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Lattice light-sheet #microscopy with 4D image analysis reveals #Bcell receptors #immunoglobulin localise into clusters to aid recognition of their #antigen. Video & research by Deniz Saltukoglu et al BIOSS Freiburg in The EMBO Journal. On

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Biomedical Picture of the Day BPoD

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11,265 görüntüleme • 2 yıl önce •via X (Twitter)

#microscopy#Bcell#immunoglobulin#antigen
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New Feature: We’ve partnered with RepoAnalyzer to bring in-depth repo quality insights into over 211 projects! Hovering over the Github Score now reveals a breakdown of repo quality across key attributes like Contributors, Stars, and Forks, resulting in a comprehensive Final Score. Clicking “View Full Analysis” takes you straight to the detailed report on their site.

GoatIndex.ai | Data Layer For Solana AI

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🚨 BREAKING - A psionic session led by Mike Battista Michael Battista in Florida captured a glowing entity manifesting in complete darkness. The short clip shows a bright central light surrounded by swirling particles and energy, with analysts from ProPixel Video Analysis ProPixel Video Analysis and Research confirming the footage as authentic and not staged or CGI. Viewers are pointing to the humanoid-like form emerging from the light, the rapid particle movement around it, and the way the being appears to stabilize before fading. The chain of custody is documented, adding weight to claims of real-time NHI contact during focused sessions. This footage joins a growing body of evidence from controlled environments where trained facilitators report direct interaction with nonhuman intelligence. Original source credit: Psionic session footage by Mike Battista, analyzed by ProPixel Imaging (recent social media post).
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🚨 BREAKING - A psionic session led by Mike Battista Michael Battista in Florida captured a glowing entity manifesting in complete darkness. The short clip shows a bright central light surrounded by swirling particles and energy, with analysts from ProPixel Video Analysis ProPixel Video Analysis and Research confirming the footage as authentic and not staged or CGI. Viewers are pointing to the humanoid-like form emerging from the light, the rapid particle movement around it, and the way the being appears to stabilize before fading. The chain of custody is documented, adding weight to claims of real-time NHI contact during focused sessions. This footage joins a growing body of evidence from controlled environments where trained facilitators report direct interaction with nonhuman intelligence. Original source credit: Psionic session footage by Mike Battista, analyzed by ProPixel Imaging (recent social media post).

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Contact sheet prompting is the hottest AI video technique right now 🤯 One image in → 6 consistent frames out → cinematic video ads in minutes. But everyone's doing it manually. I automated the entire workflow in n8n + Airtable. Here's why contact sheet prompting is blowing up: You give AI one reference image, and it generates a grid of consistent shots — same face, same outfit, different angles. Instant storyboarding, full creative control, no photoshoots. The problem? It's super tedious: → Write the prompt manually → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one by one → Repeat for every product This n8n automation handles all of it: → Upload character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 generates smooth transitions between frames → You get 5 video clips ready to stitch Approval checkpoints at every stage, no surprises. What lands in your Airtable: → AI-generated creative prompt → Core hero image (model + product) → 6-frame contact sheet → 5 cinematic video clips → Full control before each generation step Contact sheet prompting on autopilot. I filmed a 20 minute Loom video showing you exactly how I set it up. Want the Loom + the complete n8n workflow + Airtable base? > Comment "SHEET" > Like this post And I'll send it over (must be following so I can DM)
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Contact sheet prompting is the hottest AI video technique right now 🤯 One image in → 6 consistent frames out → cinematic video ads in minutes. But everyone's doing it manually. I automated the entire workflow in n8n + Airtable. Here's why contact sheet prompting is blowing up: You give AI one reference image, and it generates a grid of consistent shots — same face, same outfit, different angles. Instant storyboarding, full creative control, no photoshoots. The problem? It's super tedious: → Write the prompt manually → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one by one → Repeat for every product This n8n automation handles all of it: → Upload character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 generates smooth transitions between frames → You get 5 video clips ready to stitch Approval checkpoints at every stage, no surprises. What lands in your Airtable: → AI-generated creative prompt → Core hero image (model + product) → 6-frame contact sheet → 5 cinematic video clips → Full control before each generation step Contact sheet prompting on autopilot. I filmed a 20 minute Loom video showing you exactly how I set it up. Want the Loom + the complete n8n workflow + Airtable base? > Comment "SHEET" > Like this post And I'll send it over (must be following so I can DM)

