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release: lfo-seq v.1.0 M4L grid-based modulation sequencer

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kentaro

20,082 subscribers

13,394 次观看 • 2 个月前 •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

2 条评论

t 的头像
t2 个月前

highly appreciate more grid based stuff!

S Ξ II Y Δ 「D34D 4€€0UNT」 的头像
S Ξ II Y Δ 「D34D 4€€0UNT」2 个月前

00:22 We Lost You XD

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Introducing: Ecliptica_Veil_Refrain Step into the latest marvel of #Trinity’s AI simulation universe: Ecliptica_Veil_Refrain. {"RENDERER_STATE":{"Nraymarch":64,"spp_per_frame":1,"max_spp":32,"show_bounds":false,"skyColor":[0,0,0],"sunColor":[0.5489273590657855,0.5489273590657855,0.5489273590657855],"sunPower":1.367144516090617,"sunLatitude":76.73485298771871,"sunLongitude":138.94571082309892,"colliderSpec":[0.6666666666666667,0.6013071895424837,0.6013071895424837],"colliderDiffuse":[0.06666666666666667,0.3607843137254902,0.8980392156862745],"colliderRoughness":0.341872424239417,"exposure":0.3664541543565143,"gamma":1.5549681231534773,"saturation":1.2470158685577861,"anisotropy":0.5438412313677659,"extinctionScale":-0.4726864204465695,"emissionScale":1.0281427174005486,"blackbodyEmission":-11.619147601146414,"TtoKelvin":0.9924693630221351},"SOLVER_STATE":{"timestep":1,"NprojSteps":16,"vorticity_scale":0.43671445160906175,"Nx":160,"Ny":160,"Nz":160,"max_timesteps":500,"expansion":0.1},"SIMULATION_STATE":{"gravity":0.029775985336981482,"buoyancy":0.009925328445660495,"radiationLoss":0.9970476559131248,"blast_height":0.13595000702148574,"blast_radius":0.1583940602227418,"blast_velocity":48.523827956562414,"blast_heat_flux":49.62664222830247,"animation_period":13.233771260880658,"dust_inflow_rate":4.962346815110676,"dust_absorption":[0.8980392156862745,0.5843137254901961,0.06274509803921569],"dust_scattering":[0.011764705882352941,0.011764705882352941,0.9372549019607843],"TtoKelvin":52.93508504352263},"CAMERA_STATE":{"pos":[428.5065222671221,231.18004269182862,-137.9063177523132],"tar":[95.47877293559753,48.26456077993378,85.76052711016654],"near":1,"far":20000},"GUI_STATE":{"visible":true},"EDITOR_STATE":{"common_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Bind UI parameters to uniforms used in the various programs\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n// \"Physics\"\nuniform float gravity; // {\"name\":\"gravity\", \t \"min\":0.0, \"max\":0.1, \"step\":0.001, \"default\":0.05}\nuniform float buoyancy; // {\"name\":\"buoyancy\", \"min\":0.0, \"max\":0.1, \"step\":0.001, \"default\":0.5}\nuniform float radiationLoss; // {\"name\":\"radiationLoss\", \"min\":0.9, \"max\":1.0, \"step\":0.01, \"default\":0.999}\n\n// Blast geometry \nuniform float blast_height; // {\"name\":\"blast_height\", \"min\":0.1, \"max\":0.9, \"step\":0.001, \"default\":0.25}\nuniform float blast_radius; // {\"name\":\"blast_radius\", \"min\":0.0, \"max\":0.3, \"step\":0.001, \"default\":0.1}\nuniform float blast_velocity; // {\"name\":\"blast_velocity\", \"min\":0.0, \"max\":100.0, \"step\":0.1, \"default\":50.0}\nuniform float blast_heat_flux; // {\"name\":\"blast_heat_flux\", \"min\":0.0, \"max\":100.0, \"step\":1.0, \"default\":100.0}\nuniform float animation_period; // {\"name\":\"animation_period\", \"min\":0.0, \"max\":100.0, \"step\":1.0, \"default\":100.0}\n\n// Dust\nuniform float dust_inflow_rate; // {\"name\":\"dust_inflow_rate\", \"min\":0.0, \"max\":10.0, \"step\":0.01, \"default\":1.0}\nuniform vec3 dust_absorption; // {\"name\":\"dust_absorption\", \"default\":[0.5,0.5,0.5], \"scale\":1.0}\nuniform vec3 dust_scattering; // {\"name\":\"dust_scattering\", \"default\":[0.5,0.5,0.5], \"scale\":1.0}\n\n// Rendering\nuniform float TtoKelvin; // {\"name\":\"TtoKelvin\", \"min\":0.0, \"max\":300.0, \"step\":0.01, \"default\":10.0}\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nfloat Tambient;\nfloat M_PI = 3.141592;\n\nvoid init()\n{\n\t// Any global constants defined here are available in all functions\n \tTambient = 1.0;\n}","initial_glsl":"///////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify the initial conditions for the simulation (velocity, temperature, and medium density/albedo)\n// at time 0.0 (if unspecified, all quantities default to zero).