New Haven (Connecticut): According to a new study, a machine learning approach can assess risk factors and predict the later development of conduct disorder (CD) in children with high accuracy.The study was published in the journal, 'Biological Psychiatry: Cognitive Neuroscience and Neuroimaging'.Conduct disorder (CD) is a common yet complex psychiatric disorder featuring aggressive and destructive behaviour. Factors contributing to the development of CD span biological, psychological, and social domains. Researchers have identified a myriad of risk factors that could help predict CD, but they are often considered in isolation.The researchers used baseline data from over 2,300 children aged 9 to 10 enrolled in the Adolescent Brain Cognitive Development (ABCD) Study, a longitudinal study following the biopsychosocial development of children. The researchers "trained" their machine-learning model using previously identified risk factors from across multiple biopsychosocial domains. For example, measures included brain imaging (biological), cognitive abilities (psychological), and family characteristics (social). The model correctly predicted the development of CD two years later with over 90 per cent accuracy.Cameron Carter, MD, Editor of Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, said of the study, "These striking results using task-based functional MRI to investigate the function of the reward system suggest that risk for later depression in children of depressed mothers may depend more on mothers' responses to their children's emotional behaviour than on the mother's mood per se."The ability to accurately predicted who might develop CD would aid researchers and healthcare workers in designing interventions for at-risk youth with the potential to minimize or even prevent the harmful effects of CD on children and their families."Findings from our study highlight the added value of combining neural, social, and psychological factors to predict conduct disorder, a burdensome psychiatric problem in youth," said senior author Arielle Baskin-Sommers, PhD at Yale University."These findings offer promise for developing more precise identification and intervention approaches that consider the multiple factors that contribute to this disorder. They also highlight the utility of leveraging large, open-access datasets, such as ABCD, that collect measures about the individual across levels of analysis," she concluded.&nbsp;—ANI

According to a new study, a machine learning approach can assess risk factors and predict the later development of conduct disorder (CD) in children with high accuracy.

Scientists Use Machine-Learning Approach To Predict Risk Factors Of Conduct Disorder In Kids

New Delhi (The Hawk):&nbsp;Researchers have developed smart IoT-based machine for welding ferrous tubes faster than conventional fusion welding or solid-state processes presently used with less consumption of energy. As manufacturing industries move toward advanced technologies, there is a requirement to minimise energy consumption and automate the welding process to avoid human-induced errors and also manufacture products swiftly in an eco-friendly manner.Dr. S. Arungalai Vendan, Professor, Electronics, and Communication, School of Engineering, Dayananda Sagar University, Bangalore developed the Internet of Things (IoT) integrated machine titled “Magnetically Impelled Arc Butt Welding Equipment" embedded with sensors for sound, vibration, arc light intensity, temperature as well as smoke, along with processors for abstracting data for predicting the quality of the welding.&nbsp;The low-cost IoT integrated machine was supported by the Department of Science and Technology, Dr. Vendan who obtained his Ph.D. in MIAB welding explored the process at Welding Research Institute, Bharat Heavy Electrical Limited, Tiruchirappalli, India for pressure part applications. Observing the huge potential of adopting the process for various industrial applications to join ferrous tubes, the investigator came up with the idea of developing a low-cost IoT integrated MIAB machine for joining ferrous tubes.&nbsp;Magnetically Impelled Arc Butt (MIAB) welding involves striking of an arc between two coaxially placed tubes, followed by interaction of the axial component of arc current and radial component of a magnetic field that causes a force called Lorentz force. This force acts on the arc and impels it around the joint line with an approximate linear speed of 200m/s that uniformly heats the tube surfaces upto the highest temperature at which it is solid (solidus temperature). The softened tube edges (butt ends) are then forced into penetration by forging to form a weld.The equipment developed is customized for welding mild steel/ low carbon steel tubes for 3 outer diameters -- 21.5mm, 22.5mm and 27 mm respectively with 2-3 mm thicknesses which are typically employed in automotive and structural applications. The scientists are in the process of establishing new equations for two dependent parameters-- arc velocity and arc rotational sound, based on which an approximate prediction can be made about the welding.

