AI and ML for a better future

Have you ever considered about what motivates artificial intelligence programmes like Tony Stark’s JARVIS or the common man’s Alexa, Google Assistant, or Siri? These programmes can answer your calls and help you make decisions, but have you ever wondered what motivates them? In what ways does their brain operate? The application of Artificial Intelligence (AI) and Machine Learning is the straightforward response to each and every one of your questions (ML). The mechanical brains are controlled by artificial intelligence, which attempts to simulate human intellect so that they can perform like a human brain. With more and more research being done on AI and ML, there is the potential for AI and ML to assist in training computers to make decisions on their own, which will eventually make our lives easier by reducing the amount of work we have to perform. 

This article, which was meticulously researched and penned with the intention of depicting the future reach of AI and ML in India, was created with the goal of assisting students in understanding how this subject will be advantageous to them if they decide to pursue it. 

The potential applications of artificial intelligence in India are still in the process of being adopted, but the technology is gradually being put to use to find intelligent solutions to modern problems in almost all of the country’s most important industries, including agriculture, healthcare, education and infrastructure, transportation, cyber security, banking, manufacturing, business, hospitality, and entertainment. Readers who are interested in pursuing a course in artificial intelligence can find helpful information in this article. Candidates will gain some insight into the potential of artificial intelligence in India if they read this article and consider its contents. 

Scope of AI in India 

Both artificial intelligence and machine learning have a promising future in India and an immense potential to alter every area of the economy for the benefit of society. Artificial intelligence and machine learning have a bright future in India. AI is an umbrella term that incorporates a variety of helpful technologies, such as self-improving algorithms, machine learning, pattern recognition, and large amounts of data. Soon, there will not be a single business or market segment in India that is immune to the effects of this powerful instrument. This is one of the reasons why there is a growing demand for online courses in artificial intelligence in India. 

Scope of AI and ML in Education Sector 

By utilizing a variety of AI applications such as text translation systems, real-time message to speech, automating mundane and also repeated tasks such as taking presence, automating grading, and also customizing the learning journey based on ability, comprehension, and also experience, artificial intelligence can help our instructors be more effective. Within the purview of Artificial Intelligence education and learning is the consideration of the prospect of utilizing AI-powered rating machines that are able to evaluate solutions in an objective manner. This is being carried out in college and university settings in a step-by-step fashion. Real-time text-to-speech synthesis and text translation are two further AI-based applications in the educational sector. 

The Role of AI and ML in the Development of Chatbots 

The combination of chatbots in the digital framework or availability via the IVRS system education domain can be transformative in a country as diverse as India. They can be educated on the subject matter, and a large percentage of the students’ doubts can be answered quickly. This reduces the current workload of educators, allowing them to focus on more creative tasks. 

The Integration of AI and ML into the Automated Grading System 

On a more global scale, methods of machine learning such as Natural Language Processing could be used for automated grading of assessments on systems such as E-PATHSHALA, SWAYAM (Study Webs of Active Learning for Young Aspiring Minds), and DIKSHA. This would apply not only to inquiries that are subjective but also to those that are objective. This is because of the National Education Policy 2019, which places an emphasis on computer and internet literacy. 

The Role of AI and ML in the Healthcare Industry 

The healthcare industry in India is one of the most rapidly developing and competitive markets in the world. There is a dearth of doctors and services, including competent nurses and technicians, as well as infrastructure. This is one of the primary issues, but there are many others as well, including affordability and accessibility. As a result of the majority of high-quality medical facilities in India being situated in close proximity to tier 1 and tier 2 cities, access to healthcare in India is not uniformly distributed across the country physically. Aside from that, as Artificial Intelligence develops, there will be an increase in efficiency, which will lead to a reduction in the overall cost of medical treatment. 

Because AI is able to process vast volumes of data in a short amount of time, it can be of assistance in the creation of medical equipment, as well as in design and innovation. Having a system that is enabled with AI helps to eliminate medical errors and increases overall productivity. Artificial intelligence has the potential to both circumvent access barriers and provide a solution to the accessibility problem by applying early detection followed by suitable diagnostic conclusions. 

AI and ML in the Agriculture Sector 

In India, agriculture is a major source of income for many people. Traditional farming methods pose a slight challenge for Indian farmers. Thermal imaging cameras can be used to continuously monitor agricultural land to ensure that plants receive adequate water. When it comes to selecting the right crop and the optimum method of sowing, this tool can help you get the most out of your land and save money. 

As a result, improved insect control preparation can benefit from the application of artificial intelligence to predict behaviour and investigate parasites. Artificial intelligence-assisted anticipating modelling can be effective for delivering more detailed demand-supply details and for predicting the needs of farmers in terms of agricultural produce. 

Automated Vehicles Using AI and ML 

In the transportation industry, artificial intelligence offers a lot of potential. Artificial intelligence (AI) has the potential to be useful in a few specific contexts. Since its invention in 1922, autopilot has been used to keep ships, planes, and spacecraft on course. Self-driving cars are another field of research. Self-driving automobiles are being researched by companies around the world, including India. The use of artificial intelligence and machine learning has been prevalent in the design of these automobiles from the beginning. Self-driving cars, according to experts, will have various advantages, such as reducing pollution and eliminating human error from driving. 

Artificial Intelligence and Machine Learning for a Smart Home 

We are surrounded by artificial intelligence. Most of the time, we don’t even realize we’re interacting with devices powered by artificial intelligence. As an example, we routinely use OK GOOGLE, ALEXA, or CORTANA to execute a variety of chores by simply speaking to them. Artificial Intelligence and Machine Learning are used by these intelligent assistants for voice recognition. Learning from the user’s commands improves their productivity. You may ask a question, play a song, and buy anything online all with the help of this clever assistant. 

Applied Artificial Intelligence and Machine Learning in Cybersecurity 

Cybersecurity is another area where AI is being applied. Many companies have to deal with a lot of data. A security system is required, for example, in the banking industry or government entities that maintain vast databases containing the personal information of citizens. An good example of this topic is Cognitive Artificial Intelligence (CAI). Additionally, it helps analysts make better judgments by detecting, analysing, and reporting on hazards. 