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One trick we discovered for avoiding realistic face moderation issues in Seedance 2.0 is using character turnaround sheets (front / side / back views). The first video is one of our experiment results — and it runs successfully. We’ve now integrated character turnarounds directly into our workflow + canvas system: 1. If your artwork was generated on our site, you can drag the image into the canvas directly from the Assets tab 2. Click the “Character Turnaround” button above the image to automatically generate a 3-view turnaround sheet 3. Create a new video node and use the turnaround sheet directly with Seedance 2.0 inside the workflow I’ve shared the workflow link in the comments if you want to explore the exact prompts, setup, and workflow details.
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One trick we discovered for avoiding realistic face moderation issues in Seedance 2.0 is using character turnaround sheets (front / side / back views). The first video is one of our experiment results — and it runs successfully. We’ve now integrated character turnarounds directly into our workflow + canvas system: 1. If your artwork was generated on our site, you can drag the image into the canvas directly from the Assets tab 2. Click the “Character Turnaround” button above the image to automatically generate a 3-view turnaround sheet 3. Create a new video node and use the turnaround sheet directly with Seedance 2.0 inside the workflow I’ve shared the workflow link in the comments if you want to explore the exact prompts, setup, and workflow details.

underwood

32,883 görüntüleme • 3 ay önce

NVIDIA just released a very impressive text-to-video paper. Video Latent Diffusion Models (Video LDMs) use a diffusion model in a compressed latent space to generate high-resolution videos. Here's a brief overview of how it works: 1. Pre-train image LDM on a dataset of images. 2. Turn the image LDM into a Video LDM by adding temporal layers to model video frames. 3. Fine-tune the Video LDM on encoded video sequences to create a video generator. 4. Temporally align diffusion model upsamplers to generate high-resolution videos. 5. Validate Video LDM on real driving videos of 512x1024 resolution, achieving state-of-the-art performance. 6. Apply the approach in creative content creation with text-to-video modeling. Paper: Project:
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NVIDIA just released a very impressive text-to-video paper. Video Latent Diffusion Models (Video LDMs) use a diffusion model in a compressed latent space to generate high-resolution videos. Here's a brief overview of how it works: 1. Pre-train image LDM on a dataset of images. 2. Turn the image LDM into a Video LDM by adding temporal layers to model video frames. 3. Fine-tune the Video LDM on encoded video sequences to create a video generator. 4. Temporally align diffusion model upsamplers to generate high-resolution videos. 5. Validate Video LDM on real driving videos of 512x1024 resolution, achieving state-of-the-art performance. 6. Apply the approach in creative content creation with text-to-video modeling. Paper: Project:

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🚨 JUST IN - British PM Spokesman on Gaza: - A comprehensive ceasefire in Gaza would primarily serve the interests of Hamas - In opposition to the comments made by the United Nations Secretary-General concerning Gaza, where he accused Israel of violating international humanitarian law and mentioned the Palestinian people's 'long history of occupation.' (video below) - Discussions are underway regarding a humanitarian truce to facilitate the entry of aid into Gaza Source: Al Jazeera
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🚨 JUST IN - British PM Spokesman on Gaza: - A comprehensive ceasefire in Gaza would primarily serve the interests of Hamas - In opposition to the comments made by the United Nations Secretary-General concerning Gaza, where he accused Israel of violating international humanitarian law and mentioned the Palestinian people's 'long history of occupation.' (video below) - Discussions are underway regarding a humanitarian truce to facilitate the entry of aid into Gaza Source: Al Jazeera

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The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation
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The Hidden Language of Diffusion Models paper page: tackle the challenge of understanding concept representations in text-to-image models by decomposing an input text prompt into a small set of interpretable elements. This is achieved by learning a pseudo-token that is a sparse weighted combination of tokens from the model's vocabulary, with the objective of reconstructing the images generated for the given concept. Applied over the state-of-the-art Stable Diffusion model, this decomposition reveals non-trivial and surprising structures in the representations of concepts. For example, we find that some concepts such as "a president" or "a composer" are dominated by specific instances (e.g., "Obama", "Biden") and their interpolations. Other concepts, such as "happiness" combine associated terms that can be concrete ("family", "laughter") or abstract ("friendship", "emotion"). In addition to peering into the inner workings of Stable Diffusion, our method also enables applications such as single-image decomposition to tokens, bias detection and mitigation, and semantic image manipulation