Researchers have developed smart IoT-based machine for welding ferrous tubes faster than conventional fusion welding or solid-state processes presently used with less consumption of energy. As manufacturing industries move toward advanced technologies, there is a requirement to minimise energy consumption and automate the welding process to avoid human-induced errors and also manufacture products swiftly in an eco-friendly manner.

New Smart Machine For Making Welding Operations Faster, Energy-Efficient And Eco-Friendly

Researchers have developed smart IoT-based machine for welding ferrous tubes faster than conventional fusion welding or solid-state processes presently used with less consumption of energy. As manufacturing industries move toward advanced technologies, there is a requirement to minimise energy consumption and automate the welding process to avoid human-induced errors and also manufacture products swiftly in an eco-friendly manner.





New Delhi (The Hawk): Scientists have used Machine learning to develop a design map of alloys at the nanoscale which can help predict the match of pairs of metals that can form bimetallic nanoalloys.These nano alloys, also called core-shell nanocluster alloys, in which one metal forms the core and another stays on the surface as a shell, are a new frontier in the quest of scientists for new materials and have applications in biomedicine and other areas.It is important to know under what conditions core-shell structures are formed in the nanocluster alloys and which metal forms the core, and which stays on the surface as a shell. A number of factors like cohesive energy difference, atomic radius difference, surface energy difference and electronegativity of the two atoms may play a part in the core and shell preference of the atoms.The periodic table has 95 metals of different categories ranging from alkalis to alkaline earth, which can potentially form 4465 pairs. It is experimentally impossible to determine how they behave in forming nanocluster alloys. But computers can be programmed to predict the behaviour of these pairs and more through ‘machine learning’. The machine is taught to recognise patterns by feeding in a number of patterns with well-defined attributes. The more the data fed into the computer, the more accurate will be the recognition of an unknown data by the computer.However, scientists faced a stumbling block here because of the limited number of experimentally synthesised binary nanoclusters with clear identification of the chemical ordering of constituents, and few core−shell combinations studied theoretically. Machine Learning could not be applied with confidence on small data set of sizes less than or around 100.Researchers at the S N Bose Centre for Basic Sciences, an autonomous institute of the Department of Science and Technology, circumvented this problem by calculating the Surface-to-core relative energy on a variety of possible binary combinations of alkali metals, alkaline earth, basic metals, transition metals and p-block metals to create a large data-set of 903 binary combinations.In their paper published in the&nbsp;Journal of Physical Chemistry,&nbsp;they investigated the&nbsp;key attributes driving the core−shell morphology using the statistical tool of machine learning applied on this large data set. Core-shell structures with lighter metals having lower atomic numbers in the core were classified as Type 1, and those having the heavier metals in the core were classified as Type 2. A number of attributes were built to characterise each data point in the set. The performance of the ML model was tallied with existing experimental data, and the ML model was proved to be reliable.Having thus established confidence in the ML model, the dominant attributes driving the core-shell pattern were now analysed. It was found that the relative importance of the key factors depends on the subset combinations like alkali metal- alkaline earth, transition metal–transition metal etc. It was also found that if the difference in the cohesive energies between the two types of atoms is very small, the nanoclusters constitute a random mix of both the metals, and if the difference in the cohesive energies is very large, the atoms get segregated into a structure having two faces with one face of A atoms and another face of B atoms called the Janus structure named after two-faced Greek God.Thus the attempt to connect ML with nanoscience was successful in tracing the mixing patterns of metal atoms in nanoclusters and formed a basis for the design map, which can help select the pairs of metals for nanocluster alloys. This design map developed by the scientists will be tested out in the nano laboratories at the Moscow State University and also at the S.N Bose Centre.Another domain of study for the S.N Bose team has been the heterogeneous structure formed at the junction of two dissimilar semiconductors. They have established that using machine learning, hetero-structure types used in hetero-junctions of two semiconductors which are at the heart of devices like LEDs, solar cells and photovoltaic devices, can be predicted fairly accurately.The ML model designed by the S.N Bose team predicted 872 unknown semiconductor hetero-structures of type 2 where the electrons and holes align themselves in A semiconductor and B semiconductor, respectively, giving rise to a desirable hetero-structure for semiconductor gadgets.S.N Bose Centre has used machine learning to search for cheaper substitutes of naturally occurring rare earth material. Rare earth compounds with permanent magnetic properties are used in loudspeakers and computer hard drives.&nbsp;Of these,&nbsp;17 elements of the periodic table like Neodymium, Lanthanum and so on are found sparsely on the earth’s crust, and their supply is monopolised by the countries where their mines happen to be located. By painstakingly creating a database of rare earth compounds and their attributes and then constructing a machine-learning model, they have predicted a list of potential candidates for permanent magnets whose cost will be less than $100 per Kg.This work carried out through the ‘National Supercomputing Mission’ has added a whole new drive to humankind’s quest for new material.&nbsp;<img src="https://static.pib.gov.in/WriteReadData/userfiles/image/image002R39A.jpg">&nbsp;

