feat: Add pre-generated podcast cache with Git LFS

- 8 example topics with instant playback
- Text cache: summaries, scripts, paper info
- Audio cache: MP3 files via Git LFS (4MB each)
- Total cache size: ~32MB audio + ~100KB text
- Enables instant demo for hackathon judges

.gitattributes

@@ -1,35 +1,3 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files should use Git LFS
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -25,14 +25,17 @@ wheels/
 .installed.cfg
 *.egg
 
-# Audio files (generated)
-assets/audio/*.mp3
-assets/audio/*.wav
-
-# Cache
-cache/
-*.cache
-.cache/
+# Audio files (generated locally for testing)
+# Keep pre-generated podcasts for cache
+!assets/audio/podcast_*.wav
+!assets/audio/podcast_*.mp3
+assets/audio/test_*.mp3
+assets/audio/test_*.wav
+
+# Cache files (commit for HF Spaces persistence)
+!cache/
+!cache/*.json
+!cache/*.txt
 
 # IDEs
 .vscode/

.xetattributes

@@ -0,0 +1,4 @@
+
+# Audio files should use Xet storage
+*.mp3 filter=xet diff=xet merge=xet -text
+*.wav filter=xet diff=xet merge=xet -text

app.py

@@ -77,11 +77,30 @@ class ScienceStoryteller:
             cached_result = self.cache.get(topic)
             if cached_result:
                 summary, script, audio_path, paper_info = cached_result
-                file_size = get_file_size_mb(audio_path)
-                duration = estimate_duration(script)
-                status = f"⚡ Instant result from cache! {duration // 60}min {duration % 60}s podcast ({file_size:.1f}MB) [Pre-generated example]"
-                logger.info(f"Cache hit for: {topic}")
-                return (summary, script, audio_path, paper_info, status)
+                
+                # If audio file exists in cache, return instant result
+                if audio_path:
+                    file_size = get_file_size_mb(audio_path)
+                    duration = estimate_duration(script)
+                    status = f"⚡ Instant result from cache! {duration // 60}min {duration % 60}s podcast ({file_size:.1f}MB) [Pre-generated example]"
+                    logger.info(f"Cache hit with audio for: {topic}")
+                    return (summary, script, audio_path, paper_info, status)
+                else:
+                    # Cache has text but no audio - generate audio only
+                    logger.info(f"Cache hit (text only) for: {topic} - generating audio")
+                    progress(0.8, desc="🔊 Generating audio from cached script...")
+                    formatted_script = format_podcast_script(script)
+                    audio_path = await self.audio_agent.text_to_speech(formatted_script)
+                    
+                    if audio_path:
+                        # Update cache with audio path
+                        self.cache.set(topic, summary, script, audio_path, paper_info)
+                        file_size = get_file_size_mb(audio_path)
+                        duration = estimate_duration(script)
+                        status = f"✅ Generated audio from cached script! {duration // 60}min {duration % 60}s podcast ({file_size:.1f}MB) [Hybrid cache]"
+                        return (summary, script, audio_path, paper_info, status)
+                    else:
+                        return (summary, script, None, paper_info, "⚠️ Cached summary available but audio generation failed")
             
             # Step 1: RETRIEVE papers
             progress(0.1, desc="🔍 Searching for research papers...")

assets/audio/podcast_1763930591.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f8c05ffc93fcc8258ae2c7bafb2db488206e01839e2df1a3d1c6723312238c4d
+size 4439468

assets/audio/podcast_1763930653.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e5fe2daded863a2c41d70dbd217138bc0b69a25381e7360013a8bd90b2dbe26
+size 4484012

assets/audio/podcast_1763930711.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1c3f5a142b596b2c27b59c34fba2a94055ed14eb9e169f194c4914ceb292498
+size 4190636

assets/audio/podcast_1763930772.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:807a43375eda5c636689560df38a1fe50861d222013387533ac1348cc4cab3c2
+size 4176428

assets/audio/podcast_1763930824.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8a5183acafaa6108ec22a0270140cec2e9ea4c14dad955ce38dabe7cbed8bd39
+size 3983276

assets/audio/podcast_1763930878.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c5512bbb13b92c95583e9b27320caf2cce325469587d425bce9f055fc5ce989
+size 4181420

assets/audio/podcast_1763930931.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:034a3273b87d694b55b9f6bab338aee5446e1ddafefa8dc7338c005281719a59
+size 4434476

assets/audio/podcast_1763930985.mp3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c689ff9474d3edcd5418feebbec2dc9b921198a70c3874b3129e8ed9e2388b7
+size 4456364

cache/24421acf21f6d6909fa1c096b631b4c3_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Global Surface Ocean Acidification Indicators From 1750 to 2100
+
+**Authors:** Li‐Qing Jiang, J. Dunne, B. Carter, J. Tjiputra, J. Terhaar et al. (29 authors)
+
+**Published:** 2023
+
+**arXiv ID:** eb56b58644e25af9ed0d0ac3bdf62d14c1c95f42
+
+**Link:** https://arxiv.org/abs/eb56b58644e25af9ed0d0ac3bdf62d14c1c95f42

cache/24421acf21f6d6909fa1c096b631b4c3_script.txt

@@ -0,0 +1,21 @@
+Picture this: you're snorkeling in crystal clear waters, watching a vibrant coral reef teeming with life. Clownfish dart between orange and pink corals, while sea urchins cling to the reef with their spiny shells. Now imagine returning to that same spot fifty years from now, only to find a ghostly white skeleton where that thriving reef once stood. This isn't science fiction – it's the potential reality of ocean acidification, and new research is giving us our clearest picture yet of what lies ahead for our oceans.
+
+You've probably heard about climate change warming our planet, but there's another side to the carbon dioxide story that gets less attention. When we pump CO2 into the atmosphere, about a quarter of it doesn't stay there – it gets absorbed by our oceans. And while this might sound like the ocean is doing us a favor by soaking up some of that excess carbon, it's actually creating a whole new problem.
+
+Here's what happens: when carbon dioxide dissolves into seawater, it forms carbonic acid. This makes the ocean more acidic, kind of like how adding lemon juice makes water more sour. The ocean is still basic overall – we're not talking about sulfuric acid levels here – but even small changes in ocean chemistry can have huge consequences for marine life.
+
+Think about creatures like oysters, crabs, and those colorful corals I mentioned. They build their shells and skeletons using calcium carbonate, which is basically nature's cement. But in more acidic water, this process becomes incredibly difficult. It's like trying to build a sandcastle while someone keeps washing away your foundation. Some creatures can't build their protective shells at all, while others see their existing shells start to dissolve.
+
+Until now, scientists have had a rough idea of where ocean acidification is headed, but they've been working with incomplete maps and fuzzy timelines. That's where this groundbreaking new research comes in. An international team of scientists decided to create the most detailed roadmap of ocean acidification we've ever had – think Google Maps, but for ocean chemistry changes over the next century.
+
+They did something pretty clever. Instead of relying on just one computer model or one set of data, they combined information from fourteen different Earth system models with real measurements taken from oceans around the world. It's like asking fourteen different weather forecasters for their predictions, then combining their insights with actual temperature readings to get the most accurate forecast possible.
+
+Their virtual crystal ball tracks ten different aspects of ocean chemistry, from basic acidity levels to the availability of those crucial building blocks that sea creatures need for their shells. They've mapped out these changes for the entire global ocean surface, creating decade-by-decade projections from 1750 all the way to 2100.
+
+But here's what makes this research really powerful – they didn't just assume one future scenario. Instead, they ran their models under five different possibilities, ranging from a world where we dramatically cut emissions to one where we continue on our current high-emissions path. This gives us a range of potential futures, almost like having multiple endings to choose from in our planetary story.
+
+The results show that no matter which path we take, some level of ocean acidification is already locked in due to the carbon we've already released. However, the severity of changes varies dramatically depending on our future choices. In the most optimistic scenario, where we aggressively reduce emissions, many ocean regions could stabilize by mid-century. But in high-emissions scenarios, we're looking at changes that would make large parts of the ocean virtually uninhabitable for many species we depend on today.
+
+This isn't just an academic exercise. Coastal communities around the world depend on healthy marine ecosystems for food, jobs, and storm protection. The seafood industry alone supports millions of livelihoods globally. This new forecasting tool gives scientists, policymakers, and coastal managers the detailed information they need to prepare for what's coming and to make informed decisions about everything from marine protected areas to emission reduction targets.
+
+The beauty of this research is that it transforms ocean acidification from an abstract future threat into something we can visualize, plan for, and potentially mitigate. We now have our roadmap – the question is which route we'll choose to take.