Machine Learning formulae and Deep Learning networks are used to improve and strengthen the AI over time. As a framework and central point of control for safety and security responses, IBM Resilient is an open and agnostic platform. 

In the Manufacturing Industry, AI and ML 

The industrial sector is a popular target market for AI-based firms from India. In order to assist the manufacturing industry flourish, these companies are developing AI-based solutions. Various types of robots are controlled by artificial intelligence in the workplace. The ability to examine data and forecast the future is a unique AI technology. 

Using this AI capabilities, companies may estimate future supply and demand based on data from prior years’ sales or market surveys, allowing them to make faster decisions and better use of existing products. Artificial intelligence (AI) will be widely used in manufacturing in the future years. 

How is Biotechnology impacting millions of lives?

Are you an avid lover of biology? Are you naturally inclined to apply the principles of biology to create an impact on people’s lives? Well, then the Biotechnology sector is where you may find your dream job.

With the world still reeking of over 520 million deaths due to the COVID-19 pandemic, it is undeniable that the figure could have been in billions or even more had it not been for the Biotechnology sector. Almost everything starting from the diagnosis and immediate treatment to the development of vaccines brought to light the promise that Biotechnology holds as a leading technology in the modern world. To know more about the potential of Biotechnology and the facets of human lives that it is able to impact upon, read further down.

What is Biotechnology?

Biotechnology is an industrial sector that deals with the manipulation of living organisms to create commercial products. For instance, the wealth of knowledge accumulated by cell biologists, botanists, zoologists, molecular biologists, and geneticists have been implemented by genetic engineers to manipulate information carried by the DNA in order to create transgenic animals and plants of commercial importance. Quite undoubtedly, the deepest penetrations of the biotechnology sector has been in the healthcare and agricultural markets. However, there are several other important areas where Biotechnology is making inroads with sustainable solutions. This blog highlights some fields wherein Biotechnological interventions are working wonders.

Vaccine development

Within a few months of the detection of coronavirus, scientists mapped the entire genome of the virus and it helped to understand how the virus operates. Genome mapping being an important technique in Biotechnology, the Biotechnology sector can boast of its towering presence in global markets across the map. Also, the highly effective mRNA-based vaccine for COVID-19 was first tested in cells inside the laboratory which entails practising some basic techniques of Biotechnology. Weighing the outcomes, government organizations and pharmaceutical giants have entered into strong public-private partnerships to pool resources and fund research in the domain of vaccine development.

Next-generation computing-aided drug discovery

Advanced computing technology such as artificial intelligence and machine learning have enabled Biotech companies to automate their processes and scale up operations. This handholding of technologies have enabled to reduce the cost and time required to take new drugs from bench to bedside. The ability to analyze large data sets helps medicine manufacturers to identify treatments based on the root cause of a disease. This holds immense potential to reduce the usual 90 percent failure rate for developing new drugs.  Data mining from current clinical trials can also help to predict the effectiveness of treatments down to a molecular level and even predict new or different uses for an existing drug thereby reducing cost and effort of establishing new drugs.

Genome editing

Techniques for manipulating the information present in the DNA, known as gene editing in technical jargon, has come a long way since they were first used to make edits such as addition, deletion, silencing, or replacement of a specific gene. Precise gene editing has been made possible by the advancement of technologies such as the revolutionary CRISPR-Cas9 systems. Engineered nucleases called CRISPRs acting as molecular scissors have unfurled a plethora of applications in gene therapy for the treatment of many conditions including rare genetic disorders and even fatal cancers. Furthermore, gene editing has also allowed the development of improved transgenic plants and animals capable of synthesizing a variety of medically important recombinant human proteins such as Insulin.

Precision medicine

Sequencing the entire human genome, an initiative known as the Human Genome Project, began in 1990 and was completed by 2003. This was another hallmarking achievement of Biotechnology that now allows extensive screening of patients and targeting of interventions. Improvisation of sequencing technologies have reduced the cost of genetic sequencing drastically ever since thereby making personalized gene sequencing affordable. This, in turn, has enabled the development of personalized treatment plans and targeted therapies, which are more effective than less-specific therapies because they focus on a patient’s genetic constitution. Furthermore, the falling cost of sequencing technologies has fostered the development of rapid and inexpensive methods to detect pathogens from clinical samples as well as soil samples.

Boosting agricultural yields

The global population is set to increase by 25% from 7.9 billion in 2022 to 9.7 billion in 2050. The basic need for a growing population is food, and hence its demand for feeding both people and livestock is about to increase proportionately. This automatically necessitates the use of increasing hectares of land for farming while practically cultivable land will keep on reducing as the expanding population of humans keep encroaching onto such lands. Biotechnology offers a solution to this alarming problem through the approach of gene editing. For example, crops such as wheat or corn may be engineered through the transgenic technology to grow in harsher conditions or produce more grain in a smaller area than other crop varieties while providing the same nutritional value. From another perspective, the development of biopesticides can enable protection of crops without the use of harmful chemicals thereby averting environmental damage. 

Bioprinting and tissue engineering

Another promising futuristic application of Biotechnology in the medical field is 3D bioprinting, wherein bioprinters are used to develop cell-based scaffolds using a ‘bio-ink’ comprising cells and biomaterials. This empowers one to develop skin, bone, and vascular grafts from the patient’s own cells for personalized medicine. The bioprinting technology has added a major thrust to the field of tissue engineering and regenerative medicine by enabling the creation of autologous tissue grafts for wound healing and organ transplantation.

Conclusion

These trends clearly show that the demand for biotechnology is on the rise. The fact that this particular sector is being able to solve real-life problems related to human health and nutrition has catapulted it to fame. It is also quite evident that biotechnologists need more than just a background in biology, chemistry, or pharmaceutical science to build their careers upon. With innovative solutions rooted to the genetic level, biotechnology is here to stay and offer myriad career opportunities to the brightest minds!

Is Operations Research useful in Data Science?

“Operations research (OR) is defined as the scientific process of transforming data into insights to making better decisions.”