Scientists have used Machine learning to develop a design map of alloys at the nanoscale which can help predict the match of pairs of metals that can form bimetallic nanoalloys.

Machine learning helps predict new materials for nano alloys, semiconductors & rare earths

Houston: Chemists have demonstrated that light-activated molecular machines can drill holes through gram-negative and gram-positive bacteria membranes, killing them in as little as two minutes. Their study suggests a new way to combat antibiotic-resistant bacteria, which lack natural defences against mechanical intruders. The study has been published in the journal, "Science Advances, 2022" The latest iteration of nanoscale drills developed at Rice University is activated by visible light rather than ultraviolet (UV), as in earlier versions. These have also proven effective at killing bacteria through tests on real infections.Six variants of molecular machines were successfully tested by Rice chemist James Tour and his team. All of them punched holes in the membranes of gram-negative and gram-positive bacteria in as little as two minutes. Resistance was futile for bacteria that have no natural defences against mechanical invaders. That means they are unlikely to develop resistance, potentially offering a strategy to defeat bacteria that have become immune to standard antibacterial treatments over time. "I tell students that when they are my age, antibiotic-resistant bacteria are going to make COVID look like a walk in the park," Tour said. "Antibiotics won't be able to keep 10 million people a year from dying of bacterial infections. But this really stops them." Because extended exposure to UV can be damaging to humans, the Rice lab has been refining its molecules for years. The new version gets its energy from still-blueish light at 405 nanometers, spinning the molecules' rotors at 2 to 3 million times per second. It's been suggested by other researchers that light at that wavelength has mild antibacterial properties of its own, but the addition of molecular machines supercharges it, said Tour, who suggested bacterial infections like those suffered by burn victims and people with gangrene will be early targets.The machines are based on Nobel Prize-winning work by Bernard Feringa, who developed the first molecule with a rotor in 1999 and got the rotor to spin reliably in one direction. Tour and his team introduced their advanced drills in a 2017 Nature paper. The Rice lab's first tests of the new molecules on burn wound infection models confirmed their ability to quickly kill bacteria, including methicillin-resistant Staphylococcus aureus, a common cause of skin and soft tissue infections that was responsible for more than 100,000 deaths in 2019. The team achieved visible light activation by adding a nitrogen group. "The molecules were further modified with different amines in either the stator (stationary) or the rotor portion of the molecule to promote the association between the protonated amines of the machines and the negatively charged bacterial membrane," said Liu, now a scientist at Arcus Biosciences in California.The researchers also found the machines effectively break up biofilms and persister cells, which become dormant to avoid antibacterial drugs. "Even if an antibiotic kills most of a colony, there are often a few persister cells that for some reason don't die," Tour said. "But that doesn't matter to the drills." As with earlier versions, the new machines also promise to revive antibacterial drugs considered ineffective. "Drilling through the microorganisms' membranes allows otherwise ineffective drugs to enter cells and overcome the bug's intrinsic or acquired resistance to antibiotics," said Santos, who's on the third year of the postdoctoral global fellowship that brought her to Rice for two years and is continuing at the Health Research Institute of the Balearic Islands in Palma, Spain.The lab is working toward better targeting bacteria to minimize damage to mammalian cells by linking bacteria-specific peptide tags to the drills to direct them toward pathogens of interest. "But even without that, the peptide can be applied to a site of bacterial concentration, like in a burn wound area," Santos said.—ANI

Chemists have demonstrated that light-activated molecular machines can drill holes through gram-negative and gram-positive bacteria membranes, killing them in as little as two minutes. 