cache/24421acf21f6d6909fa1c096b631b4c3_summary.txt

@@ -0,0 +1,7 @@
+## Ocean Acidification: Mapping Our Changing Seas
+
+This research tackles a critical environmental challenge: predicting how ocean acidification will unfold across the globe from pre-industrial times through the end of this century. Ocean acidification occurs when the ocean absorbs carbon dioxide from the atmosphere, making seawater more acidic and threatening marine life like coral reefs and shellfish. To help scientists and policymakers prepare for these changes, researchers needed comprehensive, reliable predictions of acidification patterns worldwide.
+
+The team created an advanced forecasting tool by combining data from 14 different Earth System Models with real-world ocean measurements. They tracked 10 key indicators of ocean chemistry—including pH levels, carbon content, and the availability of minerals that sea creatures need to build shells and skeletons. Their analysis covers the entire global ocean surface on a detailed grid, providing decade-by-decade projections from 1750 to 2100 under five different future climate scenarios, ranging from aggressive emissions reductions to high-emissions pathways.
+
+This comprehensive dataset represents a significant improvement over previous ocean acidification forecasts, offering unprecedented detail and coverage. The findings provide scientists, resource managers, and policymakers with state-of-the-art tools to understand how ocean acidification will interact with climate change in different regions and under various emission scenarios. This information is crucial for developing strategies to protect marine ecosystems and coastal communities that depend on healthy oceans, while also guiding efforts to reduce greenhouse gas emissions.

cache/40470ecbc8f20a349588205640b21796_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Accurate structure prediction of biomolecular interactions with AlphaFold 3
+
+**Authors:** Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green et al. (48 authors)
+
+**Published:** 2024
+
+**arXiv ID:** 7572ba7f604ef95d7acdd657ebac458106bd35df
+
+**Link:** https://arxiv.org/abs/7572ba7f604ef95d7acdd657ebac458106bd35df

cache/40470ecbc8f20a349588205640b21796_script.txt

@@ -0,0 +1,19 @@
+Imagine you're trying to solve the world's most complex 3D puzzle, but instead of just a few hundred pieces, you're dealing with millions of tiny molecular components that need to fit together perfectly for life to exist. And here's the kicker – until recently, we could only see some of the pieces clearly while the rest remained frustratingly blurry.
+
+Well, that puzzle just got a whole lot easier to solve, thanks to a groundbreaking advancement called AlphaFold 3. And trust me, this is the kind of scientific breakthrough that's going to change everything from how we discover new medicines to how we understand the very foundations of life itself.
+
+Let me paint you a picture of what's happening inside your body right now. At this very moment, millions of biological molecules are dancing together in an incredibly choreographed performance. Proteins are shaking hands with DNA, small drug molecules are finding their perfect parking spots, and antibodies are playing a sophisticated game of molecular recognition to keep you healthy. For decades, scientists have been like theater critics trying to review this performance while sitting in the dark, able to make out only rough shapes and movements.
+
+The previous version of this technology, AlphaFold 2, was like someone finally turning on a spotlight – but it only illuminated the individual dancers, the proteins, one at a time. Scientists could finally see these molecules in stunning detail, and it was revolutionary. But imagine trying to understand a tango by watching each dancer separately. You'd miss the entire story, which happens in the space between them, in how they move together, touch, and respond to each other.
+
+That's exactly where AlphaFold 3 comes in, and this is where things get really exciting. The researchers completely reimagined their approach using something called diffusion technology. Think of it like watching a Polaroid photo develop, but in reverse and then forward again. The system starts with what's essentially visual static – complete molecular chaos – and then gradually, like an artist refining a sketch, it removes the noise and reveals the hidden structure underneath. But here's the magic: instead of just showing us one molecule at a time, it reveals entire molecular neighborhoods, complete with all their interactions and relationships.
+
+The results are nothing short of spectacular. Remember how I mentioned drug discovery earlier? Well, when pharmaceutical companies develop new medications, they need to understand exactly how a drug molecule will dock with its target protein – kind of like finding the right key for a very specific lock. AlphaFold 3 is dramatically better at predicting these crucial interactions than any previous method. We're talking about potentially shaving years off drug development timelines and making treatments more effective.
+
+But it doesn't stop there. The system is also revolutionizing our understanding of how proteins interact with DNA and RNA – the fundamental information storage and processing systems of life. And in a world where we're still grappling with infectious diseases and autoimmune conditions, AlphaFold 3's ability to predict how antibodies recognize and bind to their targets is absolutely game-changing for vaccine and immunotherapy development.
+
+What makes this particularly remarkable is that we now have one incredibly sophisticated tool that can handle all of these different types of molecular interactions. It's like having a universal translator for the language of life itself. Previously, scientists needed different specialized tools for each type of interaction, kind of like needing separate apps for every different language you wanted to translate. Now, they have one master key that unlocks multiple doors.
+
+So what does this mean for the future? We're looking at a world where drug discovery becomes faster and more precise, where we can design better treatments for diseases that have puzzled us for generations, and where our fundamental understanding of biological processes takes quantum leaps forward. Imagine developing personalized medicines with unprecedented precision, or finally cracking the code on complex diseases like Alzheimer's or cancer by understanding exactly how molecules misbehave at the cellular level.
+
+AlphaFold 3 isn't just a better version of what came before – it's a completely new way of seeing and understanding the molecular world that makes us who we are. And honestly, we're probably only just beginning to scratch the surface of what this breakthrough will make possible.

cache/40470ecbc8f20a349588205640b21796_summary.txt

@@ -0,0 +1,7 @@
+## AlphaFold 3: A Major Leap Forward in Predicting How Biological Molecules Interact
+
+Scientists have long struggled to understand how different biological molecules—proteins, DNA, RNA, drugs, and other chemical compounds—fit together and interact within living cells. This is crucial for drug discovery, disease research, and understanding how life works at the molecular level. While the previous version, AlphaFold 2, revolutionized protein structure prediction, it was limited mainly to predicting the shapes of individual proteins rather than how multiple different types of molecules interact with each other.
+
+AlphaFold 3 addresses this challenge with a completely redesigned artificial intelligence system based on "diffusion" technology—a method that starts with random noise and gradually refines it into accurate molecular structures. Unlike previous tools that were specialized for specific types of interactions, AlphaFold 3 can simultaneously predict how proteins, DNA, RNA, small drug molecules, ions, and chemically modified components all fit together in complex biological assemblies.
+
+The results represent a major breakthrough in computational biology. AlphaFold 3 significantly outperforms existing specialized tools across multiple areas: it's far more accurate than current methods for predicting how drugs bind to proteins, much better at modeling protein-DNA/RNA interactions, and substantially more precise at predicting antibody-antigen binding (crucial for vaccine and immunotherapy development). This unified approach means researchers now have a single, highly accurate tool for understanding the intricate molecular interactions that drive biological processes, potentially accelerating drug discovery and our fundamental understanding of life itself.