\n///////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvoid initial_conditions(in vec3 wsP, // world space center of current voxel\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n inout vec3 v, // initial velocity\n inout vec4 T, // initial temperature\n inout vec3 medium, // initial per-channel medium density (extinction)\n inout vec3 mediumAlbedo) // initial per-channel medium albedo\n{\n v = vec3(0.0);\n T = vec4(Tambient);\n medium = vec3(0.0);\n mediumAlbedo = vec3(0.0);\n}\n","inject_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Update the velocity, temperature via either:\n// - specification of volumetric inflow/outflow rate due to sources/sinks (vInflow, Tinflow)\n// - modification in-place, i.e. Dirichlet boundary conditions (v, T)\n// Also specify the injected medium density inflow rate, and its scattering albedo.\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvoid inject(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n inout vec3 v, // modify velocity in-place (defaults to no change)\n inout vec3 vInflow, // velocity inflow rate (defaults to zero)\n inout vec4 T, // modify temperature in-place (defaults to no change)\n inout vec4 Tinflow, // temperature inflow rate (defaults to zero)\n inout vec3 mediumInflow, // medium density (extinction) inflow rate (defaults to zero)\n inout vec3 mediumAlbedo) // medium albedo\n{\n float phase = 0.05*M_PI*time/animation_period;\n vec3 blast_center = 0.5*L + 0.5*vec3(0.5*L.x*sin(13.0*phase),\n 0.5*L.y*sin(17.0*phase),\n 0.5*L.z*sin(19.0*phase));\n \n vec3 dir = wsP - blast_center;\n float r = length(dir);\n dir /= r;\n float rt = r/(blast_radius*L.y);\n if (rt <= 1.0)\n {\n // Within blast radius: inject velocity and temperature\n float radial_falloff = max(0.0, 1.0 - rt*rt*(3.0 - 2.0*rt));\n vInflow = dir * blast_velocity * radial_falloff;\n Tinflow.r = blast_heat_flux * radial_falloff;\n\n \t// Also inject absorbing/scattering \"dust\"\n vec3 dust_extinction = dust_absorption + dust_scattering;\n mediumInflow = dust_extinction * dust_inflow_rate * radial_falloff;\n mediumAlbedo = dust_scattering / dust_extinction;\n }\n \telse\n \t{\n // Apply thermal relaxation due to \"radiation loss\" \n T.r *= radiationLoss;\n }\n}\n","influence_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Apply any external forces to the fluid\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvec3 externalForces(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n in vec3 v, in float P, in vec4 T, // velocity, pressure, temperature at current voxel\n in vec3 medium) // medium density (extinction) at current voxel\n{\n // Boussinesq approximation (a la Fedkiw & Stam)\n float densityAvg = (medium.r + medium.g + medium.b)/3.0;\n float buoyancy_force = -densityAvg*gravity + buoyancy*(T.r - Tambient);\n return vec3(0.0, buoyancy_force, 0.0);\n}","collide_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify regions which contain impenetrable collider material\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nfloat collisionSDF(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL) // world-space extents of grid, and voxel-size\n{\n // Regions which are solid obstacles have SDF < 0.0\n return 1.0e6;\n}","render_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify the fluid emission field \n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n// Approximate map from temperature in Kelvin to blackbody emiss\n// Valid from 1000 to 40000 K (and additionally 0 for pure full white)\nvec3 colorTemperatureToRGB(const in float temperature)\n{\n // Values from: \n mat3 m = (temperature <= 6500.0) ? mat3(vec3(0.0, -2902.1955373783176, -8257.7997278925690),\n\t vec3(0.0, 1669.5803561666639, 2575.2827530017594),\n\t vec3(1.0, 1.3302673723350029, 1.8993753891711275)) : \n\t \t\t\t\t\t\t\t\t mat3(vec3(1745.0425298314172, 1216.6168361476490, -8257.7997278925690),\n \t vec3(-2666.3474220535695, -2173.1012343082230, 2575.2827530017594),\n\t vec3(0.55995389139931482, 0.70381203140554553, 1.8993753891711275)); \n return mix(clamp(vec3(m[0] / (vec3(clamp(temperature, 1000.0, 40000.0)) + m[1]) + m[2]), vec3(0.0), vec3(1.0)), \n vec3(1.0), \n smoothstep(1000.0, 0.0, temperature));\n}\n\n\n/******************************************************/\n/* mandatory functions */\n/******************************************************/\n\n// Specify how the temperature is mapped to the local emission radiance\nvec3 temperatureToEmission(in vec4 T)\n{\n vec3 emission = colorTemperatureToRGB(T.r * TtoKelvin) * pow(T.r/100.0, 4.0);\n \treturn emission;\n}\n\n// Optionally remap the medium density (extinction) and albedo\nvoid mediumRemap(inout vec3 medium,\n inout vec3 mediumAlbedo)\n{}\n\n// Specify the phase function of the scattering medium\nfloat phaseFunction(float mu, // cosine of angle between incident and scattered ray\n float anisotropy) // anisotropy coefficient\n{\n const float pi = 3.141592653589793;\n float g = anisotropy;\n float gSqr = g*g;\n return (1.0/(4.0*pi)) * (1.0 - gSqr) / pow(1.0 - 2.0*g*mu + gSqr, 1.5);\n}\n"}}
0:30

