Calcitas - D3 Soft Gelatin Capsule Manufacturer: Intas Pharmaceuticals LtdInformation about Calcitas - D3 Soft Gelatin Capsule
Calcitas D3 Capsule contains Cholecalciferol 60,000 iu (International units). Cholecalciferol (Vitamin D3) is a fat soluble vitamin, that helps the body to absorb calcium and phosphorous found in food and supplements. Vitamin D is made by the body when skin is exposed to sunlight. Sunscreen, protective clothing, limited exposure to sunlight, dark skin, and age may prevent getting enough vitamin D from the sun, thus leading to Vitamin D3 Deficiency. Thus, Vitamin D3 in Calcitas D3 Capsule is essential for calcium absorption in the body. --- Cholecalciferol is a dietary supplement that is used to treat vitamin D deficiency. It is also used with calcium to maintain bone strength. This medicine is available both over-the-counter (OTC) and with your doctor's prescription. --- Cholecalciferol, also known as vitamin D₃ and colecalciferol, is a type of vitamin D that is made by the skin when exposed to sunlight; it is found in some foods and can be taken as a dietary supplement. Cholecalciferol is made in the skin following UVB light exposure. --- Other uses of Calcitas D3 Capsule are: Building and keeping the bones & teeth strong Reducing Fatigue/stress and muscular pains Boosting immunity and increasing resistance against infection Supplement for patients with diabetic complications and Cardio Vascular Diseases as well. Use under medical supervision.
Saturday, August 6, 2022
Calcitas - D3 Soft Gelatin Capsule
Tuesday, August 2, 2022
Chatbot Examples in Use in Different Business Domains
The Apollo 11 Mission
Apollo 11 (July 16 - 24, 1969) was the American spaceflight that first landed humans on the Moon. Commander Neil Armstrong and lunar module pilot Buzz Aldrin landed the Apollo Lunar Module Eagle on July 20, 1969, at 20:17 UTC, and Armstrong became the first person to step onto the Moon's surface six hours and 39 minutes later, on July 21 at 02:56 UTC. Aldrin joined him 19 minutes later, and they spent about two and a quarter hours together exploring the site they had named Tranquility Base upon landing. Armstrong and Aldrin collected 47.5 pounds (21.5 kg) of lunar material to bring back to Earth as pilot Michael Collins flew the Command Module Columbia in lunar orbit, and were on the Moon's surface for 21 hours, 36 minutes before lifting off to rejoin Columbia. Apollo 11 had a lunar system designed for geologists to answer their questions asked in natural language. The geologists would ask questions like "what is the average basalt content" and the system would respond back.Chatbots in Healthcare
Chatbots like Molly, Eva, Ginger, Replika, Florence, and Izzy are widely used in healthcare.Chatbots for mental health support
Bots like Wysa and Woebot are designed in such a way that they can provide support like a life coach. They are so good at asking right probing questions that can help the user to share their emotions and feelings after a hard day.Chatbots for legal advice
Lawyers can use bots like DonotPay, LISA, Ross, and BillyBot to accelerate their work and provide better client experiences.Other Chatbot applications
In Smart keyboards like Swiftkey, the software automatically completes your sentences by predicting the next word and corrects your spelling mistakes. Applications like Grammarly can automatically correct your spelling and grammar and assists you in writing better essays or emails. Dated: 2022-Aug-02
Thursday, July 28, 2022
Natural Language Processing Questions and Answers (Set 4 of 7 Questions)
Course: INTRODUCTION TO NATURAL LANGUAGE PROCESSING Q1: Multiple Choice Correct Which of the following are potential use cases of NLP? a) A self driving car drawing your attentioin to an advertising billboard b) Given the audio of a song, and its lyrics generate a translated song audio c) Understanding a cryptic language d) Determing what are the chances that you will win a law suit based on outcomes of previous similar law suits. Answer: All four are correct. Q2: Multiple Choice Correct Which of the below tasks can be performed effectively even without using sophisticated NLP techniques: a) Identifying the main topic of a document assuming that its title is not provided. b) Detecting the language in a document c) Extracting the phone numer, email address and year of graduatioin from a resume. d) Substituting words like doesn't, can't, etc with does not, and can not, etc. Answer: C and D Q3: Spam email is a persistent problem that service providers have been trying to solve for years now. One of the key tasks in building an effective spam detection system is identifying the features of an email that could be used to classify the email as spam or not. Rank the following features based on