To treat infections, visible light activates molecular machineries: Study

Houston (Texas): Chemists have demonstrated that light-activated molecular machines can drill holes through gram-negative and gram-positive bacteria membranes, killing them in as little as two minutes. Their study suggests a new way to combat antibiotic-resistant bacteria, which lack natural defences against mechanical intruders.The study has been published in the journal, "Science Advances, 2022"The latest iteration of nanoscale drills developed at Rice University is activated by visible light rather than ultraviolet (UV), as in earlier versions. These have also proven effective at killing bacteria through tests on real infections.Six variants of molecular machines were successfully tested by Rice chemist James Tour and his team. All of them punched holes in the membranes of gram-negative and gram-positive bacteria in as little as two minutes. Resistance was futile for bacteria that have no natural defences against mechanical invaders. That means they are unlikely to develop resistance, potentially offering a strategy to defeat bacteria that have become immune to standard antibacterial treatments over time."I tell students that when they are my age, antibiotic-resistant bacteria are going to make COVID look like a walk in the park," Tour said. "Antibiotics won't be able to keep 10 million people a year from dying of bacterial infections. But this really stops them."Because extended exposure to UV can be damaging to humans, the Rice lab has been refining its molecules for years. The new version gets its energy from still-blueish light at 405 nanometers, spinning the molecules' rotors at 2 to 3 million times per second. It's been suggested by other researchers that light at that wavelength has mild antibacterial properties of its own, but the addition of molecular machines supercharges it, said Tour, who suggested bacterial infections like those suffered by burn victims and people with gangrene will be early targets. The machines are based on Nobel Prize-winning work by Bernard Feringa, who developed the first molecule with a rotor in 1999 and got the rotor to spin reliably in one direction. Tour and his team introduced their advanced drills in a 2017 Nature paper.The Rice lab's first tests of the new molecules on burn wound infection models confirmed their ability to quickly kill bacteria, including methicillin-resistant Staphylococcus aureus, a common cause of skin and soft tissue infections that was responsible for more than 100,000 deaths in 2019.The team achieved visible light activation by adding a nitrogen group. "The molecules were further modified with different amines in either the stator (stationary) or the rotor portion of the molecule to promote the association between the protonated amines of the machines and the negatively charged bacterial membrane," said Liu, now a scientist at Arcus Biosciences in California.The researchers also found the machines effectively break up biofilms and persister cells, which become dormant to avoid antibacterial drugs."Even if an antibiotic kills most of a colony, there are often a few persister cells that for some reason don't die," Tour said. "But that doesn't matter to the drills."As with earlier versions, the new machines also promise to revive antibacterial drugs considered ineffective. "Drilling through the microorganisms' membranes allows otherwise ineffective drugs to enter cells and overcome the bug's intrinsic or acquired resistance to antibiotics," said Santos, who's on the third year of the postdoctoral global fellowship that brought her to Rice for two years and is continuing at the Health Research Institute of the Balearic Islands in Palma, Spain. The lab is working toward better targeting bacteria to minimize damage to mammalian cells by linking bacteria-specific peptide tags to the drills to direct them toward pathogens of interest. "But even without that, the peptide can be applied to a site of bacterial concentration, like in a burn wound area," Santos said.&nbsp;—ANI

 Chemists have demonstrated that light-activated molecular machines can drill holes through gram-negative and gram-positive bacteria membranes, killing them in as little as two minutes.

To Treat Infections, Visible Light Activates Molecular Machineries: Study

Chemists have demonstrated that light-activated molecular machines can drill holes through gram-negative and gram-positive bacteria membranes, killing them in as little as two minutes.

Kabul: The Taliban-led government in Afghanistan announced that the World Health Organization (WHO) will provide monkeypox test kits to the the war-torn nation as the virus has been confirmed in 27 countries with nearly 800 cases.According to officials from the Ministry of Public Health (MoPH), the Afghan health sector currently lacks kits to test for monkeypox, reports TOLO News. "PCR machines were handed over to the MoPH during the outbreak of Covid-19 in Afghanistan. These machines cannot be used to test for monkeypox," said Javid Hazhir, a Ministry spokesman. So far, Afghanistan has not reported any monkeypox cases. In its latest report on Sunday, the WHO said the 780 laboratory confirmed cases of monkeypox from 27 countries represented an increase of 523 cases (+203 per cent) since May 29, when a total of 257 cases were reported.However, there have been no deaths associated with the current monkeypox outbreak. Monkeypox is a sylvatic zoonosis that may cause infections in humans and the disease usually occurs in forested parts of Central and West Africa. It is caused by the monkeypox virus which belongs to the orthopoxvirus family, according to the WHO.—IANS

The Taliban-led government in Afghanistan announced that the World Health Organization (WHO) will provide monkeypox test kits to the the war-torn nation as the virus has been confirmed in 27 countries with nearly 800 cases.