The Institute for Operations Research and the Management Sciences (INFORMS)

Introduction:

In the twenty-first century, especially in the last decade, the most trending domain of study is may be Data Science and Data Analytics. In this domain of study, people work with data from different fields and they use different tools and techniques from the domain of Mathematics, Statistics, and Computer Science to study and analyze the data. Then make some conclusion from the data and use them to predict the future of the phenomenon under study. Before the rise of data science as a domain of study, Operations Research analyst and Statisticians are used to do the similar kind of job. Due to these facts, the overlap between the domain of Data Science and the domain of OR is misunderstood. Also, there is a common perception that OR is not useful in for Data Science or Data Analytics. Actually, the marketing of OR products and services which are applied to solve the real world problems leads to this kind of misconception, as most of the time the end-users do not have an understanding or background of OR and data science. Another possible reason may be that the availability of machine learning models which are available as packages of several platforms like Python and do not really contain specific any OR models. In practical, OR tools and techniques are applicable to data science. In fact, a lot of ideas which are used in Artificial Intelligence (AI) and data science problem solving, have cross-pollinated from OR due to the large overlap in the techniques and methods used. In this blog, I try to explore these relations of OR with Data Science and Data Analytics.

Data
Image Source: https://www.humancenteredor.com/2015/03/

Operations Research and Data Science:

Before going to the discussion on the role and relation between Data Science and OR, let us try to understand another very important term called Analytics. According to INFORMS, Analytics is the application of scientific & mathematical methods to the study & analysis of problems involving complex systems. There are three distinct types of analytics:

i) Descriptive Analytics gives insight into past events, using historical data;

ii) Predictive Analytics provides insight on what will happen in the future; and

iii) Prescriptive Analytics helps with decision making by providing actionable advice [https://www.informs.org/Explore/Operations-Research-Analytics]. In an INFORMS podcast, depending on organizational backgrounds, Glenn Wegryn divides Analytics into two distinct camps: Data Centric Analytics where data is used to find interesting insights and information to predict or anticipate what might happen; and Decision Centric or Problem Centric Analytics which is used to understand the problem, then determine the specific methodologies and information needed to solve the specific problem. This data centric analytics are done by using Data Science whereas problem centric analytics are done by Operations Research. The above mention figure clearly give an idea about this. From the figure, it is very clear that there is a common point of interest from both the domain. Hence OR plays a very important role in Data Science domain.

Operations Research and Machine Learning:

Machine learning is the area of data science where most of the OR tools and techniques are used. Linear programming and Optimization techniques are fundamental part of the overall machine learning lifecycle. Some of the examples of OR are:

  • Enabling smart human resource management by forecasting human resource requirements and optimizing daily schedule for resource persons (linear programming model)
  • Increasing TV program viewership by optimal scheduling of programs’ promotion (linear programming model)
  • Enabling supply chain transformation by providing AI/machine learning-based recommendations for optimized product utilization
  • AI-enabled forecasting for retail and eCommerce applications to optimize funnel and customer traffic
  • Data-driven optimization models for automated inventory management where we need to do warehouse management, inspection and quality control

Operations Research and Artificial Intelligence:

Another important area of data science is Artificial Intelligence where we can observe the use of OR algorithm. AI is used to build an automated system. Now, any real-life system have many decision variables and parameters, so if we want to build an automated system then we have to deal with a lot of decision variables. That’s why operations research algorithm must be a core engine in the system.

An Artificial Intelligence development lifecycle consists of the following steps: (Link)

Descriptive and Predictive steps:

  • In the first step, we need to define the problem to be solved
  • In the next step, we need to understand the current state of the problem and accordingly we have to define the work scope
  • Next we need to develop a Machine Learning model, where the machine learning solution is developed and tested.

Prescriptive steps:

  • Machine learning outputs or the predictions obtained using machine learning are given as OR inputs. Here, the OR techniques are used to make recommendations based on the outputs from the ML model. This is a critical step for the entire life cycle.
  • Finally, the solution output is delivered to the client.

Covid-19 impact:  

During the COVID-19 pandemic, more than ever, data science has become a powerful weapon in combating an infectious disease epidemic and arguably any future infectious disease epidemic. Computer scientists, data scientists, physicists and mathematicians have joined public health professionals and virologists to confront the largest pandemic in the century by capitalizing on the large-scale ‘big data’ generated and harnessed for combating the COVID-19 pandemic. (Zhang, Qingpeng, et al. “Data science approaches to confronting the COVID-19 pandemic: a narrative review.” Philosophical Transactions of the Royal Society A 380, No. 2214 (2022)). Covid-19 has a big impact on supply chain strategies also. People from data science community are analyzing “lessons learned” from the pandemic to better prepare and more efficiently and effectively respond to the next disaster, interested people can visit the following for a discussion on it (Link1).

Conclusion:

From the above discussion, it is very much clear that Data Science and Operations Research have some overlapping objectives with clear line of difference between these two domains of study. Also, we observe that there are several OR techniques and algorithms which have important role to play in different topics of data science. In my opinion, operations research together with data science and analytics is going to play a very important role to build the future of us.

THE NANO SCIENCE AND ITS CONTRIBUTION IN TREATING CANCER

Nanoscience involves the study of the control of matter on an atomic and molecular scale. This molecular level investigation is at a range usually below 100 nm. In simple terms, a nanometer is one billionth of a meter and the properties of materials at this atomic or subatomic level differ significantly from properties of the same materials at larger sizes. Although, the initial properties of nano materials studied were for its physical, mechanical, electrical, magnetic, chemical and biological applications, recently, attention has been geared towards its pharmaceutical application, especially in the area of drug delivery. According to the definition from NNI (National Nanotechnology Initiative), nanoparticles are structures of sizes ranging from 1 to 100 nm in at least one dimension. However, the prefix “nano” is commonly used for particles that are up to several hundred nanometers in size. Nanocarriers with optimized physicochemical and biological properties are taken up by cells more easily than larger molecules, so they can be successfully used as delivery tools for currently available bioactive compounds.