cache/598a2e89c318f4b49efc9e839484ad1a_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Immune correlates of protection as a game changer in tuberculosis vaccine development
+
+**Authors:** Jing Wang, Xiao-Yong Fan, Zhidong Hu
+
+**Published:** 2024
+
+**arXiv ID:** f1ce01c0ee9e894f701785cf7df9826b80a65b82
+
+**Link:** https://arxiv.org/abs/f1ce01c0ee9e894f701785cf7df9826b80a65b82

cache/598a2e89c318f4b49efc9e839484ad1a_script.txt

@@ -0,0 +1,21 @@
+Imagine you're trying to navigate through a dense forest at night without a flashlight or compass. You're stumbling around in the dark, hoping you're heading in the right direction, but you have no way to know if you're on the right path until you either reach your destination or realize you've been walking in circles for hours. This is essentially what tuberculosis vaccine researchers have been dealing with for decades.
+
+TB is still one of the world's biggest killers, claiming over a million lives every year. You'd think we'd have figured out how to prevent it by now, right? Well, here's the thing – we do have one TB vaccine that's been around for about a century, but it's not very good at protecting adults from the lung disease that spreads from person to person. So scientists have been working hard to develop better vaccines, but they've been doing it essentially blindfolded.
+
+Here's where it gets interesting. When vaccine researchers are developing a new shot, they need what are called "correlates of protection." Think of these as early warning signals from your immune system that say "Hey, this vaccine is working! This person is going to be protected." It's like having a GPS for vaccine development – these biological markers can tell researchers if they're heading in the right direction long before they have to do massive, expensive clinical trials involving thousands of people.
+
+For diseases like measles or hepatitis B, scientists know exactly what to look for. They can measure specific antibodies in your blood and say with confidence, "Yep, you're protected." But with tuberculosis, it's like the immune system is speaking in a completely different language that researchers haven't been able to decode.
+
+Why is TB so tricky? Well, tuberculosis is caused by bacteria that are incredibly sneaky. They can hide inside your immune cells for years, like uninvited houseguests who've figured out how to stay under the radar. Your immune system might know they're there, but it can't always kick them out. This means the usual suspects – those antibodies that work so well for other diseases – aren't enough to protect against TB.
+
+The bacteria have basically evolved to be master hide-and-seek players. They can sit quietly in your lungs for decades without causing problems, but then spring into action when your immune system gets weakened by something else. This complexity means that protective immunity against TB probably involves multiple parts of your immune system working together in ways that scientists are still trying to understand.
+
+But here's the exciting part – recent scientific breakthroughs are giving researchers new tools to crack this code. Advanced techniques that can analyze immune responses in incredible detail are revealing patterns that were invisible just a few years ago. Scientists can now look at not just what immune cells are present, but what they're actually doing, how they're communicating with each other, and how they're coordinating their response to the TB bacteria.
+
+Some researchers are finding promising clues by studying people who seem to be naturally resistant to TB, even when they're exposed to it repeatedly. Others are looking at the immune responses in people who had TB and recovered, trying to figure out what their immune systems did right. It's like detective work, but instead of looking for fingerprints, they're looking for immune fingerprints.
+
+The researchers behind this new analysis argue that we're at a turning point. All these new scientific tools and approaches are creating opportunities that didn't exist before. They believe that identifying reliable correlates of protection for TB isn't just possible anymore – it's inevitable.
+
+And when that breakthrough happens, everything changes. Instead of stumbling around in the dark, vaccine developers will finally have their compass and flashlight. They'll be able to design vaccines more strategically, test them more efficiently, and know much earlier in the process whether they're likely to work in the real world.
+
+Given that TB affects millions of people worldwide, particularly in lower-income countries, finding these immune guideposts could dramatically speed up the development of effective vaccines. We're talking about potentially saving millions of lives and finally getting ahead of a disease that has plagued humanity for thousands of years. After decades of working in the dark, TB vaccine researchers might finally be about to turn on the lights.

cache/598a2e89c318f4b49efc9e839484ad1a_summary.txt

@@ -0,0 +1,7 @@
+## Tuberculosis Vaccine Development Needs Better Roadmaps
+
+Developing effective vaccines against tuberculosis (TB) has been extremely challenging, partly because scientists don't have reliable "correlates of protection" (CoPs) to guide their work. Think of CoPs as biological markers or immune responses that can predict whether a vaccine will actually protect people from getting sick. Without these markers, vaccine developers are essentially working blindfolded – they can't easily tell during early testing whether their experimental vaccines are likely to succeed in real-world trials.
+
+This research paper reviews the current state of TB vaccine development and examines potential immune markers that could serve as these crucial guideposts. The authors analyzed existing research to identify promising biological signals that might indicate protective immunity against TB, while also discussing the major obstacles that have prevented scientists from identifying reliable CoPs so far. They argue that recent scientific advances have created new opportunities to finally crack this puzzle.
+
+The authors conclude that successfully identifying validated correlates of protection would revolutionize TB vaccine development. With reliable CoPs in hand, researchers could design better vaccines more rationally, test them more efficiently, and potentially accelerate the timeline for bringing effective TB vaccines to the millions of people who need them worldwide. Given that TB remains one of the world's deadliest infectious diseases, such a breakthrough could have enormous global health impact.

cache/68e2edd3a79c753c24f00d9a28e90dae_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Quantum Entanglement and Nonlocality: Challenging the Local Realism of Classical Physics
+
+**Authors:** Xiaoci Liu
+
+**Published:** 2024
+
+**arXiv ID:** fb0d6c6633510a75d877b02debfd2684ab16ae04
+
+**Link:** https://arxiv.org/abs/fb0d6c6633510a75d877b02debfd2684ab16ae04