Afghanistan to receive monkeypox test kits from WHO

New Delhi: The Congress is gearing up for Assembly  polls this year in Gujarat and Himachal Pradesh. Till the 2024 general elections, there are elections in Karnataka, MP, Rajasthan and Chhattisgarh in 2023.
In Gujarat and Rajasthan all the Lok Sabha MPs were elected on a BJP ticket and the Congress was wiped out, while from Karnataka, Madhya Pradesh, Himachal and Chhattisgarh the Congress presence in the Lok Sabha is very low so the state elections are crucial for the Congress till 2023.
For the Assembly elections in Gujarat and Himachal Pradesh, the Congress has appointed senior observers for both the states. Rajasthan Chief Minister Ashok Gehlot has been appointed a senior observer in Gujarat and Bhupesh Baghel, Chhattisgarh Chief Minister, will look after Himachal Pradesh.
Gehlot will be assisted by T.S. Singh Deo, a minister in Chhattisgarh and Milind Deora, former Mumbai Congress chief. Baghel will be helped by former Deputy Chief Minister of Rajasthan Sachin Pilot and Punjab Congress legislative party leader Partap Singh Bajwa. Both the states go to the polls this year.
State in-charges of both the states, Raghu Sharma of Gujarat and Rajeev Shukla of Himachal Pradesh, have been asked to give more time to the states.
Recently, the Congress appointed seven working presidents for its Gujarat unit. Following a social engineering strategy, each of these leaders represents a caste. The Congress is also attempting to send a message to upper caste voters that the party is trying to rise above its dedicated SC/ST/OBC vote bank and cares for them too.
The central Congress leadership in Delhi has asked its Gujarat unit to refrain from making personal attacks on Prime Minister Narendra Modi but to raise people's issues and target BJP policies in the run-up to the Assembly polls, sources said.
The party will organise "Mehangai Chaupal" interactive meetings at mandis, retail markets and other locations in all assembly constituencies from August 17 to 23.
The party will print booklets and will distribute them to all state organisations and they will then translate and print them in the local language and distribute them to the people.
The Congress task force has met the Gujarat leaders several times and asked them to prepare unitedly for the Assembly polls to dethrone the BJP which has been ruling the state for the past 27 years. As part of the strategy, the party will highlight the state government's failure particularly during Covid and post-Covid.
Notably, the Congress has witnessed some high profile exits in the recent past besides suffering a setback in local body elections. Hardik Patel, who had spearheaded the Patidar protest, has changed loyalties and joined the BJP. In the last Assembly polls, the party won 77 seats but many MLAs have switched sides since then.
The Gujarat Congress had won a record breaking 149 seats with a 55.55 per cent vote share in the 1985 Assembly elections, while the BJP could bag only 11 seats with a 14.96 per cent vote share.
In the 2012 elections, the Congress's vote share declined to 38.93 per cent, whereas the BJP's vote share jumped to 47.85 per cent.
The Aam Aadmi Party's threat to the Congress has also been figuring in the discussions, the Congress is trying hard not to let its vote bank be weaned away by the AAP. Congress state in-charge Raghu Sharma says there is no threat from the AAP and attacked the state government over unemployment and inflation. "Recently in Gondal a youth committed suicide, there are 5 lakh vacancies in the state but the government is not starting any recruitment process," he says.
The Congress wants to focus on people-centric issues and it is focusing on inflation and unemployment as big political issues. In early 2023 the Congress will face elections in Karnataka.  Recently Congress leader Rahul Gandhi visited the state on party leader Siddaramaiah's birthday and asked the faction led  by DK Sivakumar to work jointly.
In MP the Congress is in the opposition. In Rajasthan and Chhattisgarh the party is in power; in Madhya Pradesh Kamal Nath and Digvijaya Singh are working in tandem but in Rajasthan the issue of Chief Ministership is being raked up by Sachin Pilot who is a claimant for the top post and in Chhattisgarh the TS Singh Deo issue has not been settled. Sources close to him say that, "the high command should decide either way and settle the issue."
—IANS

The Congress is gearing up for Assembly  polls this year in Gujarat and Himachal Pradesh. Till the 2024 general elections, there are elections in Karnataka, MP, Rajasthan and Chhattisgarh in 2023.