the text content of an email based on your Understanding of the feature's importance. a) Language (English, French, etc) used in the email text. b) Presence of words with spelling mistakes / non standard form. c) Emails addressed to you and contain your name. Answer: Correct order is: C > A > B Q4) Identify the kind of ambiguity in the given sentences: a) Time flies like an arrow, fruit flies like a banana. b) Iraqi head seeks arms. c) A frog thought it saw a prince walk towards it. It thought it can't be true. List of ambiuities for matching with above sentences. I) Anaphoric Ambiguity II) Semantic Ambiguity III) Syntactic Ambiguity. Answer: A -> III B -> II C -> I Syntactic ambiguity Take a look at the sentence given below “Old men and women were taken to safe locations” This sentence has a syntactic ambiguity where the scope of the adjective “old” needs to be resolved. In this sentence, we may not know if the adjective applies only to men or to both men and women. Semantic ambiguity Semantic ambiguity refers to ambiguity in the meaning. For example, the sentence “Alice loves her mother and so does Jacob.” The ambiguity here is, we may not know if Jacob loves his own mother or Alice’s mother. Anaphoric Ambiguity In the below paragraph “The horse ran up the hill. It was very steep. It soon got tired.” In this paragraph, the pronoun ‘it’ is used to refer to the hill first and then to the horse. To interpret this sentence, we need to have knowledge of the world and context. These ambiguities are called anaphoric ambiguities. Q5) Consider the below review for co-sleeper sheets for a baby. What is the sentiment in this review? "The shipping was quick the colors are pretty but the sheets themselves are not soft." a) positive b) negative c) Neutral Amswer: Positive The user is appreciating the shipping and the colors. Q6) Do sentiment analysis of following sentence: "The parking was great, the restaurant anbience was good. But the food was utterly terrible." a) positive b) negative c) Neutral Answer: Although the number of positive words is greater than the number of negative words in these sentences, the overall sentiment was negative. Weighted Scores to Find The Polarity The short coming of this dictionary based, and weighted scores for doing Sentiment Analysis is that it misses out on the order of words and hence may classify the sentiment as wrong. Q7) Assume that you have to build an NLP application that looks at a new document and estimates how similar it is to various text documents previously ingested. Consider that similarity of 2 documents is computed on the basis of presence of common words. Based on your understanding of the NLP technique discussed so far, what are various basic pre-processing steps that you will include in this application while processing the historic data and making inferences on a new document? Steps: a. Remove any unwanted spaces, numbers, special characters, etc b. Convert all text into lower case. c. Create n-grams based on the text. d. Tokenize the text. e. Normalize data using stemming and lemmatization techniques. f. Determine the frequence of each word in each document and also in the whole corpus. g. Remove stop words from the text. h. Remove punctuation i. Perform POS tagging on the text. Options: I. All the steps listed above need to be done. II. a, b, d, f, g, h III. b, c, d, e, h, g IV. a, d, e, f, g Answer: II
20220728 - Monitoring Effects of 1 tablet of Trini Calm and 1 tablet of Petril Beta 10
Index of Journals
20220728 1910: 1 Tablet of Trinicalm Plus SALT COMPOSITION: Trifluoperazine (5mg) + Trihexyphenidyl (2mg) 1 Tablet of Petril Beta 10 Tablet SALT COMPOSITION: Clonazepam (0.25mg) + Propranolol (10mg) Note: 1. Trihexyphenidyl is also referred to as "THP" medical prescriptions for psychiatric cases. 2. Clonazepam is also known as Clazzy in the underworld of drugs. 1914: Shiva Patel has just come for Math tuition. 1918: My psychiatrist told me that: Propranolol is used to slow down racing heart beat an effect of facing a threatening situation. 2015: Finished teaching students. 2016: Having dinner. 2024: Going for shower. 2037: Am feeling sleepy and tired. Going for rest for an hour. 2040: Spoke to Anjali Devi's parents about NIOS (National Institute of Open Schooling) and readmitting her to study again. 2021: Going for rest. 8:52 pm: I cannot stop thinking how Rekha bua, Manju bua, and Kumkum bua are becoming a blocker in rental business. 8:54 pm: They do not understand that I purchased the flat after having a verbal fight with mom. Mom and I cannot live together. 9:32 pm: Self awareness was there but that panicky, irritated mood was not there. 2202: When I am in Mayur Vihar, I face harassment by uncle and aunt. And, when I am Tri Nagar, I face harassment by three buas.