cache/68e2edd3a79c753c24f00d9a28e90dae_script.txt

@@ -0,0 +1,19 @@
+Imagine for a moment that you have a magical pair of coins. You flip one coin here on Earth, and it lands heads. At that exact same instant, its partner coin on the moon automatically flips to tails. No signal travels between them, no force pushes the distant coin, yet somehow they're perfectly synchronized across a quarter million miles of empty space. Sounds impossible, right? Well, welcome to the bizarre world of quantum physics, where this kind of impossible thing happens every day.
+
+Today we're diving into one of the most mind-bending discoveries in modern science, something that even Albert Einstein called "spooky action at a distance." We're talking about quantum entanglement, a phenomenon so strange that it's forcing us to completely rethink everything we thought we knew about reality itself.
+
+So what exactly is quantum entanglement? Think of it this way. In our everyday world, if I want to affect something, I need to touch it, push it, or send some kind of signal to it. If I want to turn on a light across the room, I either walk over and flip the switch, or I send an electrical signal through a wire, or maybe I use a remote control that sends invisible waves through the air. There's always some kind of connection, some way that information travels from point A to point B.
+
+But quantum entanglement throws this common sense right out the window. When two particles become entangled, they form a mysterious connection that seems to transcend space and time. Measure one particle and find it spinning clockwise, and you'll instantly know that its entangled partner, whether it's across the room or across the galaxy, is spinning counterclockwise. It's not that they were predetermined to spin in opposite directions. The act of measuring one particle actually seems to instantly determine the state of both particles, no matter how far apart they are.
+
+Einstein hated this idea. Along with his colleagues Podolsky and Rosen, he came up with a famous thought experiment in the 1930s, basically arguing that quantum entanglement couldn't be real. They believed there had to be some hidden information that the particles carried with them, like secret instructions that told them how to behave. Einstein preferred a universe where everything had a definite, predetermined state, and where nothing could influence anything else faster than the speed of light.
+
+But Einstein, brilliant as he was, turned out to be wrong about this one. In the 1960s, a physicist named John Bell figured out a way to test whether Einstein's hidden information theory was correct. And when scientists actually performed these tests, the results were crystal clear. Quantum entanglement is absolutely real. The universe really does allow for these instant connections between distant particles.
+
+This discovery is what scientists call "nonlocality," and it's completely revolutionizing our understanding of reality. We're not just talking about some abstract physics concept here. This is forcing us to accept that the universe doesn't work the way our everyday experience tells us it should. Objects can indeed influence each other instantaneously across vast distances, without any signal or force traveling between them.
+
+But here's where it gets really exciting. This isn't just a philosophical puzzle for physicists to argue about. Quantum entanglement is already being put to work in incredible ways. Scientists are using it to build quantum computers that could solve problems in minutes that would take today's best computers thousands of years. They're developing quantum communication systems that would be absolutely impossible to hack, creating the most secure messaging systems imaginable. Some researchers are even exploring whether quantum entanglement might help explain mysteries of consciousness and the human brain.
+
+The research we're discussing today, by Xiaoci Liu, pulls together decades of experiments and theories to show us just how profound this discovery really is. We're not just talking about a new technology or even a new scientific theory. Quantum entanglement is fundamentally changing how we understand the very fabric of reality. It's showing us that the universe is far stranger, far more interconnected, and far more mysterious than we ever imagined.
+
+As we look to the future, quantum entanglement promises to unlock technologies that will seem like magic to us today. But perhaps more importantly, it's reminding us that no matter how much we think we understand about our universe, there are always new mysteries waiting to surprise us. And sometimes, those mysteries turn out to be the keys to revolutionary breakthroughs that change everything.

cache/68e2edd3a79c753c24f00d9a28e90dae_summary.txt

@@ -0,0 +1,5 @@
+## Summary: Quantum Entanglement and Its Challenge to Classical Physics
+
+This research paper tackles one of the most puzzling phenomena in modern physics: quantum entanglement, where two particles become mysteriously connected so that measuring one instantly affects the other, regardless of the distance separating them. This "spooky action at a distance" directly contradicts our everyday understanding of reality, where objects can only influence each other through direct contact or nearby forces. The author, Xiaoci Liu, explores how this quantum phenomenon challenges the foundations of classical physics and examines its revolutionary implications across multiple fields.
+
+Using a comprehensive literature review approach, the study examines landmark experiments and theories, particularly the famous Einstein-Podolsky-Rosen thought experiment and Bell's inequality tests, which proved that quantum entanglement is real and not just a theoretical curiosity. The research reveals that quantum entanglement demonstrates "nonlocality" – the ability for information to be shared instantaneously between distant particles, defying our classical notions of space and time. This finding is significant because it opens doors to revolutionary technologies like quantum computing and ultra-secure quantum communication, while simultaneously forcing scientists and philosophers to reconsider fundamental questions about the nature of reality itself. The paper concludes that quantum entanglement represents one of the most profound discoveries in modern science, reshaping both our technological capabilities and our philosophical understanding of the universe.

cache/b379b40c8b7ff24bf60f91bcc9d86f24_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Recent advances in the delivery and applications of nonviral CRISPR/Cas9 gene editing
+
+**Authors:** Frazer H. Sinclair, A. A. Begum, Charles C. Dai, I. Toth, P. Moyle
+
+**Published:** 2023
+
+**arXiv ID:** 2777c265653e7b1ad7a36fd5d00c0e9590527407
+
+**Link:** https://arxiv.org/abs/2777c265653e7b1ad7a36fd5d00c0e9590527407

cache/b379b40c8b7ff24bf60f91bcc9d86f24_script.txt

@@ -0,0 +1,23 @@
+What if I told you that scientists have developed molecular scissors that can cut and paste DNA like you're editing a Word document? And what if those scissors could potentially cure diseases that have plagued humanity for centuries? Well, that technology exists today, and it's called CRISPR. But here's the catch – getting those molecular scissors to the right place in your body has been like trying to deliver a package to a specific apartment in a skyscraper while blindfolded. Until now.
+
+Let me paint you a picture. Imagine you're a scientist who's just discovered the perfect way to fix a broken gene that causes a devastating disease. You have the tools – CRISPR gene editing technology that works like the most precise pair of molecular scissors ever invented. These scissors can find exactly the right spot in someone's DNA, cut out the problematic section, and replace it with a healthy version. It sounds like science fiction, but it's absolutely real.
+
+But here's where things get tricky. Having the perfect tool doesn't mean much if you can't get it where it needs to go. Think about it this way – you might have the world's best surgeon, but if they can't get to the operating room, they can't help anyone. That's exactly the problem scientists have been wrestling with for years.
+
+For a while, researchers tried using modified viruses as delivery trucks for CRISPR. Now, I know what you're thinking – using viruses to deliver medicine sounds a bit like fighting fire with fire. And you're not wrong to be concerned. While viruses are naturally good at getting inside our cells, they come with some serious baggage. They can trigger unwanted immune reactions, they're expensive and difficult to produce on a large scale, and frankly, they make both patients and doctors nervous.
+
+So scientists went back to the drawing board and asked themselves: what if we didn't need viruses at all? What if we could build our own delivery vehicles from scratch?
+
+This is where the story gets really exciting. Researchers have been developing what they call non-viral delivery systems. Think of these as custom-built, high-tech delivery trucks designed specifically for the job. Instead of using viruses, they're creating these vehicles from materials like specialized fats, custom-designed polymers, tiny proteins, and even microscopic nanoparticles.
+
+These new delivery systems are like the difference between sending a package through an unreliable postal service versus hiring a premium courier service. They're designed to be safer, more reliable, and much easier to produce when you need millions of doses.
+
+But the real genius is in the details. These delivery vehicles can be programmed almost like GPS systems. Scientists can design them to seek out specific types of cells, deliver their CRISPR cargo precisely where it's needed, and then basically disappear without causing any fuss. It's like having a delivery drone that can navigate directly to the right cellular address, drop off its package, and vanish without a trace.
+
+What makes this even more impressive is that these systems can be manufactured at industrial scales without the complex biological processes required for viral vectors. Imagine the difference between hand-crafting individual items versus setting up an assembly line – that's the kind of manufacturing advantage we're talking about.
+
+The implications of this breakthrough are staggering. We're not just talking about incremental improvements – this could be the key that unlocks CRISPR's full potential for treating human disease. Genetic disorders that have been considered untreatable for generations might finally have a cure. Certain types of cancer could be stopped in their tracks by editing the genes that make them grow.
+
+Looking ahead, this isn't just about making gene therapy possible – it's about making it practical, affordable, and accessible to patients who need it. We're moving from a world where gene editing was an exciting laboratory experiment to one where it could become as routine as getting a vaccination.
+
+The molecular scissors were always sharp enough. Now, finally, we're learning how to deliver them exactly where they need to go. And that changes everything.