AK

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$5B in 1960. $169B in 2025. Global foreign aid has increased over 30x in 65 years. Trillions transferred from productive Western taxpayers to governments across Asia, Africa, and beyond. But the map barely changed. The same regions still light up as major recipients with massive flows to places that remain dysfunctional. Because instead of fixing bad governance, corruption, and anti-market policies, foreign aid rewards them by creating dependency and allowing failing systems to avoid the reforms that actually build prosperity. The experiment has run long enough. End foreign aid and let nations rise or fall on their own choices.

Rothmus 🏴

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1\ 4 Regarding the Siege of Sheikh Maqsoud and Al-Ashrafiyah in Aleppo by Forces of the Syrian Interim Government Two video clips have been released concerning the ongoing siege imposed on the neighborhoods of Sheikh Maqsoud and Al-Ashrafiyah in Aleppo by forces affiliated with the Syrian Interim Government. The first video, published by pro-government media outlets, claims that the government is “assisting one of the displaced persons.” In contrast, the second video clearly shows government forces preventing displaced civilians from returning to their homes — a serious legal and humanitarian issue that the government’s planners seem to overlook.
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1\ 4 Regarding the Siege of Sheikh Maqsoud and Al-Ashrafiyah in Aleppo by Forces of the Syrian Interim Government Two video clips have been released concerning the ongoing siege imposed on the neighborhoods of Sheikh Maqsoud and Al-Ashrafiyah in Aleppo by forces affiliated with the Syrian Interim Government. The first video, published by pro-government media outlets, claims that the government is “assisting one of the displaced persons.” In contrast, the second video clearly shows government forces preventing displaced civilians from returning to their homes — a serious legal and humanitarian issue that the government’s planners seem to overlook.

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Humanitarian efforts over the past week (28 Dec - 3 Jan): ✅4,200 humanitarian aid trucks entered the Gaza Strip, according to the agreement. The trucks carried food, medical supplies and shelter equipment, based on the prioritization by the international organizations. ✅Over 160 Gazans in need of medical care and their escorts exited Gaza (Dec. 29) through the Kerem Shalom Crossing and continued to the Allenby Bridge Crossing into Jordan. ✅Continued entry of tents and clothing as well as winterization efforts, in accordance with the plan formulated with partners at the CMCC. We will continue facilitating humanitarian aid into Gaza together with our international partners.
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Humanitarian efforts over the past week (28 Dec - 3 Jan): ✅4,200 humanitarian aid trucks entered the Gaza Strip, according to the agreement. The trucks carried food, medical supplies and shelter equipment, based on the prioritization by the international organizations. ✅Over 160 Gazans in need of medical care and their escorts exited Gaza (Dec. 29) through the Kerem Shalom Crossing and continued to the Allenby Bridge Crossing into Jordan. ✅Continued entry of tents and clothing as well as winterization efforts, in accordance with the plan formulated with partners at the CMCC. We will continue facilitating humanitarian aid into Gaza together with our international partners.

COGAT

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Humanitarian efforts over the past week (4-10 Jan): 🚛4,200 humanitarian aid trucks entered the Gaza Strip, according to the agreement. The trucks carried food, medical supplies and shelter equipment, based on the prioritization by the international organizations. 🏨Dozens of Gazans in need of medical care and their escorts exited Gaza (Jan. 5) through the Kerem Shalom Crossing and continued to the Allenby Bridge Crossing into Jordan. ⚙️2 rotation coordinations of humanitarian personnel by registered and approved organizations have been successfully completed. ⛺️Continued entry of tents and clothing as well as winterization efforts, in accordance with the plan formulated with partners at the CMCC. We will continue facilitating humanitarian aid into Gaza together with our international partners.
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Humanitarian efforts over the past week (4-10 Jan): 🚛4,200 humanitarian aid trucks entered the Gaza Strip, according to the agreement. The trucks carried food, medical supplies and shelter equipment, based on the prioritization by the international organizations. 🏨Dozens of Gazans in need of medical care and their escorts exited Gaza (Jan. 5) through the Kerem Shalom Crossing and continued to the Allenby Bridge Crossing into Jordan. ⚙️2 rotation coordinations of humanitarian personnel by registered and approved organizations have been successfully completed. ⛺️Continued entry of tents and clothing as well as winterization efforts, in accordance with the plan formulated with partners at the CMCC. We will continue facilitating humanitarian aid into Gaza together with our international partners.