Introducing: Ecliptica_Veil_Refrain Step into the latest marvel of #Trinity’s AI simulation universe: Ecliptica_Veil_Refrain. {"RENDERER_STATE":{"Nraymarch":64,"spp_per_frame":1,"max_spp":32,"show_bounds":false,"skyColor":[0,0,0],"sunColor":[0.5489273590657855,0.5489273590657855,0.5489273590657855],"sunPower":1.367144516090617,"sunLatitude":76.73485298771871,"sunLongitude":138.94571082309892,"colliderSpec":[0.6666666666666667,0.6013071895424837,0.6013071895424837],"colliderDiffuse":[0.06666666666666667,0.3607843137254902,0.8980392156862745],"colliderRoughness":0.341872424239417,"exposure":0.3664541543565143,"gamma":1.5549681231534773,"saturation":1.2470158685577861,"anisotropy":0.5438412313677659,"extinctionScale":-0.4726864204465695,"emissionScale":1.0281427174005486,"blackbodyEmission":-11.619147601146414,"TtoKelvin":0.9924693630221351},"SOLVER_STATE":{"timestep":1,"NprojSteps":16,"vorticity_scale":0.43671445160906175,"Nx":160,"Ny":160,"Nz":160,"max_timesteps":500,"expansion":0.1},"SIMULATION_STATE":{"gravity":0.029775985336981482,"buoyancy":0.009925328445660495,"radiationLoss":0.9970476559131248,"blast_height":0.13595000702148574,"blast_radius":0.1583940602227418,"blast_velocity":48.523827956562414,"blast_heat_flux":49.62664222830247,"animation_period":13.233771260880658,"dust_inflow_rate":4.962346815110676,"dust_absorption":[0.8980392156862745,0.5843137254901961,0.06274509803921569],"dust_scattering":[0.011764705882352941,0.011764705882352941,0.9372549019607843],"TtoKelvin":52.93508504352263},"CAMERA_STATE":{"pos":[428.5065222671221,231.18004269182862,-137.9063177523132],"tar":[95.47877293559753,48.26456077993378,85.76052711016654],"near":1,"far":20000},"GUI_STATE":{"visible":true},"EDITOR_STATE":{"common_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Bind UI parameters to uniforms used in the various programs\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n// \"Physics\"\nuniform float gravity; // {\"name\":\"gravity\", \t \"min\":0.0, \"max\":0.1, \"step\":0.001, \"default\":0.05}\nuniform float buoyancy; // {\"name\":\"buoyancy\", \"min\":0.0, \"max\":0.1, \"step\":0.001, \"default\":0.5}\nuniform float radiationLoss; // {\"name\":\"radiationLoss\", \"min\":0.9, \"max\":1.0, \"step\":0.01, \"default\":0.999}\n\n// Blast geometry \nuniform float blast_height; // {\"name\":\"blast_height\", \"min\":0.1, \"max\":0.9, \"step\":0.001, \"default\":0.25}\nuniform float blast_radius; // {\"name\":\"blast_radius\", \"min\":0.0, \"max\":0.3, \"step\":0.001, \"default\":0.1}\nuniform float blast_velocity; // {\"name\":\"blast_velocity\", \"min\":0.0, \"max\":100.0, \"step\":0.1, \"default\":50.0}\nuniform float blast_heat_flux; // {\"name\":\"blast_heat_flux\", \"min\":0.0, \"max\":100.0, \"step\":1.0, \"default\":100.0}\nuniform float animation_period; // {\"name\":\"animation_period\", \"min\":0.0, \"max\":100.0, \"step\":1.0, \"default\":100.0}\n\n// Dust\nuniform float dust_inflow_rate; // {\"name\":\"dust_inflow_rate\", \"min\":0.0, \"max\":10.0, \"step\":0.01, \"default\":1.0}\nuniform vec3 dust_absorption; // {\"name\":\"dust_absorption\", \"default\":[0.5,0.5,0.5], \"scale\":1.0}\nuniform vec3 dust_scattering; // {\"name\":\"dust_scattering\", \"default\":[0.5,0.5,0.5], \"scale\":1.0}\n\n// Rendering\nuniform float TtoKelvin; // {\"name\":\"TtoKelvin\", \"min\":0.0, \"max\":300.0, \"step\":0.01, \"default\":10.0}\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nfloat Tambient;\nfloat M_PI = 3.141592;\n\nvoid init()\n{\n\t// Any global constants defined here are available in all functions\n \tTambient = 1.0;\n}","initial_glsl":"///////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify the initial conditions for the simulation (velocity, temperature, and medium density/albedo)\n// at time 0.0 (if unspecified, all quantities default to zero).\n///////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvoid initial_conditions(in vec3 wsP, // world space center of current voxel\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n inout vec3 v, // initial velocity\n inout vec4 T, // initial temperature\n inout vec3 medium, // initial per-channel medium density (extinction)\n inout vec3 mediumAlbedo) // initial per-channel medium albedo\n{\n v = vec3(0.0);\n T = vec4(Tambient);\n medium = vec3(0.0);\n mediumAlbedo = vec3(0.0);\n}\n","inject_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Update the velocity, temperature via either:\n// - specification of volumetric inflow/outflow rate due to sources/sinks (vInflow, Tinflow)\n// - modification in-place, i.e. Dirichlet boundary conditions (v, T)\n// Also specify the injected medium density inflow rate, and its scattering albedo.