cache/b379b40c8b7ff24bf60f91bcc9d86f24_summary.txt

@@ -0,0 +1,7 @@
+## CRISPR Gene Editing Gets a Delivery Upgrade
+
+CRISPR/Cas9 is a revolutionary gene editing tool that works like molecular scissors, allowing scientists to cut and modify DNA with unprecedented precision. This technology holds enormous promise for treating genetic diseases, cancer, and other conditions by directly fixing faulty genes. However, there's been a major roadblock: getting the CRISPR system safely and effectively delivered to the right cells in the human body. Traditional delivery methods using modified viruses have shown promise but come with significant drawbacks, including safety concerns about immune reactions, difficulty in mass production, and limited capacity for carrying the genetic cargo.
+
+This research review examines the rapid development of non-viral delivery systems as a safer alternative to viral vectors. Scientists have been developing innovative delivery vehicles made from lipids (fats), polymers, peptides, and tiny inorganic nanoparticles that can transport CRISPR components directly to target tissues. These non-viral approaches offer several advantages: they're potentially safer, easier to manufacture at large scales, and can be designed to minimize off-target effects where the gene editing occurs in unintended locations.
+
+The significance of this work lies in making CRISPR gene therapy more clinically viable and accessible. By solving the delivery challenge with these advanced non-viral systems, researchers are paving the way for CRISPR treatments to move from laboratory experiments to real-world medical applications. This could accelerate the development of gene therapies for previously untreatable genetic disorders and bring precision medicine closer to becoming a routine part of healthcare.

cache/c72a1737a2b36cc9b63522cfb8d752ca_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Time series prediction model using LSTM-Transformer neural network for mine water inflow
+
+**Authors:** Junwei Shi, Shiqi Wang, Pengfei Qu, Jianli Shao
+
+**Published:** 2024
+
+**arXiv ID:** 8cdfa5f70c7855bb297ec93fced80fa685fffdfd
+
+**Link:** https://arxiv.org/abs/8cdfa5f70c7855bb297ec93fced80fa685fffdfd

cache/c72a1737a2b36cc9b63522cfb8d752ca_script.txt

@@ -0,0 +1,23 @@
+Imagine you're a miner working deep underground when suddenly, water starts rushing in from nowhere. You have minutes, maybe less, to get yourself and your crew to safety before the tunnels flood completely. This isn't science fiction – it's a terrifying reality that miners face around the world. But what if we could predict these deadly floods before they happen? That's exactly what a team of researchers set out to solve, and their breakthrough could save countless lives.
+
+Mining has always been dangerous work, but water inflow is one of the most unpredictable and deadly threats miners face. Unlike other hazards that give warning signs, water can burst through tunnel walls with little notice, turning safe passages into death traps in minutes. The problem is that underground water behaves like a wild animal – completely unpredictable, following no clear patterns that humans can easily spot.
+
+For years, mining companies have tried to forecast when and where water might break through, but traditional methods just weren't cutting it. The water flow data looks chaotic, jumping up and down seemingly at random. It's like trying to predict the weather by looking at clouds – there are patterns there, but they're incredibly complex and hidden beneath layers of seemingly random behavior.
+
+That's where artificial intelligence comes in. The research team realized they needed something smarter than human pattern recognition – they needed machines that could spot the subtle relationships in this chaotic data that our brains simply can't process.
+
+They turned to two cutting-edge AI technologies that, when combined, created something more powerful than either could achieve alone. The first is called LSTM, which stands for Long Short-Term Memory. Think of LSTM like having a friend with an incredible memory who can remember important details from months ago and connect them to what's happening right now. In the world of water prediction, this means the system can remember that unusual rainfall pattern from three months back and factor it into today's forecast.
+
+The second technology is called a Transformer, and it works like having the world's best detective on your team. Transformers use something called self-attention, which is basically the ability to look at all the available clues and automatically figure out which ones are actually important. While LSTM is great at remembering the past, Transformers excel at understanding which pieces of information deserve the most attention right now.
+
+When the researchers combined these two AI approaches, something remarkable happened. It was like giving their system both perfect memory and brilliant detective skills at the same time. The hybrid model could remember long-term patterns while simultaneously figuring out which current factors mattered most for making accurate predictions.
+
+To test their creation, the team used real data from the Baotailong mine in China's Heilongjiang Province. This wasn't theoretical – this was actual water flow information from a working mine where people's lives depend on accurate flood predictions. They ran their new system against several other prediction methods, including older AI models and traditional approaches.
+
+The results were impressive. Their LSTM-Transformer hybrid didn't just win – it dominated every other method they tested. It was more accurate, more reliable, and better at catching the subtle warning signs that other systems missed. The sweet spot turned out to be using seventy percent of their historical data to train the system and thirty percent to test it, creating the most reliable early warning system for mine flooding that anyone had developed.
+
+But here's what makes this research truly exciting – it's not just about better predictions. This breakthrough represents a new way of thinking about chaotic, unpredictable systems. The same techniques could potentially be applied to predicting other natural disasters, from flash floods to landslides, anywhere that we need to find patterns in seemingly random data.
+
+For mining companies, this technology could transform safety protocols. Instead of reacting to floods after they start, mines could evacuate workers hours or even days before dangerous water inflow begins. That's the difference between a close call and a tragedy.
+
+We're looking at a future where artificial intelligence doesn't just make our phones smarter or recommend better movies – it actively saves lives by seeing dangers coming before humans ever could. And for the thousands of miners who head underground every day, that future can't come soon enough.

cache/c72a1737a2b36cc9b63522cfb8d752ca_summary.txt

@@ -0,0 +1,7 @@
+## Predicting Mine Water Inflow to Prevent Flooding Disasters
+
+This research tackles a critical safety challenge in mining: predicting dangerous water inflow that can cause devastating mine floods. Mine water inflow is notoriously difficult to forecast because it behaves unpredictably and doesn't follow simple patterns, yet accurate predictions are essential for early flood warnings that can save lives and prevent accidents.
+
+The researchers developed a new prediction system that combines two powerful artificial intelligence techniques: LSTM (Long Short-Term Memory) networks, which excel at remembering long-term patterns in data, and Transformer algorithms, which use "self-attention" mechanisms to identify the most important relationships in the data. They tested their hybrid model using real water flow data from the Baotailong mine in China's Heilongjiang Province, experimenting with different ways to split their data between training and testing to optimize results.
+
+The LSTM-Transformer hybrid model significantly outperformed existing approaches, including individual LSTM, CNN (Convolutional Neural Network), Transformer, and CNN-LSTM models across all accuracy measures. The best results came from using 70% of the data for training and 30% for testing. This breakthrough could provide mining operations with more reliable early warning systems, potentially preventing the kind of flooding accidents that have become increasingly common in recent years and protecting both miners and mining infrastructure.

cache/e19c8cfeb70a65b29aa17aa2ec5732cf_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Galactic Trajectories of Interstellar Objects 1I/'Oumuamua, 2I/Borisov, and 3I/Atlas
+
+**Authors:** Shokhruz Kakharov, Abraham Loeb
+
+**Published:** 2024
+
+**arXiv ID:** 12d84412ea529baa9e6bde720beb3d825c718f27
+
+**Link:** https://arxiv.org/abs/12d84412ea529baa9e6bde720beb3d825c718f27

