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Double Top Buy triggered above 1886.26 daily close on 1% Box size chart. https://t.co/RxpbnbBeSp

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।

(MAJOR NOTE) The reason Manafort took over Trump's campaign in just 3 weeks despite being hired as a mere delegate counter is that ROGER STONE initiated a whisper campaign against Corey Lewandowski. That campaign started...days after Manafort returned from meeting with WikiLeaks.

2/ Stone and Manafort are longtime business partners; we'd expect Manafort to tell Stone what Assange told him, and for him to expect Stone to then pressure the campaign not only to hire him but quickly elevate him.

And who was Stone in touch with at the campaign? Trump himself.

3/ I bet you Manafort's late March emails are very interesting and that some of them are to/from his longtime business associate Roger Stone. And I bet Roger Stone's late March phone calls are very interesting and that some of them are to/from his longtime friend Donald Trump.

4/ At the end of March 2016, Trump suddenly convenes a NatSec meeting. At that meeting he directs his NatSec team to change the RNC platform in July to benefit Putin. Who later takes credit for that change?

Paul Manafort's business associate, Kremlin agent Konstantin Kilimnick.

5/ Why did Donald Trump suddenly convene a NatSec meeting 3 days after he finally hired Manafort? Why did he issue a pro-Kremlin directive at that meeting that Manafort's camp would later take credit for? What did Manafort tell Trump in the days leading up to that NatSec meeting?

STORY OF PURANAS AND SUB PURANA (उप पुराण).

We have already gone through the series on importance & characteristics of all the eighteen Purans. We also know that originally there were hundred crore shlokas but were divided by Vyas in each Kalp and was compiled as eighteen Purans

for the common people to understand it properly and now their total is about four lakhs.

In Brahm Puran, Brahma preached this to Marichi. So this Puran of ten thousand shlokas is called Brahm Puran.

In Padma Puran, the base of the story is the appearance of Brahma on a lotus(Padm) from Vishnu' s navel.This has fifty five thousand shlokas.

Vishnu Puran is primarily based in Varah kalp. This book is on Vishnu and this book has twenty three thousand shlokas.

Vaayu Puran is written in Shwet Kalp and has twenty four thousand shlokas. Here Vayudev preaches about Dharma.

In Bhagwat Puran, which is written with the base of Gayatri mantra describes Dharma extensively. It has 18000 shlokas. It also mentions the story of Vritrasur.

In Narad Puran, which has twenty five thousand shlokas, is a sermon on Dharma by Narad based in Brihad Kalp.

Markandeya Puran has nine thousand shlokas and here it is through the birds that Dharma is described.

DEVI KARUMARIAMMAN, THIRUVERKADU (TN)

Devi is worshipped here as both Swayambhu (self-manifested) and as Parashakti (with 4 arms holding skull,sword,trishul,udukkai/damru).

Here, Muruga got Vel from Devi to fight Suran. So the place was called Vel kadu which became Verkadu.

It is said that there was an anthill here long ago. Devi appeared in the dream of a devotee and asked him to build a shrine at that spot. When the anthill was removed, the swayambhu murti of Devi emerged. So Devi is called Karuvil Illadha Karumari ( not in the womb of mother).

Once, Devi went to Surya in the form of an old woman but Surya neglected her. Devi’s anger made Surya lose his brightness.
To appease her, Surya said that His rays would fall on Her directly twice in a year and touch her feet. Also, Sunday is celebrated as day of Devi Karumari.

There is also a wooden image of Devi (Marachilai Amman) here. Devotees offer locks to her in the belief that She would safe guard their houses.
Temple tank (Thiruchamber Poigai) is said to have been created by Subramanya. Taking dip in it is said to cure skin related disorders.

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.