Cell-specific targeting can be achieved by attaching drugs to individually designed carriers. Recent developments in nanotechnology have shown that nanoparticles (structures smaller than 100 nm in at least one dimension) have a great potential as drug carriers. Due to their small sizes, the nanostructures exhibit unique physicochemical and biological properties (e.g., an enhanced reactive area as well as an ability to cross cell and tissue barriers) that make them a favorable material for biomedical applications. It is difficult to use large size materials in drug delivery because of their poor bioavailability, in vivo solubility, stability, intestinal absorption, sustained and targeted delivery, plasma fluctuations, therapeutic effectiveness etc. To overcome these challenges nanodrug delivery have been designed through the development and fabrication of nanostructures. Nanoparticles have the ability to penetrate tissues, and are easily taken up by cells, which allows efficient delivery of drugs to target site of action. Uptake of nanostructures has been reported to be 15–250 times greater than that of microparticles in the 1–10 um range. Nanoparticles can mimic or alter biological processes (e.g., infection, tissue engineering, de novo synthesis, etc. These devices include, but not limited to, functionalized carbon nanotubes, nanofibers, self-assembling polymeric nano constructs, nanomembranes, and nano-sized silicon chips for drug, protein, nucleic acid, or peptide delivery and release, and biosensors and laboratory diagnostics. Various polymers have been used in the design of drug delivery system as they can effectively deliver the drug to a target site and thus increase the therapeutic benefit, while minimizing side effects. The controlled release (CR) of pharmacologically active agents to the specific site of action at the therapeutically optimal rateand dose regimen has been a major goal in designing such devices. The drug is dissolved, entrapped, encapsulated or attached to a NP matrix and depending upon the method of preparation, nanoparticles, nanospheres or nanocapsules can be obtained. Nanocapsules are vesicular systems in which the drug is confined to a cavity surrounded by a unique polymer membrane, while nanospheres are matrix systems in which the drug is physically and uniformly dispersed. Biodegradable polymeric nanoparticles have attracted considerable attention as potential drug delivery devices in view of their applications in the controlled release of drugs, their ability to target particular organs/tissues, as carriers of DNA in gene therapy, and in their ability to deliver proteins, peptides and genes through a per oral route of administration. Recent advances in the application of nanotechnology in medicine, often referred to as nanomedicine, may revolutionize our approach to healthcare. Cancer nanotechnology is a relatively novel interdisciplinary area of comprehensive research that combines the basic sciences, like biology and chemistry, with engineering and medicine. Nanotechnology involves creating and utilizing the constructs of variable chemistry and architecture with dimensions at the nanoscale level comparable to those of biomolecules or biological vesicles in the human body. Operating with sub-molecular interactions, it offers the potential for unique and novel approaches with a broad spectrum of applications in cancer treatment including areas such as diagnostics, therapeutics, and prognostics.

Nanotechnology also opens pathways to developing new and efficient therapeutic approaches to cancer treatment that can overcome numerous barriers posed by the human body compared to conventional approaches. Improvement in chemotherapeutic delivery through enhanced solubility and prolonged retention time has been the focus of research in nanomedicine. The submicroscopic size and flexibility of nanoparticles offer the promise of selective tumor access. Formulated from a variety of substances, nanoparticles are configured to transport myriad substances in a controlled and targeted fashion to malignant cells while minimizing the damage to normal cells. They are designed and developed to take advantage of the morphology and characteristics of a malignant tumor, such as leaky tumor vasculature, specific cell surface antigen expression, and rapid proliferation.

Nanotechnology offers a revolutionary role in both diagnostics (imaging, immune-detection) and treatment (radiation therapy, chemotherapy, immunotherapy, thermotherapy, photodynamic therapy, and anti-angiogenesis). Moreover, nanoparticles may be designed to offer a multifunctional approach operating simultaneously as an effective and efficient anticancer drug as well as an imaging material to evaluate the efficacy of the drug for treatment follow-up. In recent years, nanomedicine has exhibited strong promise and progress in radically changing the approach to cancer detection and treatment.

Post-pandemic career prospects in sound

Summary: A discussion about the subjects related to sound and the respective career opportunities.

Introduction: Though pandemic made the lives of sound professionals a bit miserable like it did for many others, now it is back to quite normal.  The cinema, radio, music and television industry are again back in full swing after a small dip in the graph. So for those interested to build a career in the audio, it is necessary to understand the subjects related to sound. Hence, first I will give a brief idea about the subjects related to sound and then I will mention the career opportunities.

How to begin? : The study of sound is a vast field. It is like an ocean with innumerable waves that one can choose form. Precisely the subject of sound is a field of study that deals with how human beings perceive sound. That perception can be manipulated for a better listening experience. That’s the primary goal of a sound practitioner. Now this listening experience of human beings varies according to the sonic environment, where the listener places himself. Depending on this varied listening environments, the science of sound could be studied differently. This is why study of sound has given birth to many disciplines. For example, sound engineering or audio engineering, sound designing for cinema, theatre, radio and television, music production, live recording for cinema, television, auditorium shows, podcasting, acoustics, and sound installation to name a few. Now let’s have a brief idea about each of the field mentioned above.