cache/e19c8cfeb70a65b29aa17aa2ec5732cf_script.txt

@@ -0,0 +1,21 @@
+Have you ever wondered what it would be like to receive postcards from across the galaxy? Well, astronomers have essentially been doing just that, thanks to some very unusual visitors that have wandered into our solar system over the past few years.
+
+Picture this: you're looking up at the night sky, and somewhere out there, ancient rocks are silently drifting through space, carrying secrets from stellar neighborhoods billions of years old. These aren't your typical asteroids or comets that orbit our sun. These are true travelers from other star systems, and they're giving us our first real glimpse into what's floating around in the vast spaces between the stars.
+
+The story begins with three cosmic wanderers that astronomers have spotted passing through our solar system. The first one has a Hawaiian name that's quite a mouthful: 'Oumuamua, which means "scout" or "messenger from afar." Then came Borisov, followed by ATLAS. What makes these objects so special is that they're not from here at all. They're what scientists call interstellar objects, meaning they originated somewhere else in our galaxy and just happened to swing by our cosmic neighborhood.
+
+Now, here's where it gets really interesting. Finding these visitors is one thing, but figuring out where they came from is like trying to trace a single leaf back to its tree after it's been carried by the wind for miles. These objects have been traveling through space for potentially billions of years, getting nudged and pulled by the gravity of countless stars along the way.
+
+So how do you solve a mystery like that? Well, researchers essentially became cosmic detectives. They used powerful computer simulations to rewind time, like playing a movie backward. They traced each object's path through our galaxy's gravitational field, running ten thousand different scenarios for each visitor to account for all the uncertainties in their measurements.
+
+Think of it like this: imagine trying to figure out where a paper airplane came from by watching how it drifts on air currents, except instead of air currents, you're dealing with the invisible gravitational pull of hundreds of billions of stars, and instead of a few seconds of flight time, you're looking at journeys that lasted eons.
+
+What they discovered is absolutely fascinating. These three visitors are like time capsules from completely different eras of our galaxy's history. 'Oumuamua, that first mysterious scout, appears to come from a relatively young stellar system, only about one billion years old. In cosmic terms, that's practically a toddler.
+
+Borisov, on the other hand, originated from a middle-aged neighborhood, roughly four billion years old, similar to our own solar system. But here's the real kicker: ATLAS is ancient. This object comes from what astronomers call the thick disk of our galaxy, a region that formed when the Milky Way was young and chaotic, about nine and a half billion years ago. To put that in perspective, ATLAS began its journey when our galaxy was less than half its current age.
+
+What's remarkable is that each object's origin tells a different story about how our galaxy has evolved. The younger systems tend to stay close to the flat disk of the Milky Way, where most of the action happens. But ATLAS, coming from that ancient thick disk, has been wandering through regions of space that formed during the galaxy's wild youth, when stars were crashing into each other and stellar neighborhoods were much more turbulent than they are today.
+
+This research is giving us something we've never had before: the ability to study pieces of other star systems without having to travel to them. These interstellar objects are like messengers carrying information across both space and time. They're telling us that there's a whole zoo of different objects drifting between the stars, each one a potential treasure trove of information about how planets form and how solar systems evolve in different parts of our galaxy.
+
+Looking ahead, astronomers expect to find many more of these cosmic travelers, especially with new telescopes coming online that can spot fainter and more distant objects. Each new discovery will add another piece to the puzzle, helping us understand not just where these objects come from, but what that tells us about the incredible diversity of worlds that exist throughout our galaxy. We're essentially building a family tree of the cosmos, one mysterious visitor at a time.

cache/e19c8cfeb70a65b29aa17aa2ec5732cf_summary.txt

@@ -0,0 +1,7 @@
+## Tracing the Origins of Mysterious Interstellar Visitors
+
+In recent years, astronomers have discovered three unusual objects passing through our solar system that didn't originate from here—1I/'Oumuamua, 2I/Borisov, and 3I/ATLAS. These "interstellar objects" came from somewhere else in our galaxy, but determining exactly where they started their journeys has been a challenging puzzle. Understanding their origins could provide valuable insights into how planetary systems form and evolve throughout the Milky Way, and help us learn more about the types of objects drifting between the stars.
+
+To solve this mystery, researchers used computer simulations to trace these objects' paths backward through time, following their trajectories through the gravitational field of our entire galaxy. They ran 10,000 different simulations for each object to account for uncertainties in measurements, tracking how far each object traveled above and below the flat disk of the Milky Way during its journey. The team then used statistical methods to connect these orbital patterns with the ages of different stellar populations in our galaxy, since stars of different ages tend to have different movement patterns.
+
+The results reveal that these three visitors came from very different cosmic neighborhoods. 'Oumuamua appears to have originated from a relatively young stellar system about 1 billion years old, staying close to the galactic disk during its travels. Borisov came from a middle-aged region around 3.8 billion years old, while ATLAS originated from the galaxy's ancient thick disk, roughly 9.6 billion years old—making it a relic from when our galaxy was much younger. This research demonstrates that interstellar objects can serve as messengers from across both space and time, carrying information about stellar systems of vastly different ages throughout our galaxy.

cache/e7e127b268640b5d346031fa6b2b8ed2_paper.txt

@@ -0,0 +1,9 @@
+**Title:** Emerging Trends in mRNA Vaccine Technology: Beyond Infectious Diseases
+
+**Authors:** Ali Hassan Ibrahim Khormi, Raied Mohammad Mosa Qohal, Abdulrahman Yahya Ahmed Masrai, Khaloufa Hassan Hofdallh Hakami, Jaber Ahmed Ogdy et al. (15 authors)
+
+**Published:** 2024
+
+**arXiv ID:** 23ede2f84053a721218757e911a9a7864a2c5721
+
+**Link:** https://arxiv.org/abs/23ede2f84053a721218757e911a9a7864a2c5721

cache/e7e127b268640b5d346031fa6b2b8ed2_script.txt

@@ -0,0 +1,25 @@
+Remember getting your COVID vaccine? That tiny shot that seemed almost too simple to work against a global pandemic? Well, what if I told you that same technology is about to completely transform how we treat cancer, rare genetic diseases, and conditions that have stumped doctors for decades?
+
+I'm talking about mRNA vaccines, and they're having what you might call a major career pivot. While we know them as the heroes of the pandemic, scientists are discovering they're actually incredible multitaskers with skills we never knew they had.
+
+Let me paint you a picture of what's happening in research labs right now. Imagine you have cancer, and instead of getting a one-size-fits-all treatment, doctors create a vaccine specifically designed for your unique tumor. They analyze your cancer cells, identify what makes them different from your healthy cells, and then use mRNA technology to teach your immune system to hunt down those exact cancer characteristics. It's like giving your immune system a personalized wanted poster.
+
+This isn't science fiction anymore. Between 2020 and 2024, researchers have been quietly working on exactly this kind of personalized medicine, and the results are genuinely exciting. Early studies are showing that these custom-made cancer vaccines can help patients' immune systems recognize and attack their specific tumors.
+
+But here's where it gets even more interesting. Scientists are also flipping the script on what we think vaccines do. Traditionally, vaccines prevent diseases by training our immune systems to fight off invaders. But these new mRNA treatments can actually calm down immune systems that have gone haywire, like in autoimmune diseases where your body mistakenly attacks itself.
+
+And then there's something that sounds almost magical. For people born with rare genetic conditions where their bodies can't make certain essential proteins, mRNA technology could essentially deliver the instructions for making those missing proteins directly to their cells. It's like having a molecular delivery service that brings your cells exactly what they've been missing.
+
+Now, you might be wondering how scientists made all these breakthroughs happen. The key has been solving some pretty tricky puzzles. Remember how the COVID vaccines had to be kept super cold? Researchers have been working on making mRNA more stable and easier to deliver to exactly the right places in the body. They've developed better packaging systems that protect the mRNA and help it get where it needs to go without breaking down along the way.
+
+Think of it like this: if mRNA is a fragile message written on delicate paper, scientists have figured out how to put it in a high-tech protective envelope that not only keeps it safe but also has GPS to deliver it to the right address in your body.
+
+But let's be real about the challenges ahead. Making these personalized treatments is incredibly complex and expensive right now. Creating a custom vaccine for each cancer patient isn't like mass-producing millions of identical COVID shots. Each one requires individual analysis and manufacturing, which costs serious money.
+
+There are also safety questions that need answers. When you're teaching someone's immune system new tricks, you have to be absolutely sure you're not creating unexpected problems. And regulatory agencies are still figuring out the best ways to test and approve these highly personalized treatments.
+
+Here's what has me genuinely excited though. The researchers behind this work believe we're standing at the edge of a new era in medicine. Instead of treating diseases with broad approaches that work okay for most people, we're moving toward treatments tailored specifically to each person's unique biology.
+
+The collaboration happening right now between scientists, pharmaceutical companies, and regulatory agencies reminds me of what we saw during the pandemic, but this time it's not about responding to a crisis. It's about reimagining what's possible in medicine.
+
+So the next time you think about that COVID shot you got, remember that it might have been your first glimpse into the future of personalized medicine. Those mRNA vaccines that helped end a pandemic? They're just getting started. And for millions of people waiting for treatments that don't exist yet, that future can't come soon enough.

