Just got this email from the Indian Hotels Company
Good campaign #DekhoApnaDesh
Especially when most of the holidays are happening domestically. No wonder the Stock is Strong.

This is just information sharing. I may be holding this stock. Please do your own research.

कुंडली में 12 भाव होते हैं। कैसे ज्योतिष द्वारा रोग के आंकलन करते समय कुंडली के विभिन्न भावों से गणना करते हैं आज इस पर चर्चा करेंगे।
कुण्डली को कालपुरुष की संज्ञा देकर इसमें शरीर के अंगों को स्थापित कर उनसे रोग, रोगेश, रोग को बढ़ाने घटाने वाले ग्रह

रोग की स्थिति में उत्प्रेरक का कार्य करने वाले ग्रह, आयुर्वेदिक/ऐलोपैथी/होमियोपैथी में से कौन कारगर होगा इसका आँकलन, रक्त विकार, रक्त और आपरेशन की स्थिति, कौन सा आंतरिक या बाहरी अंग प्रभावित होगा इत्यादि गणना करने में कुंडली का प्रयोग किया जाता है।

मेडिकल ज्योतिष में आज के समय में Dr. K. S. Charak का नाम निर्विवाद रूप से प्रथम स्थान रखता है। उनकी लिखी कई पुस्तकें आज इस क्षेत्र में नए ज्योतिषों का मार्गदर्शन कर रही हैं।
प्रथम भाव -
इस भाव से हम व्यक्ति की रोगप्रतिरोधक क्षमता, सिर, मष्तिस्क का विचार करते हैं।

द्वितीय भाव-
दाहिना नेत्र, मुख, वाणी, नाक, गर्दन व गले के ऊपरी भाग का विचार होता है।
तृतीय भाव-
अस्थि, गला,कान, हाथ, कंधे व छाती के आंतरिक अंगों का शुरुआती भाग इत्यादि।

चतुर्थ भाव- छाती व इसके आंतरिक अंग, जातक की मानसिक स्थिति/प्रकृति, स्तन आदि की गणना की जाती है

पंचम भाव-
जातक की बुद्धि व उसकी तीव्रता,पीठ, पसलियां,पेट, हृदय की स्थिति आंकलन में प्रयोग होता है।

षष्ठ भाव-
रोग भाव कहा जाता है। कुंडली मे इसके तत्कालिक भाव स्वामी, कालपुरुष कुंडली के स्वामी, दृष्टि संबंध, रोगेश की स्थिति, रोगेश के नक्षत्र औऱ रोगेश व भाव की डिग्री इत्यादि।

IT WAS RISHI KANADA WHO GAVE THE ATOMIC THEORY & TALKED ABOUT THE GRAVITY OF EARTH, 2600 YEARS BEFORE AN APPLE FELL IN FRONT OF NEWTON'S EYES:

Scientists of the modern world credit an English scientist John Dalton (1766 CE -1844 CE) for the Atomic Theory.

And this is because, most of us are not even aware of an ancient Indian Sage named Kanada, who was the first to formulate the theory of atoms, almost 2600 yrs before Dalton and talk about earth's gravity.

Rishi Kanada was born around 600 BCE in Dwarka, Gujarat and he was the son of a philosopher named Ulka. He was fascinated with the minute detailing of the things right from his childhood. Once, when he was very young, he accompanied his father on a journey to Prayaga.

He saw plentiful grains scattered along the path leading to the shore of river Ganga. It's a tradition in Hindu families to scatter the grains for the ants and birds to feed on them. Suddenly, an ant caught his attention, who was feeding on a rice grain.

He was mesmerised by this very fact that how a small grain of rice becomes food for the ant but to satisfy the hunger of a person so many grains are needed together. This incidence made him realize the importance of a single grain of rice.

🚔 HUGE #Tesla SERVICE PROBLEMS THREAD🚔

You might remember my 3 prior threads on how
TESLA. TREATS. ITS. CUSTOMERS. LIKE. TRASH.

Here's the 4th installment.
@tomkeinan @jonsey_lisa @jwmooc @tchanpoker @bryanthediamond @EconomicManBlog
$TSLA $TSLAQ 1/22

Welcome to Greta's 4th edition of #Tesla customers getting used and abused. Because that's the Elon Musk way.
@coffeebreakls @KocgibiHarun @omaragha @JayGhahari
$TSLA $TSLAQ 2/22

"The best service is no service." - Elon Musk a.k.a. #SpaceKaren
@briansaziz @FarSha998899 @thinktankfour @Billoday1
#Tesla $TSLA $TSLAQ 3/22

These #Tesla customers represent just the very tip of the iceberg. They are ones who have Twitter, have decided to complain about their #TeslaServiceIssues publicly, and were found by yours truly.
@yanismydj @hajelatweets @AlanHeldman @francislongo5 $TSLA $TSLAQ 4/22

Dear #Tesla customers: In California, if your vehicle has been out of service for >30 days total, it's a lemon. You can get punitive damages and attorney's fees. Don't sit around and take Elon's abuse. @13arm13arm @cecimar12 @richardson_skip @shootinglee $TSLA $TSLAQ 5/22

1 There's a chasm between an NLP technology that works well in the research lab and something that works for applications that real people use. This was eye-opening when I started my career, and every time I talk to an NLP engineer at @textio, it continues to strike me even now.

2 Research conditions are theoretical and/or idealized. A huge problem for so-called NLP or AI startups with highly credentialed academic founders is that they bring limited knowledge of what it takes to build real products outside the lab.

3 A product is ultimately a thing that people pay for - not just cool technology or user experience. But I’m not even talking about knowledge gaps in go-to-market work. I'm talking purely technical gaps: how you go from science project to performant + delightful user experience.

4 Most commoditized NLP packages solve well-understood problems in standard ways that sacrifice either precision or performance. In a research lab, this is not usually a hard trade-off; in general, no one is using what you make, so performance is less important than precision.

5 In software, when you’re making something for real people to use, these tradeoffs are a big deal. Especially if you’re asking those people to pay for what you’ve made (can’t get away from that pesky GTM thinking). They expect quality, which includes precision AND performance.