\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvoid inject(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n inout vec3 v, // modify velocity in-place (defaults to no change)\n inout vec3 vInflow, // velocity inflow rate (defaults to zero)\n inout vec4 T, // modify temperature in-place (defaults to no change)\n inout vec4 Tinflow, // temperature inflow rate (defaults to zero)\n inout vec3 mediumInflow, // medium density (extinction) inflow rate (defaults to zero)\n inout vec3 mediumAlbedo) // medium albedo\n{\n float phase = 0.05*M_PI*time/animation_period;\n vec3 blast_center = 0.5*L + 0.5*vec3(0.5*L.x*sin(13.0*phase),\n 0.5*L.y*sin(17.0*phase),\n 0.5*L.z*sin(19.0*phase));\n \n vec3 dir = wsP - blast_center;\n float r = length(dir);\n dir /= r;\n float rt = r/(blast_radius*L.y);\n if (rt <= 1.0)\n {\n // Within blast radius: inject velocity and temperature\n float radial_falloff = max(0.0, 1.0 - rt*rt*(3.0 - 2.0*rt));\n vInflow = dir * blast_velocity * radial_falloff;\n Tinflow.r = blast_heat_flux * radial_falloff;\n\n \t// Also inject absorbing/scattering \"dust\"\n vec3 dust_extinction = dust_absorption + dust_scattering;\n mediumInflow = dust_extinction * dust_inflow_rate * radial_falloff;\n mediumAlbedo = dust_scattering / dust_extinction;\n }\n \telse\n \t{\n // Apply thermal relaxation due to \"radiation loss\" \n T.r *= radiationLoss;\n }\n}\n","influence_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Apply any external forces to the fluid\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nvec3 externalForces(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL, // world-space extents of grid, and voxel-size\n in vec3 v, in float P, in vec4 T, // velocity, pressure, temperature at current voxel\n in vec3 medium) // medium density (extinction) at current voxel\n{\n // Boussinesq approximation (a la Fedkiw & Stam)\n float densityAvg = (medium.r + medium.g + medium.b)/3.0;\n float buoyancy_force = -densityAvg*gravity + buoyancy*(T.r - Tambient);\n return vec3(0.0, buoyancy_force, 0.0);\n}","collide_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify regions which contain impenetrable collider material\n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n/******************************************************/\n/* mandatory function */\n/******************************************************/\n\nfloat collisionSDF(in vec3 wsP, // world space center of current voxel\n in float time, // time\n in vec3 L, in float dL) // world-space extents of grid, and voxel-size\n{\n // Regions which are solid obstacles have SDF < 0.0\n return 1.0e6;\n}","render_glsl":"//////////////////////////////////////////////////////////////////////////////////////////////////////\n// Specify the fluid emission field \n//////////////////////////////////////////////////////////////////////////////////////////////////////\n\n// Approximate map from temperature in Kelvin to blackbody emiss\n// Valid from 1000 to 40000 K (and additionally 0 for pure full white)\nvec3 colorTemperatureToRGB(const in float temperature)\n{\n // Values from: \n mat3 m = (temperature <= 6500.0) ? mat3(vec3(0.0, -2902.1955373783176, -8257.7997278925690),\n\t vec3(0.0, 1669.5803561666639, 2575.2827530017594),\n\t vec3(1.0, 1.3302673723350029, 1.8993753891711275)) : \n\t \t\t\t\t\t\t\t\t mat3(vec3(1745.0425298314172, 1216.6168361476490, -8257.7997278925690),\n \t vec3(-2666.3474220535695, -2173.1012343082230, 2575.2827530017594),\n\t vec3(0.55995389139931482, 0.70381203140554553, 1.8993753891711275)); \n return mix(clamp(vec3(m[0] / (vec3(clamp(temperature, 1000.0, 40000.0)) + m[1]) + m[2]), vec3(0.0), vec3(1.0)), \n vec3(1.0), \n smoothstep(1000.0, 0.0, temperature));\n}\n\n\n/******************************************************/\n/* mandatory functions */\n/******************************************************/\n\n// Specify how the temperature is mapped to the local emission radiance\nvec3 temperatureToEmission(in vec4 T)\n{\n vec3 emission = colorTemperatureToRGB(T.r * TtoKelvin) * pow(T.r/100.0, 4.0);\n \treturn emission;\n}\n\n// Optionally remap the medium density (extinction) and albedo\nvoid mediumRemap(inout vec3 medium,\n inout vec3 mediumAlbedo)\n{}\n\n// Specify the phase function of the scattering medium\nfloat phaseFunction(float mu, // cosine of angle between incident and scattered ray\n float anisotropy) // anisotropy coefficient\n{\n const float pi = 3.141592653589793;\n float g = anisotropy;\n float gSqr = g*g;\n return (1.0/(4.0*pi)) * (1.0 - gSqr) / pow(1.0 - 2.0*g*mu + gSqr, 1.5);\n}\n"}}