  1. Sound Engineering/Audio Engineering: This field is a bit technical. To pursue a higher degree in sound engineering one should have a clear understanding of basic physics and mathematics of higher secondary standard. In this subject students are taught about the technical or engineering aspects of the sound systems that are responsible for generating, recording and processing sound for various fields. For instance, in this subject of sound engineering students learn details of microphones including how and where to place them. In other words students develop an idea of selecting suitable microphones for specific purposes. Similarly they learn about speaker systems, how to manufacture them and how to select suitable speaker systems for given sonic environments. They are also taught about the relation between sound reinforcement systems and various types for enclosed and open environments.
  2. Sound Designing: This field focuses more on the aesthetics of sound with respect to various media like cinema, television, theatre, radio etc. It does not require hard core knowledge of physics and mathematics that is required to study sound or audio engineering. Instead it requires a creative drive or passion to play with sound. In this course students are generally taught how to evoke an emotion from within the hearts of an audience. That’s the primary purpose of studying sound designing and it is not as easy as it sounds. To play with the emotion of an audience requires absolute mastery over the art and craft of sound. However, this course introduces students with Digital Audio Workstation or DAW equipped with software, computer, mixing console, sound card, microphones, speakers etc. all installed within an acoustically treated room for a specific purpose. However to design a DAW, the help of a sound engineer is needed. DAW is a concept that has come from cinema post production and then it has been incorporated in the field of television and radio too. For theatre the support of DAW is often required to predesign the sound track for the show. But the live arrangement might also be needed for the same. For cinema generally students are extensively taught about the sound elements like dialogue, music, ambience and foley and to record these elements students are taught how to operate a dubbing studio for dialogue, how to operate a studio for music, how to record and lay ambience in a DAW and how to operate a foley studio. Besides they are also taught about creating and working with various sound effects.
  3. Live Recording: This field is probably the most adventurous part of sound. It requires extreme travelling. For cinema there remains dedicated location audio engineers, whose job is to record clear audio especially dialogue at the location of shooting itself. So in this course students are taught about the dedicated location audio gears and how to record with them. Also this field requires extreme man management skill as the location engineer and his/her team must know how to handle actors and other crew members at shooting spot. Apart from cinema, live recording is a challenging and well paid job for music shows. So the students of this course are taught extensively about setting up sound reinforcement systems for  music shows for example in a stadium. Besides they are also taught about how to manage sound reinforcement system in an enclosed environment e.g. an auditorium.
  4. Podcasting: Podcasting is comparatively a new buzzword. This became popular with the arrival of internet. This is nothing but making an audio track available for downloading for other users. It could be either free or paid. So the students of podcasting are mainly taught about the same thing related to sound designing. There is a trend nowadays that podcasting could be done with a smart phone. It is true that it is possible. But the quality of this type of audio will always be questionable and unprofessional since however digital we might become, our ears are still analogue, microphones and speakers are still analogue and will always remain so. So the quality of a podcast will always indicate whether it has been recorded in a bad or good studio or acoustically controlled environment. So the students of podcasting are taught about the quality of an audio track especially about the difference of recording with a bad set-up and a good set-up as quality does matter in the long run.
  5. Acoustics: This field is basically the study of behaviour of sound in a specific environment. Basically it teaches how to build up an environment for soothing aural experience. It could be a cinema hall, an auditorium, a shopping mall or even a house. All require acoustic treatment to avoid the irritating unwanted sound or noise of surroundings. So the students of acoustics are taught about architectural designs for less noisy and soothing sonic environments. However, this course requires basic idea about mathematics and physics as a prerequisite.
  6. Sound Installation: This is another field of sound. This course teaches about sound reinforcement systems and how to install them. For example, in a multiplex of, say, four cinema halls, the sound reinforcement systems are to be installed. This course teaches about how to do that. It requires basic ideas about electronics and electrical engineering along with thorough knowledge of sound engineering.

Career Opportunities: So studying any of these subjects will open the doors for a professional to work as

  1. Sound Engineer
  2. Sound Designer for movies, television, radio and theatre.
  3. Studio Manager
  4. Acoustic Consultant
  5. Digital Remastering Engineer
  6. Live Sound Engineer
  7. Studio Designer
  8. Academician
  9. Entrepreneur
  10. Technician
  11. Researcher

Conclusion: In a nut shell to become a sound professional requires hard work, patience and passion. There are many schools in India and abroad that teach various disciplines of audio and now the cinema, television, radio and internet portals are operating in full swing after being hit by an instantaneous wave of the pandemic. The demand for the right sound professionals is higher than before as both the audiovisual and audio-only contents are becoming more and more popular every day.  All you need is to develop the right skill sets and aptitude for audio. Then the world is yours!

Lean Management – An Advanced Management Practice in Construction Industry

1.0 Preamble

The lean thinking is a scientific approach in managing time and cost of the construction project which emphasize waste minimization and customer satisfaction. It originated from Toyota and adopted all over the world for managing the manufacturing process to enhance the quality, productivity and safety. The focus point of lean management is to design a customer centric approach by minimizing cost and time by reducing all kind of wastes in the production.

2.0 Lean Management in Construction

The construction is an uncertain sector where the target business remains as it is but priorities changes frequently. Here supportive and non-value addition works are more comparing than manufacturing sector, adopting lean principle is a challenge. Here to increase the operational efficiency, one need to control the inventory even though the unpredictable weather, market, vendors, inventory requirements and especially the labours both skilled and unskilled.  These variations cannot be eliminated by one go with lean principles but it can improve the controllable and uncertainties will be addressed confidently. Lean management helps the team to schedule the resource requirements such as men, machine and materials more effectively which provides the expected outcome within the estimated time and budget. This encourages the construction firms to adopt lean management as tool for continual improvement in product and services through effectively managing process and practices.

The six basic lean principles followed in construction management are discussed below for common understanding and implementation.

  1. Identifying Value

The construction industry mainly has focused on the needs of the customer to provide value to the product/service demanded.  Realizing the customer requirement and perspective during the planning stage and shape their idea in to reality with an efficient team of engineers, suppliers and labours will provide great faith on the firm.

  1. Map the Value Stream

Generate a value stream such a way that the process and procedures are well defined and precisely mapped with action plan and resources requirements to give the confidence to the customer that it will be delivered in time.

  1. Eliminating Waste

The main aim of lean practice is to eliminate waste where every possible and following are the major areas to be considered

  • Transportation –  Avoid waste during transportation of men, machine, materials and equipment when moved from one site to other. Provide precise information about the transfer of goods, date, time, location and quantity to avoid excessive waiting, movement and overproduction.
  • Inventory –  Provide exact inventory requirements by proper estimation and avoid surplus materials which will be idle in the site and shoots-up the cost and space.
  • Movement –  Avoid moving materials, equipment and manpower multiple time across the site and create unnecessary motion.
  • Wait Time –  Do proper scheduling to avoid unengaged manpower, material and machines. This makes either manpower or equipment kept idle for unavailability of one over other because of improper planning.
  • Utilisation of Resources – Allocate right person for the right job to avoid expertise or knowledge go waste on the other hand quality output will not be there right in time. Maximum utilization of available resources is very much important.
  • Excess Processing –  Reduce the unwanted task which doesn’t make any value to the project which lead over processing.
  • Over Production –  It happens when one process completed earlier than the expected time.
  1. Create Continuous Workflow

The purpose of lean practice is to achieve systematic, reliable and time bounded result in the construction project. In the lean management, every stage is to predetermined and need to be performed sequentially. There should not be any bottlenecks and to achieve this proper communication and collaboration required among team at every stage. Need to divide the construction activity and ensure time and resources to complete the work within the project schedule.

