 annual deaths pre-lockdown to nearly 7,000—a tragic escalation that persists to this day. Children, too, have suffered inexplicably. "Those deaths have increased by 16%," Carpay said of kids aged 1-14. "In 2022, there were just under 800 children ages one to 14 who died." This permanent uptick cries out for scrutiny, potentially linked to lockdown-induced mental health crises, obesity, isolation, and novel pharmaceutical products never before unleashed on the general public. Adding to the crisis, unknown causes now account for 15% of young Canadian deaths in 2022—astronomically high, with autopsies performed only 6% of the time. Yet health and government officials are eerily silent, which Carpay attributes to denial: "Why are the politicians and public health officials not looking into this? Well, there's an old saying: It's easy to fool people; it's very hard to persuade people that they have been fooled." The report ties these trends to the fallout from unscientific policies: forced isolation, gym closures, and fines for outdoor walks, all eroding physical and mental health. Diabetes and hypertension-related deaths ballooned, underscoring how stress and inactivity shorten lives. Carpay issues a stark warning: "This report would just confirm that the experts were wrong in locking us down. It has very likely led to [these] catastrophic outcomes. So I think the biggest takeaway is let's not be governed by experts." As the World Health Organization warns of inevitable future pandemics, Canada must reject technocratic overreach and demand accountability. Though it seems unlikely, as federal Health Minister Marjorie Michel, shadow minister Dan Mazier, and Alberta's Adriana LaGrange refused to comment on the alarming, post-pandemic trends. This willful blindness confirms the establishment's evasion, leaving constitutional champions like the JCCF to step up where officials fail. FULL REPORT by Tamara Ugolini 🇨🇦:](https://image.24vids.com/tw-1964797471520940403/amplify_video_thumb/1964795839265607682/img/SXv6lGHmg1oyEGMo.jpg)