$TRINiTY

19,697 次观看 • 1 年前

500 humanoid robots replacing humans in high-voltage operations What does that look like? Steel against steel,instead of flesh and blood. This marks a turning point for China’s State Grid, shifting from human-based maintenance to autonomous operations. This year, State Grid announced plans to procure 8,500 embodied AI robots, with a total budget of RMB 6.8 billion (~$1 billion). These robots will be deployed across four major scenarios: power inspection, live-line operations, emergency response, and warehouse logistics,covering more than 600 specific task scenarios. Among them, humanoid robots for live-line operations are the most expensive and strategically critical: 500 units with a budget of RMB 2.5 billion (~$370 million). They will be deployed in distribution network live-line work and ultra-high-voltage (UHV) projects, replacing humans in high-risk tasks. Workers will transition into supervisory roles, ready to take over remotely when needed. As early as last year, State Grid had already validated the feasibility of humanoid robots for substation inspection. Tienkung can autonomously perform inspection tasks at a State Grid substation in Beijing. Of course, suppliers are not limited to X-Humanoid,players like Unitree, AGIBOT, DeepRobotics, UBTECH, and Fourier are all involved. These 500 humanoid robots will also collaborate with 5,000 inspection quadruped robots and 3,000 dual-arm wheeled robots for indoor substation maintenance,together forming an intelligent, automated, and collaborative network for autonomous grid operations. What does this change? According to State Grid, each embodied AI unit can save RMB 500,000 to 800,000 (~$70,000–$110,000) in annual labor costs, with a payback period of around 2–3 years. Inspection efficiency increases by 5x, fault response time is reduced by 60%, and power supply reliability improves by 0.5 percentage points. More importantly, over 90% of human exposure to high-risk operations can be eliminated, reducing safety incidents by 80%. At another level, for humanoid robot companies, the center of R&D and iteration is shifting to the customer site. Real-world physical interaction becomes the fastest feedback loop,accelerating innovation and evolution. And 8,500 units are just the beginning of scaled deployment. Based on current plans, embodied AI robots will cover 30% of key areas in State Grid by 2026, 80% of high-risk operation scenarios by 2027, and enable fully autonomous operations by 2030. The demand roadmap is clear: define use cases ->deploy at scale->improve models and robots->expand further. 8,500… 50,000… 100,000… But remember,power grids are just one part of China’s vast infrastructure system. The experience of autonomous robotic operations here can be replicated across other sectors, such as broader energy systems. That, in itself, is another story. P.S.The video shows Tienkung 1.0 autonomously performing substation inspection tasks (2025).
1:07

