Do you know the detailing about 'Drugs' or 'Medicine' ?

Do you know the detailing about 'Drugs' ?

  Drugs are chemicals that interact with the macromolecular targets to produce a biological response.

  However, some drugs are also used as a stimulant arising a state of euphoria and can be habit forming leading to addiction.

   Drugs are classified into different categories depending on certain criteria like their chemical structure, physical and psychological effects. Drugs affect the nervous system of individuals and create varied responses. 

              Pic Credit : Pixabay

Brief classification of drugs based on their physical and psychological effects is given below:

 Analgesics like aspirin reduce pain. 

  Anti-inflammatory drugs reduce inflammation in the body.  

  Antipyretics reduce body temperature. 

  Depressents are drugs that supress the activity of brain and nerves. These drugs are administered to relieve anxiety and promote sleep.

  Stimulants increase the activity of the brain and nervous system making an individual more energetic and ecstactic. They can also make an individual paranoid and induce anger.

   Hallucinogens are drugs that act on the central nervous system. They alter the perception of space, time and reality and the individual may start imagining things and situations that are not real.

   Opioids are used to treat pain and cough. 

   Inhalants exist in vapour state at room temperature and are consumed by inhaling 

   Antibiotics were earlier defined as chemicals produced from microorganisms used to kill or inhibit the growth of other microorganisms. Now since they can be artificially synthesised hence now they are defined as molecules that either kill or inhibit the growth of microorganisms.

  Psychoactive drugs affect the functioning of the central nervous system and alter mood, perception and consciousness. 

  Cannabis is an illicit drug used worldwide as charas, bhang and ganja. There are several other ways of classifying drugs. It should be remembered that most of the drugs serve medicinal purpose only in small quantity and have side effects if consumed in larger quantities. Here we shall discuss two commonly used drugs aspirin and paracetamol.

    Aspirin: It is a common drug used to reduce fever (antipyretic) and as an analgesic to relieve pain. Chemically it is acetyl salicylic acid prepared by the reaction of salicylic acid with acetic anhydride. 

    Paracetamol: It is one of the most common drug used to reduce fever and in the treatment of mild pain like headache, pain in joints, muscles and body pain.It is prepared by the nitration of phenol which gives both ortho and para-nitro phenol. The ortho isomer is removed by steam distillation and the para isomer is reduced to give p-aminophenol which on acetylation gives acetaminophen widely known as paracetamol. Although it causes lesser gastrointestinal side effects as compared to aspirin but overdose of paracetamol causes damage to liver.

     When the biological response is therapeutic assisting in the diagnosis, treatment or prevention of a disease it is termed as a medicine.

    

What is exactly Machine Learning and Data Mining ?

What is the exactly diffence between Machine Learning and Data Mining ??

Machine Learning and Data Mining are closely related fields, but they differ in their focus and methods. 

Here are the main differences between these two fields:

 Machine learning: 

    Machine learning is a subset of artificial intelligence that involves teaching computers to learn from data without being explicitly programmed. 

    In other words, machine learning algorithms can improve their performance on a task by learning from experience.   

    Machine learning is used in a wide range of applications, such as image recognition, speech recognition, natural language processing, and predictive analytics.

Data mining: 

    Data mining is the process of discovering patterns in large datasets using statistical and computational techniques. 

    Data mining is often used to find correlations and associations between different variables in the data and to identify patterns that can be used for prediction or decision-making. 

    Data mining can be used in a variety of domains, such as marketing, healthcare, and finance.

 If we discuss course point of view :

Machine learning courses typically cover topics such as supervised learning, unsupervised learning, reinforcement learning, decision trees, neural networks, and deep learning. 

These courses focus on the algorithms and techniques used to train machine learning models, as well as their applications in areas such as computer vision, natural language processing, and predictive analytics.

Data mining courses typically cover topics such as data preprocessing, association rules, clustering, classification, and outlier detection. 

These courses focus on the statistical and computational techniques used to discover patterns in large datasets, as well as their applications in areas such as marketing, healthcare, and finance.

Is Human intelligence still relevant in the time of Artificial Intelligence ??

Why we are using Gradient, Divergence and Curl in Mathematics and Physics ?

Why we are using Gradient, Divergence and Curl in Mathematics and Physics ?

      Gradient, divergence and curl are mathematical operations that are widely used in physics, particularly in the field of vector calculus. 

      These operations help to describe various physical quantities in terms of their spatial distribution and how they change over time.

Here are some examples of how these mathematical concepts are used in physics:

1.      Gradient: The gradient of a scalar field (a function that assigns a scalar value to each point in space) describes the direction and magnitude of the maximum rate of change of the scalar field. 

       In physics, the gradient is often used to describe the direction and magnitude of a force acting on an object, such as the gravitational force or electric field.

2.      Divergence: The divergence of a vector field (a function that assigns a vector to each point in space) describes the rate at which the vector field is expanding or contracting at each point in space. 

       In physics, the divergence is often used to describe the behavior of a fluid, such as the rate at which mass or energy is flowing into or out of a region of space.

3.      Curl: The curl of a vector field describes the rotation or twisting of the vector field at each point in space. 

        In physics, the curl is often used to describe the behavior of a magnetic field, such as the motion of charged particles in a magnetic field.

Overall, gradient, divergence, and curl are fundamental mathematical tools that help to describe the physical world in terms of its spatial and temporal variations.

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What is the diffrence between Interference and Diffraction ??

Interference and diffraction are both phenomena that occur when waves encounter an obstacle or opening in their path, but they differ in their underlying mechanisms and the patterns they produce.

Interference occurs when two or more waves interact with each other in a region of space. When waves of the same frequency meet, they add together to produce a new wave that has a larger amplitude (constructive interference) or a smaller amplitude (destructive interference) than the individual waves. This creates a pattern of alternating bright and dark fringes, known as an interference pattern.

Diffraction, on the other hand, occurs when waves encounter an obstacle or aperture that is comparable in size to their wavelength. When waves encounter such an obstacle, they bend around it and spread out in all directions. This bending and spreading out of waves is known as diffraction, and it produces a pattern of light and dark bands or fringes that are characteristic of the shape and size of the obstacle or aperture.

In summary,

 interference involves the interaction of waves with each other, resulting in the creation of an interference pattern.

Diffraction involves the bending and spreading out of waves around obstacles or apertures, resulting in the creation of a diffraction pattern.