  1. Create Pull System

Creating stable workflow is a healthy sign to your organization that it will deliver the work task faster and effortless. This can be achieved by pull system or scheduling appropriately to make the collaborative work to understand the sequential nature of the work to complete with in the target time.

  1. Continuous Improvement

The continuous improvement is an essential life line of lean construction. Always identify the scope for improvement and act accordingly, for this close monitoring is required, similarly at any time uncertainties may occur for that you should be vigilant enough to control and manage the project with in the time frame and budget. This makes the construction project economical and profitable to the company.

3.0 Benefits of Lean Management in Construction Industry

  1. Lean Management minimize the cost of production and maximize the profit
  2. It values the customer feedback and improves the customer interaction and value. This enhances the product and services of the organization.
  3. Establishment of Pull and Push system prevents over production and carrying cost.
  4. The focused monitoring in to detail minimize the defects and increases the quality of the product.
  5. Lean Management provides a systematic, well defined work frame which reduces uncertainties and increases the safety of the employees.
  6. Introducing Lean Management will encourage work force for daily improvement that create a healthy atmosphere within the organization
  7. In the lean process, managers are frequently in interaction with employees about the work process, this makes them feel aligned and creates great bonding.

4.0 Concluding Note

The implementation of lean management is the need of the hour to all the construction industry to practice sustainable technology by eliminating the waste, increasing the efficiency, productivity and quality of the construction. This customer focused approach will promote inclusive culture within the organization lifts not only productivity and also employee satisfaction.

Technological spin-offs from High Energy Physics research

The Large hadron Collider at the CERN (Image courtesy: CERN)
The Large hadron Collider at the CERN (Image courtesy: CERN)

There is some good news waiting for the air travellers. They’ll soon be able to walk through airport security without having to separate liquids and gels in their hand baggage. Thanks to the new upgraded computerised tomography (CT) scanners that can detect explosives without going through a separate screening for the liquids and gels.

This discovery was widely publicised and lauded as a lifesaver for both travellers and security staff. But what was less frequently noted in those reports is that this advancement was made feasible due to the insights gained from the development of particle accelerator physics.

The bright and novel concepts and technology of particle physics have penetrated the mainstream of society to revolutionise our lives, from the first days of high energy physics to the recent times.

A broad and rising list of useful practical applications with contributions from particle physics can be seen in medicine, homeland security, industry, computers, science, workforce development etc. Noted below are a few such examples.

 

Medicine:

  • MRI: Magnetic resonance imaging (MRI) is a basic medical diagnostic technique that employs superconducting magnet technology, which was developed by scientists to accelerate protons to the maximum energy possible. Based on nuclear magnetic resonance principles, MRI creates high-quality images of the inside of the human body. Powerful magnets composed of superconducting wire and cable are at the heart of MRI technology. This technique was first created to build Fermilab’s Tevatron, the world’s first superconducting synchrotron, by a team of professionals in superconductivity, physics, engineering, material science, and manufacturing.

 

  • Cancer Therapy: Particle physics technology has resulted in significant advancements in cancer treatment. Accelerators that produce x-rays, protons, neutrons, or heavy ions are used at every major medical centre for illness diagnosis and treatment. Proton therapy, in comparison to x-rays, has significant therapeutic benefits, particularly for young patients. In the 1950s, medical linear accelerators for cancer therapy were developed at Stanford and in the United Kingdom using techniques developed for high-energy physics research. This innovation leads to a new industry and countless lives were saved. According to estimates over 7,000 functioning medical linear accelerators have treated over 30,000,000 people around the world.

Computing: 

  • The World Wide Web: The World Wide Web was created by particle physicists to allow them to connect rapidly and effectively with peers all around the world. Tim Berners-Lee, a CERN scientist, created the World Wide Web to allow particle physicists to interact seamlessly with colleagues at universities and laboratories all around the world. This breakthrough has a massive impact on the global economy and societal ties that few other innovations can equal.

 

  • The Grid Computing: Particle physics experiments generate massive volumes of data, which necessitates the use of cutting-edge computing equipment. The Grid is a revolutionary particle physics computing platform that combines the power of hundreds of thousands of separate computing farms to allow physicists to manage and process unprecedented volumes of data around the globe. Medicine and finance are two examples of industries that create vast volumes of data and can benefit from improved computing technologies. To process this large volume of data, particle physicists took advantage of the computers located all around the world and build a virtual supercomputer – making it the latest computing machine for the particle physicists

Industry:

  • Biomedicine and drug development: The role of protein in biological processes is paramount. Thus, to find the root cause of diseases we need to identify the responsible protein and understand its structure. This process is the prerequisite for any drug development. The technologies used for particle physics experiments are proving to be of great help in this endeavour of analyzing the protein structure.

 

  • Power Transmission: With the advancement of accelerator technology, significant progress has been made in the area of superconducting materials. Now, these innovations are being applied in the sector of power transmission. The advantage of using superconducting materials over the conventional wire results in transmitting more electricity while keeping the power losses at a minimum.

To summarize, we can say particle accelerator research and development has fuelled innovation for over a century. As a result, applications with huge societal benefits have emerged. A brighter future is on the horizon.

References:

Green Hydrogen – A New Fuel of the Future

India is witnessing the multitude of benefits of renewable energy, including increased access to electricity, reduced local air pollution and carbon dioxide emissions, and lower energy imports. There are easy ways to boost renewable energy’s position in the grid as well as end-use industries like transportation and industrial. Nonetheless, there remain economic, technological, and feasibility challenges to fully electrifying all existing energy usage, limiting the extent to which renewable power may directly replace fossil fuels. Hydrogen is already widely employed, particularly as an industrial feedstock in the production of ammonia-based fertilizers. Most of the hydrogen is produced through methane reforming, which results in large carbon dioxide emissions. Carbon capture and storage (CCS) technologies can collect these emissions, but they are yet undeveloped in India.