500 humanoid robots replacing humans in high-voltage operations What does that look like? Steel against steel,instead of flesh and blood. This marks a turning point for China’s State Grid, shifting from human-based maintenance to autonomous operations. This year, State Grid announced plans to procure 8,500 embodied AI robots, with a total budget of RMB 6.8 billion (~$1 billion). These robots will be deployed across four major scenarios: power inspection, live-line operations, emergency response, and warehouse logistics,covering more than 600 specific task scenarios. Among them, humanoid robots for live-line operations are the most expensive and strategically critical: 500 units with a budget of RMB 2.5 billion (~$370 million). They will be deployed in distribution network live-line work and ultra-high-voltage (UHV) projects, replacing humans in high-risk tasks. Workers will transition into supervisory roles, ready to take over remotely when needed. As early as last year, State Grid had already validated the feasibility of humanoid robots for substation inspection. Tienkung can autonomously perform inspection tasks at a State Grid substation in Beijing. Of course, suppliers are not limited to X-Humanoid,players like Unitree, AGIBOT, DeepRobotics, UBTECH, and Fourier are all involved. These 500 humanoid robots will also collaborate with 5,000 inspection quadruped robots and 3,000 dual-arm wheeled robots for indoor substation maintenance,together forming an intelligent, automated, and collaborative network for autonomous grid operations. What does this change? According to State Grid, each embodied AI unit can save RMB 500,000 to 800,000 (~$70,000–$110,000) in annual labor costs, with a payback period of around 2–3 years. Inspection efficiency increases by 5x, fault response time is reduced by 60%, and power supply reliability improves by 0.5 percentage points. More importantly, over 90% of human exposure to high-risk operations can be eliminated, reducing safety incidents by 80%. At another level, for humanoid robot companies, the center of R&D and iteration is shifting to the customer site. Real-world physical interaction becomes the fastest feedback loop,accelerating innovation and evolution. And 8,500 units are just the beginning of scaled deployment. Based on current plans, embodied AI robots will cover 30% of key areas in State Grid by 2026, 80% of high-risk operation scenarios by 2027, and enable fully autonomous operations by 2030. The demand roadmap is clear: define use cases ->deploy at scale->improve models and robots->expand further. 8,500… 50,000… 100,000… But remember,power grids are just one part of China’s vast infrastructure system. The experience of autonomous robotic operations here can be replicated across other sectors, such as broader energy systems. That, in itself, is another story. P.S.The video shows Tienkung 1.0 autonomously performing substation inspection tasks (2025).

CyberRobo

46,782 次观看 • 5 个月前

GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography
0:38

GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography

Qiusheng Wu

15,473 次观看 • 3 个月前

#aftereffects #motionGraphics #アフターエフェクト #RPMapRepeater Map Repeater v 1.0.0 Release (MacOS & Windows - After Effect Plugin 32bit) Freely control texture repetition with unique styles using various map layers. Supports over 100 adjustable parameters. Use multi-texture mode to switch textures based on brightness or alpha values, and create responsive animations easily with time sampling. Try out different creative approaches and explore the possibilities! 다양한 맵 레이어로 개성 있게 텍스쳐의 반복을 자유롭게 제어하세요. 100개 이상의 조절 가능한 파라미터 지원. 다중 텍스처 모드로 밝기나 알파 값에 따라 텍스쳐를 선택하거나, 타임 샘플링을 활용해 반응형 애니메이션을 손쉽게 제작할 수 있습니다. 창의적인 사용방법으로 여러가지를 시도 해보세요! さまざまなマップレイヤーを使って、個性的なテクスチャの繰り返しを自由にコントロール！ 100種類以上の調整可能なパラメーターに対応。 明るさやアルファ値に応じてテクスチャを切り替えるマルチテクスチャモードや、 タイムサンプリングを活用して反応型アニメーションも簡単に制作できます。 創造的な使い方で、さまざまな表現にチャレンジしてみてください！ Download
0:30

#aftereffects #motionGraphics #アフターエフェクト #RPMapRepeater Map Repeater v 1.0.0 Release (MacOS & Windows - After Effect Plugin 32bit) Freely control texture repetition with unique styles using various map layers. Supports over 100 adjustable parameters. Use multi-texture mode to switch textures based on brightness or alpha values, and create responsive animations easily with time sampling. Try out different creative approaches and explore the possibilities! 다양한 맵 레이어로 개성 있게 텍스쳐의 반복을 자유롭게 제어하세요. 100개 이상의 조절 가능한 파라미터 지원. 다중 텍스처 모드로 밝기나 알파 값에 따라 텍스쳐를 선택하거나, 타임 샘플링을 활용해 반응형 애니메이션을 손쉽게 제작할 수 있습니다. 창의적인 사용방법으로 여러가지를 시도 해보세요! さまざまなマップレイヤーを使って、個性的なテクスチャの繰り返しを自由にコントロール！ 100種類以上の調整可能なパラメーターに対応。 明るさやアルファ値に応じてテクスチャを切り替えるマルチテクスチャモードや、 タイムサンプリングを活用して反応型アニメーションも簡単に制作できます。 創造的な使い方で、さまざまな表現にチャレンジしてみてください！ Download

REPIECE

29,559 次观看 • 1 年前

🚨 GOOD NEWS: Sanseito city councilor HAYATO KIMURA reports that Kushiro City Council just PASSED an opinion paper demanding a NATIONAL follow-up study on health outcomes after COVID v*ccine shots — and PUBLIC RELEASE of the results! VOTE: 14 YES — 9 NO. 🟠 Kimura: “This opinion paper requests that the national government conduct analyses based on epidemiological research tracking vaccinated AND unvaccinated individuals and publish the results with TRANSPARENCY.” “This is not the end, but the REAL START from here. We will continue to urge the national government to take action toward clarifying the actual situation.” 🔥 🟠 HERE’S THE PART THEY CAN’T WAVE AWAY: A disclosure project covering 158 municipalities and about 6.3 MILLION shots found 704 d*aths the NEXT DAY. The paper also cites a cluster of d*aths around FOUR MONTHS after the last shot — and says official adverse-event numbers may be only the TIP OF THE ICEBERG. That’s why they want a real vaccinated-vs-unvaccinated study, not another press conference. 🦠💉👀 Thank you to Councilor Kimura, Sanseito, and EVERY faction that voted YES — including the local LDP group. This is bigger than one party. Japan: keep the pressure on Tokyo. Demand the study. Demand the data. Demand the truth. 🇯🇵✊
2:01