COGAT

23,645 görüntüleme • 7 ay önce

This guy said a SUV with DHS tags pulled up next to him in Chicago & looked into his vehicle as if they were profiling him & then took off like a bat out of hell on the shoulder with their lights on,but they didn’t seem to be after anyone! They do y seem to abide by road rules!
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This guy said a SUV with DHS tags pulled up next to him in Chicago & looked into his vehicle as if they were profiling him & then took off like a bat out of hell on the shoulder with their lights on,but they didn’t seem to be after anyone! They do y seem to abide by road rules!

Suzie rizzio

211,723 görüntüleme • 10 ay önce

This video was the last thing that Bob Suberi onboard the Handala freedom flotilla sent to me, with the message “we’re still chugging along”. There were 21 beautiful souls onboard the Handala who had every right to bring humanitarian aid into Gaza by sea, in accordance with international law. Instead, the world has allowed for their abduction by Israeli forces and the seizing of the Handala boat by Israel. All we want is to see an end to the famine and forced starvation imposed by Israel. An end to the genocide committed by Israel. An end to the illegal Israeli occupation of Palestine. Free Palestine from Zionist settler colonialism.
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This video was the last thing that Bob Suberi onboard the Handala freedom flotilla sent to me, with the message “we’re still chugging along”. There were 21 beautiful souls onboard the Handala who had every right to bring humanitarian aid into Gaza by sea, in accordance with international law. Instead, the world has allowed for their abduction by Israeli forces and the seizing of the Handala boat by Israel. All we want is to see an end to the famine and forced starvation imposed by Israel. An end to the genocide committed by Israel. An end to the illegal Israeli occupation of Palestine. Free Palestine from Zionist settler colonialism.

Yipeng Ge 葛义朋

18,456 görüntüleme • 1 yıl önce

Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)
0:13

Contact sheet prompting is the hottest AI video technique right now 🤯 If you've seen this technique blowing up, here's why it works: You feed AI one image, and it generates a grid of consistent shots—same face, same outfit, different angles and poses. Instant storyboarding. Full creative control. No reshoots. But doing it manually is brutal: → Write the prompt from scratch → Generate the contact sheet → Crop each frame by hand → Feed frames into a video model one at a time → Repeat for every single product That's hours of work per campaign. This n8n automation handles everything: → Upload a character image + product image → AI analyzes both and writes the contact sheet prompt → Nano Banana Pro generates a 6-frame grid → System extracts each frame automatically → Kling 2.5 creates smooth transitions between frames → 5 video clips land in Airtable ready to use No manual cropping. No frame-by-frame prompting. No tedious busywork. What you get in Airtable: - AI-generated creative prompt - Hero image (model + product) - Full 6-frame contact sheet - 5 cinematic video clips - Approval gates before each step All inside n8n + Airtable. Contact sheet prompting on complete autopilot. I recorded a 20-minute Loom showing exactly how I built this. Want the walkthrough + the full n8n workflow + Airtable base? > Like this post > Comment "CONTACT" And I'll send it over (must be following so I can DM)