Hydrogen produced using electrolysis powered by renewable energy—green hydrogen—and its use in fuel cells has a long history of promising a pathway to a global clean energy economy yet failing to deliver. Electrolysis, where water (H2O) is split into its component parts using electricity, is an alternate means of processing. While there is important research activity on electrolysis, photolysis and biogenic hydrogen production methods, these low-carbon emission technologies have not yet been implemented on a scale. This is partially due to today’s low-carbon hydrogen production costs that are higher than fossil fuel-based hydrogen or other fossil-fuel alternatives. However, it is possible that these costs could achieve equilibrium in the future with green hydrogen in desirable regions undercutting grey hydrogen. This is made more possible in India, where tariffs on renewable energy are already among the lowest in the world and natural gas supplies are low and expensive. The capital cost of electrolysers, along with energy costs, is another significant factor for reducing the cost of green hydrogen. With a ramp-up in implementation, these are likely to continue to decline, since most electrolysers are produced on a relatively small scale today.

Fresh water resources make up around 2.5 percent of the total amount of water on the planet. As shown in figure 1, fortunately, the accessible seawater resource is 39 times that of fresh water. Water use due to electrolysis should, however, not be viewed as gradually using up the water resource, because when green hydrogen is oxidized (by combustion or via a fuel cell) it yields the same amount of water as was originally electrolyzed. This may enter the atmosphere as water vapor or be condensed at the point of use and recovered as liquid water. Moreover, the production of green hydrogen simultaneously produces oxygen in the exact amount required to oxidize the hydrogen, this is an important characteristic, because atmospheric oxygen depletion is contributing to global warming. 

Figure 1: Annual water requirement of Green Hydrogen production relative to                 Earth’s water resources. [Source: https://www.sciencedirect.com/science/article/pii/S1464285921006581]
Figure 1: Annual water requirement of Green Hydrogen production relative to Earth’s water resources.
[Source: https://www.sciencedirect.com/science/article/pii/S1464285921006581]

Green hydrogen provides India with major opportunities to grow into a new field of renewable energy technology, building domestic manufacturing expertise to supply the Indian market as well as overseas. Electrolysers would be the principal technology of significance. There are currently no major Indian producers of this technology, with electrolysers being imported from Germany, Norwegian or Japanese companies currently in use in India.

Globally, the momentum for hydrogen and fuel cell technology is rising, with market forecasts ranging from $2.5 trillion to $11.7 trillion by 2050. India has the capacity to manufacture more than its domestic demand, large quantities of low-cost, low green hydrogen. Significant economic value could be produced by exploiting the country’s diverse range of hydrogen production feedstocks to produce hydrogen for export. To manufacture hydrogen for sale, India has many strategic advantages, as depicted in the figure 2 below:

Figure 2: Strategic Advantages of Green Hydrogen in India; Source: Self-evaluation
Figure 2: Strategic Advantages of Green Hydrogen in India; Source: Self-evaluation

Green hydrogen is therefore widely viewed as the ‘net zero’ fuel for our future energy system, with green oxygen replenishing the associated consumption of atmospheric oxygen. However, it should be noted that some of the hydrogen will be required as a feedstock (e.g., for ammonia and methanol production) rather than as a fuel, and some of the green oxygen will be applied to industrial processes and water oxygenation as opposed to being vented to the atmosphere. For instance, hydrogen and nitrogen will be carried into plants in the form of ammonium, and oxygen will be used by the steel industry. It is therefore important to identify synergies between the electrolysers’ need for water and the use of both green hydrogen and oxygen, because these could accelerate the deployment of electrolysis in the limited period, we have left to combat climate change.

As a result, green hydrogen and its derivatives are projected to play a crucial role in global decarbonization at scale due to their adaptability, which allows them to be used in a variety of applications and decarbonizes hard-to-abate sectors.

MONKEYPOX – A THREATENING RECURRENCE OF A FORGOTTEN AILMENT

On 23rd May 2022, the world stood alarmed once again, when the increasing number of cases of the rare Monkeypox infections were reported to stand at 131 from 18 non-endemic countries, although there has been no recent associated death.

The Monkeypox virus (MPXV) which belongs to the Orthopoxvirus genus of the Poxviridae family is made up of double-stranded DNA and is zoonotic in nature. Due to its maintenance in the wild animal population, it is far less sensitive to common eradication methods.  Certain risk factors associated with MPXV infection include increase in geographical range and cessation of vaccination of the host. Environmental factors like increasing risk of animal-host transmission and frequency of contact with potential host may also contribute to viral transmission.

Back in 1958, the MPXV was first identified as a member of the Orthopoxvirus genus by the State Serum Institute in Copenhagen, Denmark. It was isolated first from vesiculo-pustular lesions of infected cynomolgus macaques. In 1970, first human infection was detected in the remote area of Democratic Republic of Congo. 6 deaths were reported in 1996 along with 71 clinical cases. In 2003, first case of MPX in the USA was initiated by exotic pets imported from Ghana. Reemergence of MPXV occurred in 2017 in Nigeria after 39 years of no reported case. In 2018, 3 individual patients were diagnosed with MPX in the UK.

MPXV originated from progenitor pox virus and shares similarities with the variola virus. It has two origins, one of which is the West African variant, exhibiting lower virulence and are less transmissible to humans. The only few cases were reported from certain West African nations. The other strain originates from Central African which prohibits inflammatory cytokine production in infected patients by preventing T-cell receptor-mediated activation and hence is far more virulent.

Specimens for clinical diagnosis purposes include that from skin lesions and swabs. The dermis might exhibit papular lesions. Keratinocytes exhibit vasculitis and viral inclusions apart from spongiosis. Detection of immune responses to the presence of other OPXV makes serological testing unsuitable for MPXV diagnosis, although it may provide evidence of viral exposure.  Injection of anti-poxvirus antibodies into unvaccinated infected individual may aid in diagnosis of MPX. All cases from Nigeria, Singapore, UK and Israel were identified as West African MPXV using PCR and genetic sequencing.