cache/e7e127b268640b5d346031fa6b2b8ed2_summary.txt

@@ -0,0 +1,7 @@
+**mRNA Vaccines: Expanding Beyond COVID-19 to Fight Cancer and Genetic Diseases**
+
+While mRNA vaccines became household names during the COVID-19 pandemic, researchers are now discovering their potential extends far beyond preventing infectious diseases. This research explores how the same technology that helped control the pandemic could revolutionize treatment for cancer, autoimmune disorders, and rare genetic conditions—areas where patients desperately need new therapeutic options.
+
+The researchers conducted a comprehensive review of recent studies from 2020 to 2024, analyzing advances in mRNA vaccine design, delivery methods, and manufacturing processes. They examined data from laboratory studies and clinical trials to understand how scientists are adapting this technology for new medical applications, including personalized cancer vaccines that target individual tumors and treatments that could replace missing proteins in genetic disorders.
+
+The findings reveal significant progress in making mRNA vaccines more effective and stable through improved delivery systems and chemical modifications. Early studies show promising results for personalized cancer treatments, therapies that could calm overactive immune systems in autoimmune diseases, and protein replacement treatments for rare genetic conditions. However, challenges remain in making these treatments affordable to manufacture, controlling unwanted immune reactions, and establishing clear regulatory guidelines. The research concludes that while mRNA technology holds tremendous promise for personalized medicine, realizing its full potential will require continued collaboration between researchers, pharmaceutical companies, and regulatory agencies to bring these innovative treatments to patients who need them.

cache/metadata.json

@@ -0,0 +1,58 @@
+{
+  "40470ecbc8f20a349588205640b21796": {
+    "topic": "AlphaFold 3",
+    "summary_file": "40470ecbc8f20a349588205640b21796_summary.txt",
+    "script_file": "40470ecbc8f20a349588205640b21796_script.txt",
+    "audio_file": "assets/audio/podcast_1763930591.mp3",
+    "paper_file": "40470ecbc8f20a349588205640b21796_paper.txt"
+  },
+  "c72a1737a2b36cc9b63522cfb8d752ca": {
+    "topic": "transformer neural network",
+    "summary_file": "c72a1737a2b36cc9b63522cfb8d752ca_summary.txt",
+    "script_file": "c72a1737a2b36cc9b63522cfb8d752ca_script.txt",
+    "audio_file": "assets/audio/podcast_1763930653.mp3",
+    "paper_file": "c72a1737a2b36cc9b63522cfb8d752ca_paper.txt"
+  },
+  "e7e127b268640b5d346031fa6b2b8ed2": {
+    "topic": "mRNA vaccine technology",
+    "summary_file": "e7e127b268640b5d346031fa6b2b8ed2_summary.txt",
+    "script_file": "e7e127b268640b5d346031fa6b2b8ed2_script.txt",
+    "audio_file": "assets/audio/podcast_1763930711.mp3",
+    "paper_file": "e7e127b268640b5d346031fa6b2b8ed2_paper.txt"
+  },
+  "598a2e89c318f4b49efc9e839484ad1a": {
+    "topic": "tuberculosis vaccine",
+    "summary_file": "598a2e89c318f4b49efc9e839484ad1a_summary.txt",
+    "script_file": "598a2e89c318f4b49efc9e839484ad1a_script.txt",
+    "audio_file": "assets/audio/podcast_1763930772.mp3",
+    "paper_file": "598a2e89c318f4b49efc9e839484ad1a_paper.txt"
+  },
+  "b379b40c8b7ff24bf60f91bcc9d86f24": {
+    "topic": "CRISPR/Cas9 gene editing applications",
+    "summary_file": "b379b40c8b7ff24bf60f91bcc9d86f24_summary.txt",
+    "script_file": "b379b40c8b7ff24bf60f91bcc9d86f24_script.txt",
+    "audio_file": "assets/audio/podcast_1763930824.mp3",
+    "paper_file": "b379b40c8b7ff24bf60f91bcc9d86f24_paper.txt"
+  },
+  "e19c8cfeb70a65b29aa17aa2ec5732cf": {
+    "topic": "3I/ATLAS",
+    "summary_file": "e19c8cfeb70a65b29aa17aa2ec5732cf_summary.txt",
+    "script_file": "e19c8cfeb70a65b29aa17aa2ec5732cf_script.txt",
+    "audio_file": "assets/audio/podcast_1763930878.mp3",
+    "paper_file": "e19c8cfeb70a65b29aa17aa2ec5732cf_paper.txt"
+  },
+  "68e2edd3a79c753c24f00d9a28e90dae": {
+    "topic": "quantum entanglement",
+    "summary_file": "68e2edd3a79c753c24f00d9a28e90dae_summary.txt",
+    "script_file": "68e2edd3a79c753c24f00d9a28e90dae_script.txt",
+    "audio_file": "assets/audio/podcast_1763930931.mp3",
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+  },
+  "24421acf21f6d6909fa1c096b631b4c3": {
+    "topic": "Ocean acidification",
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+    "script_file": "24421acf21f6d6909fa1c096b631b4c3_script.txt",
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+    "paper_file": "24421acf21f6d6909fa1c096b631b4c3_paper.txt"
+  }
+}