Student Update (2022-Jul-28)
Index of Journals
Counting
Srishti Patel Class: Nursery Till: 8 Anjali Devi Class: 5 Till: 9Tables
Sonam Patel Class: 7 Till: 12 Shiva Patel Class: 6C Till: 18Addition
Sonam Patel Class: 7 Till Level: 4 Shiva Patel Class: 6C Till Level: 9Subtraction
Sonam Patel Class: 7 Till Level: 8
Types of Ambiguities in Natural Language
Lexical ambiguity
Take a look at the following sentences: John bagged two silver medals. Mary made a silver speech. Roger’s worries had silvered his hair. The word silver is used as a noun, an adjective, and a verb. The word silver in isolation is mostly associated with the metal and considered as a noun. However, in other sentences, the context gives the word silver different meanings and also different parts of speech like adjectives and verbs. This ambiguity is called lexical ambiguity.Syntactic ambiguity
Take a look at the sentence given below “Old men and women were taken to safe locations” This sentence has a syntactic ambiguity where the scope of the adjective “old” needs to be resolved. In this sentence, we may not know if the adjective applies only to men or to both men and women.Semantic ambiguity
Semantic ambiguity refers to ambiguity in the meaning. For example, the sentence “Alice loves her mother and so does Jacob.” The ambiguity here is, we may not know if Jacob loves his own mother or Alice’s mother.Anaphoric ambiguity
In the below paragraph “The horse ran up the hill. It was very steep. It soon got tired.” In this paragraph, the pronoun ‘it’ is used to refer to the hill first and then to the horse. To interpret this sentence, we need to have knowledge of the world and context. These ambiguities are called anaphoric ambiguities.Pragmatic Ambiguity
The hardest kind of ambiguity to resolve is the pragmatic ambiguity. This kind of ambiguity arises from the inability to process the intention or sentiment or world belief. For example, in the below conversation, My wife said: "Please go to the store and buy a carton of milk and if they have eggs, get six." I came back with 6 cartons of milk She said, "why did you buy six cartons of milk?" I replied, "They had eggs" As you can see here, the ambiguity is in understanding the intention of the speaker.
Wednesday, July 27, 2022
Risperidone (Salt) from 1mg.com
Risperidone Uses
Risperidone is used in the treatment of schizophrenia and mania.How Risperidone works
Risperidone is an atypical antipsychotic. It works by affecting the levels of chemical messengers (dopamine and serotonin) to improve mood, thoughts and behavior.Common side effects of Risperidone
Insomnia (difficulty in sleeping), Parkinsonism, Sedation, Dizziness, Weight gain, Akathisia (inability to stay still), Anxiety, Gastrointestinal symptom, Increased prolactin level in blood.EXPERT ADVICE FOR RISPERIDONE
1. Risperidone helps treat schizophrenia and mania. 2. It may cause less weight gain, sedation, and heart problems as compared to other similar medicines. 3. It may take 4-6 weeks to notice any medication effects. Keep taking it as prescribed. 4. Use caution while driving or doing anything that requires concentration as Risperidone can cause dizziness and sleepiness. 5. It may cause increase in weight, blood sugar, cholesterol, and fat. Eat healthy, exercise, and monitor your levels regularly. 6. Inform your doctor if you experience any abnormal movements or restlessness. 7. Inform your doctor if you have a history of heart diseases as Risperidone can increase your risk of irregular heartbeat. 8. Do not stop taking Risperidone without talking to your doctor first as it may cause worsening of symptoms.