Direct or indirect contact with infected animals (live or dead), for e.g. hunting of small animals for food is the main cause for the transmission of virus in humans, while in animals, aerosol transmission has been detected. Due to increase in T-cell response and production of antiviral antibodies during the course of infection, the development of highly-sensitive diagnostic techniques may help cure patients faster.

The impact of the existing smallpox vaccine on MPXV infections will play an important role in the prevention of the disease, due to concerns regarding its adverse effects in an immunocompromised population. Till now, the Modified vaccinia Ankara (MVA) has been found to confer protection against lethal doses of MPXV except for cases in which severely diminished T-cell protection has been observed in the primates.

Contrasting SARS-COV2 MPXV which spreads though aerosols and is more contagious, MPXV spreads though contact and is less contagious. Nevertheless, an extended chain of person-to-person transmission of monkeypox in the Democratic Republic of Congo is an indication of the potential of the virus to infect immunocompromised individuals, which may cause its evolution and independent maintenance in the human population. Groups of population including pregnant women and immunocompromised persons are at higher risk of getting infected. Due to diversity of taxa supporting MPXV replication, more species of animals are prone to the risk of viral infection. Although, there is a lack of information regarding the species causing the viral transmission, certain approaches may be useful in detecting and better understanding the origin, transmission and risk factors of MPXV. These include predictive risk modelling across different landscapes and scales, theoretical mathematical modelling studies, population genetic studies, ecologic risk mapping studies and surveys.

Know the Game: Augment your career with Skills, Competencies, and Expertise in the niche segment of Health Geo-Informatics

The WHO has taken pledge to help countries and partners in making informed public health choices more quickly and to spread geospatial knowledge throughout the organization by connecting maps, apps, data, and people. Because of this change in emphasis, organizations all around the world are depending more and more on location intelligence to make smarter public health decisions. Human services and health geoinformatics occupations are in greater demand than ever.

John Snow’s ground-breaking work serves as an example of the effectiveness of mapping and geographic systems in addressing the cholera pandemic. The World Health Organization (WHO) has a long history of analyzing spatial distribution and risk factor patterns, identifying, preventing, and controlling diseases, and enhancing the effectiveness of public health initiatives. Making timely and trustworthy judgments that have the potential to save many lives is made possible by using GIS to connect spatial representation and public health planning. To name a few, 15 of the 17 health-related SDGs rely on GIS, for example, by monitoring air, water quality, and sanitation, neglected tropical diseases (malaria, guinea worm, snake bites), Polio, as well as health emergencies. Geoinformatics is defined as an academic discipline or career of working with geographical data for better understanding and interpretation of human interaction with the earth’s surface. It encompasses several technologies, approaches, processes, and methods to interpret and discourse spatial questions that necessitate spatial sense to address it. ESRI comments that “Hundreds of thousands of organizations in virtually every field are using GIS to make maps that communicate, perform analysis, share information, and solve complex problems around the world. This is changing the way the world works.”

Geoinformatics – Future Science
Figure 1. Geoinformatics – Future Science (Conceptualized and compiled by Dr. Anu Rai)

With its underlying capacity, Geoinformatics is emerging as a billion-dollar industry and offers lucrative opportunities to its professionals and trainers. In order to promote better public health planning and decision-making, geospatial technology, namely Health Geoinformatics, offers spatial representation of data. It is a niche segment of Geoinformatics and has significant uses in the fields of medicine and global health, but many nations currently limited or no access to these advantages in order to improve their health information systems. However, in post pandemic era, WHO and partner countries aggressively acknowledge and recommend the application of Geoinformatics in addressing public health issues.  WHO has taken pledge to help countries and partners in making informed public health choices more quickly and to spread geospatial knowledge throughout the organization by connecting maps, apps, data, and people. The WHO GIS Centre for Health wants to have a direct and long-lasting influence on the public by increasing its engagement with partners. Supporting geospatial data and analytics to enhance adherence and stewardship with WHO Standard Operating Procedures for maps and Web GIS applications are a few examples of the specific services offered by WHO. The purpose of such services is to improve national, regional, and analytical data as well as the health information system in order to boost the Member States’ and Partners’ effective use of GIS. Because of this change in emphasis, organizations all around the world are depending more and more on location intelligence to make smarter public health decisions. Human services and health geoinformatics occupations are in greater demand than ever. In order to forecast and evaluate industry trends utilizing a range of data and pro-actively build solutions and messaging to address important issues, drivers, and challenges, health GIS analysts or public health solution managers work closely with teams in varied domains of public health, human services, hospitals, insurance, managed health care systems, and environmental health. Despite corporate and public jobs and entrepreneurial opportunities, GIS analysts are highly engaged in investigating, understanding, and developing new businesses in areas underserved or not currently served with GIS applications in the health and human services space. This creates a new field of opportunity for work with product development as a customer advocate for the requirements of the health and human services sector.

In my academic career as an educator of Geography and Geoinformatics, I have often noticed curiosity among youngsters about career opportunities with the Health Geography and Geoinformatics, irrespective of the discipline and domain of undergraduate and postgraduate degrees they hold. I would answer that if you are interested to play with the nuts and bolts of spatial health science, the Post Graduate Program on Geography and Geoinformatics is a good option for you. You may select diverse fields of Health Geoinformatics depending on the expertise of the domain varying from map making to app development. You can also opt for jobs in Public Health firms that include diverse skill-based jobs in the field of marketing development and testing and even entrepreneurship. Research-based course experience also opens huge job prospects in development and planning commission, scientists in HRD, and other research institutions in India and abroad. Application of neo-geographical tools, statistical algorithms, machine learning, multi-criterion decision-making techniques, computer-programming, SQLs, text-analytics and learning and practices of GIS and statistical packages that enable GI Scientists to solve the multifaceted real-life problem has opened extensive career opportunities to practitioners of geoinformatics in the field of public health data science as well. Health data scientists, data analysts, big data analysts, spatial data analysts, etc. are some of the lucrative jobs paying high salary packages to deserving candidates. So, if spatial logic of health attracts you, Health Geoinformatics is the best option to augment your career with skills, competencies, and expertise.

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