Mike Futia

24,589 görüntüleme • 7 ay önce

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.
0:12

Wonderland: Navigating 3D Scenes from a Single Image Contributions: • First, we introduce a representation for controllable 3D generation by leveraging the generative priors from camera-guided video diffusion models. Unlike image models, video diffusion models are trained on extensive video datasets. This enables them to capture comprehensive spatial relationships within scenes across multiple views and embed a form of "3D awareness" in their latent space, which allows us to maintain 3D consistency in novel view synthesis. • Second, to achieve controllable novel view generation, we empower video models with precise control over specified camera motions. We introduce a novel dual-branch conditioning mechanism that effectively incorporates desired diverse camera trajectories into the video diffusion model. This enables expansion of a single image into a multi-view consistent capture of a 3D scene with precise pose control. • Third, to achieve efficient 3D reconstruction, we directly transform video latents into 3DGS. We propose a novel latent-based large reconstruction model (LaLRM) that lifts video latents to 3D in a feed-forward manner. With this design, during inference, our model directly predicts 3DGS from a single input image, effectively aligning the generation and reconstruction tasks—and bridging image space and 3D space—through the video latent space. Compared with reconstructing scenes from images, the video latent space offers a 256× spatial-temporal reduction while retaining essential and consistent 3D structural details. Such a high degree of compression is crucial, as it allows the LaLRM to handle a wider range of 3D scenes within the reconstruction framework, with the same memory constraints.

MrNeRF

52,849 görüntüleme • 1 yıl önce

1- This photo from Sham al-Assad’s birthday at Bagatelle #Dubai provides a glimpse into the family’s lavish exile. 2- Sham’s birthday in #Dubai showed the Assads’ wealth in exile, after they left #Syria in economic ruins. The Times unearthed the image by tracing the social media of the family’s inner circle. 3-#Video shared to Instagram of the second day of Sham’s birthday celebration shows revelers dancing with a #DJ aboard a #luxury private yacht. Promotional materials shared with The Times show the rental likely cost at least several thousand #dollars. 4-Zein al-Assad, center, in white striped dress, at her graduation at the Moscow State Institute of International Relations on June 30. The #photo was found by The Times in a publicly accessible Google #Drive folder hosted by the university.
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1- This photo from Sham al-Assad’s birthday at Bagatelle #Dubai provides a glimpse into the family’s lavish exile. 2- Sham’s birthday in #Dubai showed the Assads’ wealth in exile, after they left #Syria in economic ruins. The Times unearthed the image by tracing the social media of the family’s inner circle. 3-#Video shared to Instagram of the second day of Sham’s birthday celebration shows revelers dancing with a #DJ aboard a #luxury private yacht. Promotional materials shared with The Times show the rental likely cost at least several thousand #dollars. 4-Zein al-Assad, center, in white striped dress, at her graduation at the Moscow State Institute of International Relations on June 30. The #photo was found by The Times in a publicly accessible Google #Drive folder hosted by the university.

Qusay Noor

222,341 görüntüleme • 8 ay önce

This week Lebanon installed one of the largest statues of Jesus Christ in the Middle East. The statue stands 26 meters tall, with a 16 meter figure of Christ mounted on a 10 meter base, on Jabal al-Salib, which translates to Mount of the Cross, in the village of Al Qaa in the Bekaa Valley overlooking the Syrian border. The project was funded and built by local resident Fadi Elias Awad in cooperation with the Al Qaa municipality. Al Qaa is one of the oldest Christian communities in the region, populated mainly by Maronite and Greek Catholic families. The village was previously on the direct frontline with *S*S and was targeted by a terrorist bombing at its church. The statue was described by residents as a symbol of Christian presence, faith, and resilience on their land. The wider religious site including a church is still under construction.​​​​​​​​​​​​​​​​ Credit: sacredchad for editing this video
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This week Lebanon installed one of the largest statues of Jesus Christ in the Middle East. The statue stands 26 meters tall, with a 16 meter figure of Christ mounted on a 10 meter base, on Jabal al-Salib, which translates to Mount of the Cross, in the village of Al Qaa in the Bekaa Valley overlooking the Syrian border. The project was funded and built by local resident Fadi Elias Awad in cooperation with the Al Qaa municipality. Al Qaa is one of the oldest Christian communities in the region, populated mainly by Maronite and Greek Catholic families. The village was previously on the direct frontline with *S*S and was targeted by a terrorist bombing at its church. The statue was described by residents as a symbol of Christian presence, faith, and resilience on their land. The wider religious site including a church is still under construction.​​​​​​​​​​​​​​​​ Credit: sacredchad for editing this video

Trad West

19,692 görüntüleme • 5 ay önce