Student Update (2022-Jul-27)
Index of Journals
Counting
Komal Kumari Class: 4 Trial 1 (Beginning of class): Till: 16 Trial 2 (After an hour): Till: 20 Srishti Patel Class: Nursery Till: 1Tables
Kusum Kumari Class: 5 Till: 2Addition
Kusum Kumari Class: 5 Level: 7Subtraction
Kusum Kumari Class: 5 Level: 1 URL: https://survival8.blogspot.com/2022/01/add-subtract-multiply-divide.html
Tuesday, July 26, 2022
Detailed Solution to Upto Three Digit Subtraction
Note: We are going to subtract the smaller number from the bigger one.
Enter two numbers between 0 to 999.
First Number:
Second Number:
0
0
-
------------
Monday, July 25, 2022
Student Update (2022-Jul-25)
Index of Journals
Tags: Student Update,Counting
Komal Kumari Class: 4th Till: 16 Srishti Patel Class: Nursery Till: 10Tables
Kusum Kumari Class: 5B Till: 3 Yash Kashyap Class: 5 Till: 8Addition
Kusum Kumari Class: 5B Till Level: 4Subtraction
Kusum Kumari Class: 5B Till Level: 1 Yash Kashyap Class: 5 Till Level: 2
Sunday, July 24, 2022
Converting image to text, saving to disk, reading text from disk and displaying image
A brief introduction of 'base64' functions 'b64encode' and 'b64decode':
(base) C:\Users\Ashish Jain>python
Python 3.7.1 (default, Dec 10 2018, 22:54:23) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from base64 import b64encode as b, b64decode as d
>>> s = 'hello'
>>> b(bytes(s, 'utf-8'))
b'aGVsbG8='
>>> bs = b(bytes(s, 'utf-8'))
>>> d(bs)
b'hello'
>>> d(b'aGVsbG8=')
b'hello'
>>> d(bs).decode("utf-8")
'hello'
Now with image:
from base64 import b64decode, b64encode
image_handle = open('test_image.png', 'rb')
raw_image_data = image_handle.read()
encoded_data = b64encode(raw_image_data)
with open('i.txt', 'wb') as f:
f.write(encoded_data)
with open('i.txt', 'rb') as f:
b = f.read()
print(type(b))
[class 'bytes']
print(encoded_data == b)
True
with open('i.png', 'wb') as f:
f.write(b64decode(b))
If you have a text file and it has data such as this: b'iVB...ggg=='
That means you had called str() function on 'bytes' type data and saved that string.
If you have a text file that has data such as this: iVB...ggg==
Then, you can read this file as ">>> with open('img.txt', 'rb') as f:" to get a 'bytes' type data.
Deriving Derangement Theorem
Deriving Derangement Theorem
The growth of both the functions n! (factorial) and !n (derangement) is exponential, look at the table of values below:
| n | Permutation | Derangement |
| 2 | 2 | 1 |
| 3 | 6 | 2 |
| 4 | 24 | 9 |
| 5 | 120 | 44 |
| 6 | 720 | 265 |
| 7 | 5040 | 1854 |
We will work with the log (base Math.E) of these functions. Look at the table of values below:
| n | log(Permutation) | log(Derangement) |
| 2 | 0.693 | 0 |
| 3 | 1.791 | 0.693 |
| 4 | 3.178 | 2.197 |
| 5 | 4.787 | 3.784 |
| 6 | 6.5792 | 5.5797 |
| 7 | 8.5251 | 7.5251 |
We see the following relationship between these values:
log(!n) = log(n!) - 1
=> log(!n) = log(n!) - log(e)
=> log(!n) = log(n! / e)
=> !n = n! / e
And true relationship between !n and n! is: !n = round(n! / e)
Test this out by adding data to the plot showing n! and !n below:
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