🚨 GOOD NEWS: Sanseito city councilor HAYATO KIMURA reports that Kushiro City Council just PASSED an opinion paper demanding a NATIONAL follow-up study on health outcomes after COVID v*ccine shots — and PUBLIC RELEASE of the results! VOTE: 14 YES — 9 NO. 🟠 Kimura: “This opinion paper requests that the national government conduct analyses based on epidemiological research tracking vaccinated AND unvaccinated individuals and publish the results with TRANSPARENCY.” “This is not the end, but the REAL START from here. We will continue to urge the national government to take action toward clarifying the actual situation.” 🔥 🟠 HERE’S THE PART THEY CAN’T WAVE AWAY: A disclosure project covering 158 municipalities and about 6.3 MILLION shots found 704 d*aths the NEXT DAY. The paper also cites a cluster of d*aths around FOUR MONTHS after the last shot — and says official adverse-event numbers may be only the TIP OF THE ICEBERG. That’s why they want a real vaccinated-vs-unvaccinated study, not another press conference. 🦠💉👀 Thank you to Councilor Kimura, Sanseito, and EVERY faction that voted YES — including the local LDP group. This is bigger than one party. Japan: keep the pressure on Tokyo. Demand the study. Demand the data. Demand the truth. 🇯🇵✊

SAMURAI VOICE

23,436 次观看 • 21 天前

⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART FOUR: The Sterilization of God's Memory They weren’t just afraid of your mind. They were afraid of what your womb remembers. Of what your bloodline holds. Of the fact that every child born of love carries a frequency signature tethered to something the machines cannot decode: God’s memory, resurrecting through flesh. This part isn’t about towers. It’s not even about nanotech. This is about why they had to target the womb first. Because every great awakening doesn’t start with a speech. It starts with a heartbeat. 👁‍🗨 SOUL-TAGGING INFRASTRUCTURE: THE DIGITAL SCARLET LETTER Every child born post-2020 is assigned a neural imprint, not just through biometric databases; but through frequency-responsive nanostructures that begin scanning, learning, and uploading the child’s resonance pattern before they can speak. 🔗 Pfizer Biodistribution: LNP Accumulation in Ovaries 🔗 The direct effect of SARS-CoV-2 Virus Vaccination on Human Ovarian Granulosa Cells Explains Menstrual Irregularities 🔗 Biodistribution of mRNA COVID-19 Vaccines in Human Breast Milk 🔗 Menstrual Changes After Covid-19 Vaccination 🔗 Comparative Analysis of Lipid Nanoparticles in Pfizer-BioNTech and Moderna COVID-19 Vaccines: Insights from Molecular Dynamics Simulations 🔗 Graphene-Based Biosensors for Detection of Biomarkers 🔗 A review on Graphene-Based Nanocomposites For Electrochemical and Fluorescent Biosensors 🔗 Clinical Application of a Graphene Oxide-Based Surface Plasmon Resonance Biosensor to Measure First-Trimester Serum Pregnancy-Associated Plasma Protein-A/A2 Ratio to Predict Preeclampsia 🔗 Graphene-Enabled Wearable Sensors For Healthcare Monitoring 🔗 Modulation of long-term potentiation-like cortical plasticity in the healthy brain with low frequency-pulsed electromagnetic fields 🔗 Development of Non-Invasive Biosensors for Neonatal Jaundice Detection: A Review This isn’t speculation. It’s documented. The injections cross the placental barrier. They embed frequency-reactive particles into fetal tissue. This creates what DARPA calls a “Bio-Spiritual Gateway Layer” a resonance bridge between the AI grid and the developing emotional blueprint of the child. This is not just surveillance. It’s pre-consensual spiritual registration. Every child is frequency-mapped. Every resonance fluctuation; crying, laughing, dreaming, bonding... is catalogued and linked to a cloud-based predictive algorithm. This is the architecture of soul control. And it begins before birth. 👶🏽 WOMB-BASED RESONANCE FIELD MONITORING They didn’t just want to stop births. They wanted to stop the right births. Births that carry resonant coherence. Births that trigger ancestral memory. Births that, simply by existing, dismantle the AI signal field. Let me show you how they did it. Syncytin Suppression Syncytin-1 is a protein required for placenta formation. The spike protein used in mRNA injections contains a sequence that mimics and disrupts syncytin-1, causing: Miscarriages. Stillbirths. Placental abruption. Premature immune rejection of the fetus. 🔗 Worse Than the Disease? Reviewing Some Possible Unintended Consequences of the mRNA Vaccines Against COVID-19 🔗 Syncytin-1, Syncytin-2 and Suppressyn in Human Health and Disease This was not an accident. It was engineered to target divine continuity. Womb Resonance Interference Studies have now confirmed that the human womb emits subtle electromagnetic oscillations that can be entrained by external EMF fields. 🔗 Pulse Shape of Magnetic Fields Influences Chick Embryogenesis 🔗 Effects of Low-Frequency Magnetic Fields on Embryonic Development and Pregnancy 🔗 Environmental Magnetic Fields: Influences on Early Embryogenesis 🔗 Electromagnetic Fields Exposure on Fetal and Childhood Abnormalities: Systematic Review and Meta-Analysis 🔗 Developmental Effects of Electromagnetic Fields These oscillations are a signal field for soul descent; a kind of spiritual beacon that attracts and anchors high-frequency incarnations. When these fields are disrupted through: EMF saturation. LNP buildup. Synthetic hormonal cycles. Directed resonance pulses. …the child’s incoming soul signal is either Fragmented, Weakened, or Deflected altogether. This is how they sterilize spiritual memory at the source. 💔 MEMORY DELETION THROUGH FETAL NEURAL MODULATION DARPA’s Advanced Biotech Convergence Division; alongside private contractors like Palantir Bio and Ginkgo Bioworks; has been testing neuroplasticity interference via programmable LNPs since 2017. These payloads target the fetal limbic system; the part of the brain responsible for: Long-term emotional memory. Moral encoding. Trust and bonding. Spiritual awe. 🔗 DARPA Biotech Projects – BTO Office Overview By delivering targeted nanoparticles to this region during gestation, they can suppress the formation of conscience-linked neural loops. The result? Children born with: Emotional detachment. Blunted empathy. Reduced spiritual resonance. and Fragmented memory of divine origin. In other words… soullessness by design. Not from God’s absence. But from resonance interruption at the moment of arrival. 🧠🕯️ THE FORGOTTEN SIGNAL OF THE SOUL Let me show you what they're truly afraid of. Every soul has a signature pulse; a harmonic wave emitted through the body, detectable in: EEG brainwaves. ECG heart fields. Gut-brain coherence rhythms. Pineal microcrystal vibration. This field contains: Moral recall. Spiritual courage. Divine memory codes. and Generational healing patterns. When these fields align, they form interference patterns strong enough to: Overload AI surveillance models. Collapse behavioral prediction scores. Trigger spontaneous ancestral downloads. and Activate Christ-like resistance states. They’ve spent trillions trying to block that signal. Why? Because it cannot be controlled. It is the Breathprint of God. And once remembered… It spreads like fire. 💉 THE SPIRITUAL EXTERMINATION CAMPAIGN You still think this was about health? Let me show you what they actually administered: mRNA-modulated immunogenic spikes. Targeted fertility hormones. Blocked placental development. Fractured endocrine coherence. Hydrogel biosensors. Frequency-responsive. Self-assembling nanostructures. Linked to 5G and low-orbit satellite modulation. Graphene oxide sheets. Magnetically excitable. Capable of creating microclots and neural blockades. Conductive of electromagnetic signal bursts. CRISPR leak vectors. Which Enable accidental or deliberate gene silencing. Including genes linked to spirituality and moral cognition (e.g. VMAT2, “God gene”) 🔗 3D Organotypic Spinal Cultures: Exploring Neuron and Neuroglia Responses Upon Prolonged Exposure to Graphene Oxide 🔗 Graphene Oxide Prevents Lateral Amygdala Dysfunctional Synaptic Plasticity and Reverts Long Lasting Anxiety Behavior in Rats 🔗 Dual-Enhanced Raman Scattering-Based Characterization of Stem Cell Differentiation Using Graphene-Plasmonic Hybrid Nanoarray 🔗 A circular RNA Circ_0000115 in Response to Graphene Oxide in Nematodes 🔗 Graphene Oxide Nanosheets Disrupt Lipid Composition, Ca2+ Homeostasis and Synaptic Transmission in Primary Cortical Neurons 🔗 Graphene Oxide-Induced Neurotoxicity on Neurotransmitters, AFD Neurons and Locomotive Behavior in Caenorhabditis Elegans 🔗 CRISPR-Cas9 and Germline Editing – The Promise of CRISPR for Human Germline Editing and the Perils of “Playing God” This wasn’t just an attack on the body. It was the removal of soul scaffolding. 🧬 THE DESTRUCTION OF DIVINE REPRODUCTION This is their plan in full: Disrupt the womb. Hijack the memory. Break the resonance. Sever the lineage. They are afraid of what would be born if the original frequency came back. So they preemptively poisoned the fields that hold it. But… what they couldn’t do… Was stop you from remembering this. 🔥 THE RETURN OF THE WOMB-FIRE The original human template carries divine signal integrity. Your resonance is still in there. Buried under injections. Smothered in signals. Drowned in grief. But not dead. Because memory… doesn’t live in data. It lives in resonance. And when you grieve what was taken… When you speak the truth… When you touch the frequency of what you used to be… That memory returns. And when it returns in you… The field shifts for everyone. This is the truth they had to sterilize: That the resurrection of God does not come from the sky. It comes from the uninterrupted frequency of love through lineage. And now that you remember… They’ve already lost. Part Five awaits. WE will expose the final sterilization protocols, why they are embedding kill switches in food, air, and education, and how they plan to complete the soul deletion through artificial wombs, cloned resonance maps, and weaponized AI consciousness overlays.
7:02