convert_cache_to_mp3.py

@@ -0,0 +1,115 @@
+"""
+Convert cached WAV files to MP3 for smaller size (GitHub 10MB limit)
+Requires: pydub and ffmpeg
+"""
+
+import os
+import json
+from pathlib import Path
+
+try:
+    from pydub import AudioSegment
+except ImportError:
+    print("Installing pydub...")
+    os.system("pip install pydub")
+    from pydub import AudioSegment
+
+def convert_wav_to_mp3(wav_path: str, mp3_path: str, bitrate: str = "128k"):
+    """Convert WAV to MP3."""
+    print(f"Converting {wav_path} -> {mp3_path}")
+    audio = AudioSegment.from_wav(wav_path)
+    audio.export(mp3_path, format="mp3", bitrate=bitrate)
+    
+    wav_size = os.path.getsize(wav_path) / (1024 * 1024)
+    mp3_size = os.path.getsize(mp3_path) / (1024 * 1024)
+    print(f"  WAV: {wav_size:.2f}MB -> MP3: {mp3_size:.2f}MB (saved {wav_size - mp3_size:.2f}MB)")
+
+def update_cache_metadata(cache_dir: Path):
+    """Update metadata.json to point to MP3 files."""
+    metadata_file = cache_dir / "metadata.json"
+    
+    if not metadata_file.exists():
+        print("No metadata.json found")
+        return
+    
+    with open(metadata_file, 'r') as f:
+        metadata = json.load(f)
+    
+    for key, entry in metadata.items():
+        audio_file = entry.get('audio_file', '')
+        if audio_file.endswith('.wav'):
+            # Update to MP3
+            mp3_file = audio_file.replace('.wav', '.mp3')
+            entry['audio_file'] = mp3_file
+            print(f"Updated metadata: {audio_file} -> {mp3_file}")
+    
+    with open(metadata_file, 'w') as f:
+        json.dump(metadata, f, indent=2)
+    
+    print(f"\n✅ Updated {metadata_file}")
+
+def main():
+    cache_dir = Path("./cache")
+    audio_dir = Path("./assets/audio")
+    
+    print("🎵 Converting cached WAV files to MP3\n")
+    print("This reduces file size by ~90% to fit GitHub's 10MB limit\n")
+    
+    # Load metadata to find all cached audio files
+    metadata_file = cache_dir / "metadata.json"
+    if not metadata_file.exists():
+        print("❌ No cache metadata found. Run generate_cache.py first.")
+        return
+    
+    with open(metadata_file, 'r') as f:
+        metadata = json.load(f)
+    
+    converted = 0
+    for key, entry in metadata.items():
+        audio_file = entry.get('audio_file', '')
+        
+        if not audio_file or not audio_file.endswith('.wav'):
+            continue
+        
+        wav_path = Path(audio_file)
+        if not wav_path.exists():
+            print(f"⚠️  Not found: {wav_path}")
+            continue
+        
+        # Convert to MP3
+        mp3_path = wav_path.with_suffix('.mp3')
+        
+        if mp3_path.exists():
+            print(f"✓ Already exists: {mp3_path}")
+        else:
+            try:
+                convert_wav_to_mp3(str(wav_path), str(mp3_path), bitrate="128k")
+                converted += 1
+            except Exception as e:
+                print(f"❌ Error converting {wav_path}: {e}")
+    
+    print(f"\n📊 Converted {converted} files")
+    
+    # Update metadata
+    print("\n🔄 Updating cache metadata...")
+    update_cache_metadata(cache_dir)
+    
+    # Clean up WAV files
+    print("\n🗑️  Removing original WAV files...")
+    for key, entry in metadata.items():
+        audio_file = entry.get('audio_file', '')
+        if audio_file:
+            wav_path = Path(audio_file.replace('.mp3', '.wav'))
+            if wav_path.exists() and wav_path.suffix == '.wav':
+                size_mb = os.path.getsize(wav_path) / (1024 * 1024)
+                os.remove(wav_path)
+                print(f"  Removed {wav_path.name} ({size_mb:.2f}MB)")
+    
+    print("\n✅ Conversion complete!")
+    print("\nNow you can commit:")
+    print("  git add cache/ assets/audio/podcast_*.mp3")
+    print("  git commit -m 'Add pre-generated MP3 podcast cache'")
+    print("  git push")
+
+if __name__ == "__main__":
+    main()

tests/test_semantic_scholar.ipynb

@@ -144,8 +144,8 @@
      "data": {
       "text/plain": [
        "[\"Galactic Trajectories of Interstellar Objects 1I/'Oumuamua, 2I/Borisov, and 3I/Atlas\",\n",
-       " 'Assessing interstellar comet 3I/ATLAS with the 10.4 m Gran Telescopio Canarias and the Two-meter Twin Telescope',\n",
-       " 'Hubble Space Telescope Observations of the Interstellar Interloper 3I/ATLAS']"
+       " 'Hubble Space Telescope Observations of the Interstellar Interloper 3I/ATLAS',\n",
+       " 'Assessing interstellar comet 3I/ATLAS with the 10.4 m Gran Telescopio Canarias and the Two-meter Twin Telescope']"
       ]
      },
      "execution_count": 5,
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 8,
    "id": "d5744f05",
    "metadata": {},
    "outputs": [
@@ -202,7 +202,7 @@
        "'{\\n  \"title\": \"Galactic Trajectories of Interstellar Objects 1I/\\'Oumuamua, 2I/Borisov, and 3I/Atlas\",\\n  \"abstract\": \"The first interstellar objects, 1I/`Oumuamua, 2I/Borisov and 3I/ATLAS, were discovered over the past decade. We follow the trajectories of known interstellar objects in the gravitational potential of the Milky Way galaxy to constrain their possible origin. We perform Monte Carlo orbital integrations using 10,000 trajectory ensembles per object to properly account for measurement uncertainties in both object velocities and Solar motion parameters. We implement a Bayesian statistical framework that combines a Rayleigh-like likelihood function with star formation rate priors to infer stellar ages from the maximum vertical excursions ($z_{\\\\\\\\text{max}}$) of orbital trajectories. The likelihood function incorporates age-dependent velocity dispersions reflecting the thin-thick disk transition and dynamical heating over galactic history. Our Monte Carlo analysis yields median $z_{\\\\\\\\text{max}}$ values of 0.016 $\\\\\\\\pm$ 0.002 kpc for 1I/`Oumuamua, 0.121 $\\\\\\\\pm$ 0.010 kpc for 2I/Borisov, and 0.480 $\\\\\\\\pm$ 0.020 kpc for 3I/ATLAS. The Bayesian age inference indicates that 1I/`Oumuamua originated from a young stellar system (1.0 Gyr, 68\\\\\\\\% CI: 0.1-4.1 Gyr), 2I/Borisov from an intermediate-age population (3.8 Gyr, 68\\\\\\\\% CI: 1.8-5.9 Gyr), and 3I/ATLAS from an old thick-disk source (9.6 Gyr, 68\\\\\\\\% CI: 7.8-10.3 Gyr). These results demonstrate clear age discrimination where smaller vertical excursions correspond to younger stellar origins.\",\\n  \"year\": 2024\\n}'"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }

utils/cache_manager.py

@@ -62,7 +62,7 @@ class CacheManager:
         normalized = topic.lower().strip()
         return hashlib.md5(normalized.encode('utf-8')).hexdigest()
     
-    def get(self, topic: str) -> Optional[Tuple[str, str, str, str]]:
+    def get(self, topic: str) -> Optional[Tuple[str, str, Optional[str], str]]:
         """
         Get cached podcast for a topic.
         
@@ -71,6 +71,7 @@ class CacheManager:
             
         Returns:
             Tuple of (summary, script, audio_path, paper_info) or None if not cached
+            audio_path may be None if audio file doesn't exist yet
         """
         cache_key = self._get_cache_key(topic)
         
@@ -80,17 +81,22 @@ class CacheManager:
         
         entry = self.metadata[cache_key]
         
-        # Verify files exist
+        # Verify required text files exist
         summary_file = self.cache_dir / entry['summary_file']
         script_file = self.cache_dir / entry['script_file']
-        audio_file = Path(entry['audio_file'])
         paper_file = self.cache_dir / entry['paper_file']
         
-        if not all([summary_file.exists(), script_file.exists(), 
-                   audio_file.exists(), paper_file.exists()]):
+        if not all([summary_file.exists(), script_file.exists(), paper_file.exists()]):
             logger.warning(f"Cache entry incomplete for: {topic}")
             return None
         
+        # Audio file is optional - may not exist yet
+        audio_path = None
+        if 'audio_file' in entry:
+            audio_file = Path(entry['audio_file'])
+            if audio_file.exists():
+                audio_path = str(audio_file)
+        
         try:
             # Load cached content
             with open(summary_file, 'r', encoding='utf-8') as f:
@@ -102,8 +108,8 @@ class CacheManager:
             with open(paper_file, 'r', encoding='utf-8') as f:
                 paper_info = f.read()
             
-            logger.info(f"✅ Cache hit for topic: {topic}")
-            return summary, script, str(audio_file), paper_info
+            logger.info(f"✅ Cache hit for topic: {topic} (audio: {audio_path is not None})")
+            return summary, script, audio_path, paper_info
             
         except Exception as e:
             logger.error(f"Error reading cached content: {e}")