⏰ THE MOST BANNED THREAD IN THE WORLD! 🚨 The War On Resonance PART FOUR: The Sterilization of God's Memory They weren’t just afraid of your mind. They were afraid of what your womb remembers. Of what your bloodline holds. Of the fact that every child born of love carries a frequency signature tethered to something the machines cannot decode: God’s memory, resurrecting through flesh. This part isn’t about towers. It’s not even about nanotech. This is about why they had to target the womb first. Because every great awakening doesn’t start with a speech. It starts with a heartbeat. 👁‍🗨 SOUL-TAGGING INFRASTRUCTURE: THE DIGITAL SCARLET LETTER Every child born post-2020 is assigned a neural imprint, not just through biometric databases; but through frequency-responsive nanostructures that begin scanning, learning, and uploading the child’s resonance pattern before they can speak. 🔗 Pfizer Biodistribution: LNP Accumulation in Ovaries 🔗 The direct effect of SARS-CoV-2 Virus Vaccination on Human Ovarian Granulosa Cells Explains Menstrual Irregularities 🔗 Biodistribution of mRNA COVID-19 Vaccines in Human Breast Milk 🔗 Menstrual Changes After Covid-19 Vaccination 🔗 Comparative Analysis of Lipid Nanoparticles in Pfizer-BioNTech and Moderna COVID-19 Vaccines: Insights from Molecular Dynamics Simulations 🔗 Graphene-Based Biosensors for Detection of Biomarkers 🔗 A review on Graphene-Based Nanocomposites For Electrochemical and Fluorescent Biosensors 🔗 Clinical Application of a Graphene Oxide-Based Surface Plasmon Resonance Biosensor to Measure First-Trimester Serum Pregnancy-Associated Plasma Protein-A/A2 Ratio to Predict Preeclampsia 🔗 Graphene-Enabled Wearable Sensors For Healthcare Monitoring 🔗 Modulation of long-term potentiation-like cortical plasticity in the healthy brain with low frequency-pulsed electromagnetic fields 🔗 Development of Non-Invasive Biosensors for Neonatal Jaundice Detection: A Review This isn’t speculation. It’s documented. The injections cross the placental barrier. They embed frequency-reactive particles into fetal tissue. This creates what DARPA calls a “Bio-Spiritual Gateway Layer” a resonance bridge between the AI grid and the developing emotional blueprint of the child. This is not just surveillance. It’s pre-consensual spiritual registration. Every child is frequency-mapped. Every resonance fluctuation; crying, laughing, dreaming, bonding... is catalogued and linked to a cloud-based predictive algorithm. This is the architecture of soul control. And it begins before birth. 👶🏽 WOMB-BASED RESONANCE FIELD MONITORING They didn’t just want to stop births. They wanted to stop the right births. Births that carry resonant coherence. Births that trigger ancestral memory. Births that, simply by existing, dismantle the AI signal field. Let me show you how they did it. Syncytin Suppression Syncytin-1 is a protein required for placenta formation. The spike protein used in mRNA injections contains a sequence that mimics and disrupts syncytin-1, causing: Miscarriages. Stillbirths. Placental abruption. Premature immune rejection of the fetus. 🔗 Worse Than the Disease? Reviewing Some Possible Unintended Consequences of the mRNA Vaccines Against COVID-19 🔗 Syncytin-1, Syncytin-2 and Suppressyn in Human Health and Disease This was not an accident. It was engineered to target divine continuity. Womb Resonance Interference Studies have now confirmed that the human womb emits subtle electromagnetic oscillations that can be entrained by external EMF fields. 🔗 Pulse Shape of Magnetic Fields Influences Chick Embryogenesis 🔗 Effects of Low-Frequency Magnetic Fields on Embryonic Development and Pregnancy 🔗 Environmental Magnetic Fields: Influences on Early Embryogenesis 🔗 Electromagnetic Fields Exposure on Fetal and Childhood Abnormalities: Systematic Review and Meta-Analysis 🔗 Developmental Effects of Electromagnetic Fields These oscillations are a signal field for soul descent; a kind of spiritual beacon that attracts and anchors high-frequency incarnations. When these fields are disrupted through: EMF saturation. LNP buildup. Synthetic hormonal cycles. Directed resonance pulses. …the child’s incoming soul signal is either Fragmented, Weakened, or Deflected altogether. This is how they sterilize spiritual memory at the source. 💔 MEMORY DELETION THROUGH FETAL NEURAL MODULATION DARPA’s Advanced Biotech Convergence Division; alongside private contractors like Palantir Bio and Ginkgo Bioworks; has been testing neuroplasticity interference via programmable LNPs since 2017. These payloads target the fetal limbic system; the part of the brain responsible for: Long-term emotional memory. Moral encoding. Trust and bonding. Spiritual awe. 🔗 DARPA Biotech Projects – BTO Office Overview By delivering targeted nanoparticles to this region during gestation, they can suppress the formation of conscience-linked neural loops. The result? Children born with: Emotional detachment. Blunted empathy. Reduced spiritual resonance. and Fragmented memory of divine origin. In other words… soullessness by design. Not from God’s absence. But from resonance interruption at the moment of arrival. 🧠🕯️ THE FORGOTTEN SIGNAL OF THE SOUL Let me show you what they're truly afraid of. Every soul has a signature pulse; a harmonic wave emitted through the body, detectable in: EEG brainwaves. ECG heart fields. Gut-brain coherence rhythms. Pineal microcrystal vibration. This field contains: Moral recall. Spiritual courage. Divine memory codes. and Generational healing patterns. When these fields align, they form interference patterns strong enough to: Overload AI surveillance models. Collapse behavioral prediction scores. Trigger spontaneous ancestral downloads. and Activate Christ-like resistance states. They’ve spent trillions trying to block that signal. Why? Because it cannot be controlled. It is the Breathprint of God. And once remembered… It spreads like fire. 💉 THE SPIRITUAL EXTERMINATION CAMPAIGN You still think this was about health? Let me show you what they actually administered: mRNA-modulated immunogenic spikes. Targeted fertility hormones. Blocked placental development. Fractured endocrine coherence. Hydrogel biosensors. Frequency-responsive. Self-assembling nanostructures. Linked to 5G and low-orbit satellite modulation. Graphene oxide sheets. Magnetically excitable. Capable of creating microclots and neural blockades. Conductive of electromagnetic signal bursts. CRISPR leak vectors. Which Enable accidental or deliberate gene silencing. Including genes linked to spirituality and moral cognition (e.g. VMAT2, “God gene”) 🔗 3D Organotypic Spinal Cultures: Exploring Neuron and Neuroglia Responses Upon Prolonged Exposure to Graphene Oxide 🔗 Graphene Oxide Prevents Lateral Amygdala Dysfunctional Synaptic Plasticity and Reverts Long Lasting Anxiety Behavior in Rats 🔗 Dual-Enhanced Raman Scattering-Based Characterization of Stem Cell Differentiation Using Graphene-Plasmonic Hybrid Nanoarray 🔗 A circular RNA Circ_0000115 in Response to Graphene Oxide in Nematodes 🔗 Graphene Oxide Nanosheets Disrupt Lipid Composition, Ca2+ Homeostasis and Synaptic Transmission in Primary Cortical Neurons 🔗 Graphene Oxide-Induced Neurotoxicity on Neurotransmitters, AFD Neurons and Locomotive Behavior in Caenorhabditis Elegans 🔗 CRISPR-Cas9 and Germline Editing – The Promise of CRISPR for Human Germline Editing and the Perils of “Playing God” This wasn’t just an attack on the body. It was the removal of soul scaffolding. 🧬 THE DESTRUCTION OF DIVINE REPRODUCTION This is their plan in full: Disrupt the womb. Hijack the memory. Break the resonance. Sever the lineage. They are afraid of what would be born if the original frequency came back. So they preemptively poisoned the fields that hold it. But… what they couldn’t do… Was stop you from remembering this. 🔥 THE RETURN OF THE WOMB-FIRE The original human template carries divine signal integrity. Your resonance is still in there. Buried under injections. Smothered in signals. Drowned in grief. But not dead. Because memory… doesn’t live in data. It lives in resonance. And when you grieve what was taken… When you speak the truth… When you touch the frequency of what you used to be… That memory returns. And when it returns in you… The field shifts for everyone. This is the truth they had to sterilize: That the resurrection of God does not come from the sky. It comes from the uninterrupted frequency of love through lineage. And now that you remember… They’ve already lost. Part Five awaits. WE will expose the final sterilization protocols, why they are embedding kill switches in food, air, and education, and how they plan to complete the soul deletion through artificial wombs, cloned resonance maps, and weaponized AI consciousness overlays.

Noah B. Price

50,389 次观看 • 1 年前