 Cong cranks up its election machinery for crucial tests ahead

New Delhi (The Hawk): With India becoming a food surplus country, the Indian farmer needs affordable machinery and technologies to expand production and come up with value-added products with export potential, said Sushri Shobha Karandlaje, Union Minister of State for Agriculture and Farmers Welfare, at the 7th International Exhibition and Conference EIMA Agrimach India 2022. Sushri Shobha Karandlaje, accompanied by Shri Murugesh R Nirani, Minister of Large and Medium Industries, and Shri Muniratna, Minister for Horticulture and Planning &amp; Statistics, Government of Karnataka, inaugurated the three-day conference cum exhibition in Benguluru yesterday.
Speaking on the occasion, MoS Karandlaje encouraged equipment manufacturers and technology developers to manufacture food processing machinery to check the rampant wastage of agriculture and horticulture produce in the absence of value addition. She said that instead of wasting, the food could be exported to nations with limited food production avenues. Sushri Karandlaje said, "what the country needs now is affordable and quality food processing, agri-marketing and agri-export avenues." She also noted that with 2023 being the 'International Year Of Millets', India could step up exports as the country is among the leading producers of millets. In his address, Shri Murugesh R Nirani said that increased efforts were needed for technology improvement, adoption, and exports. In addition, the minister encouraged foreign industry participants to introduce affordable mechanised farming, given the small land holdings in the state.
EIMA Agrimach India 2022, running in its 7th edition, is being organised for the first time in Bengaluru. The event has registered participants from more than 40 countries. Over three days, more than 10,000 farmers, industry participants, foreign delegates, investors, agriculture researchers, and students would visit the exhibition and conference.

With India becoming a food surplus country, the Indian farmer needs affordable machinery and technologies to expand production and come up with value-added products with export potential, said Sushri Shobha Karandlaje, Union Minister of State for Agriculture and Farmers Welfare, at the 7th International Exhibition and Conference EIMA Agrimach India 2022. Sushri Shobha Karandlaje, accompanied by Shri Murugesh R Nirani, Minister of Large and Medium Industries, and Shri Muniratna, Minister for Horticulture and Planning & Statistics, Government of Karnataka, inaugurated the three-day conference cum exhibition in Benguluru yesterday.

India Needs Machinery & Technologies For Small & Marginal Farmers: Minister 

New Delhi: Google has announced to soon allow people to translate news coverage in other languages directly from Search via machine translation.
Currently, people see Search results about news in their countries in their preferred language.
"In early 2023, we'll launch a new feature that will give people a simple way to find translated news coverage using machine translation," said the company.
To begin with, the feature will translate news results in French, German and Spanish into English on mobile and desktop, and will be expanded to other languages later.
"You'll be able to read authoritative reporting from journalists in the country, giving you a unique perspective of what's happening there," Google said in a blog post late on Wednesday.
The new Google Search tool feature connects readers looking for international news to relevant local reporting in other languages, giving them access to more complete on-the-ground coverage.
The company also announced another feature that will help people find out what others are saying in online discussions and forums across the web.
"Starting today, a new feature will appear when you search for something that might benefit from the diverse personal experiences found in online discussions," said the company.
The new feature, called 'Discussions and forums', will include helpful content from a variety of popular forums and online discussions across the web.
This feature has been rolled out for English users on mobile in the US, said Google.&nbsp;
—IANS

Google has announced to soon allow people to translate news coverage in other languages directly from Search via machine translation.

 Google to soon allow people to translate local news directly in Search

New Delhi: Indian Institute of Technology (IIT) Mandi and National Skill Development Corporation (NSDC) have introduced a Certificate and an Advanced Certificate programme in the fast growing domain of Data Science and Machine Learning.
The certificate programme will be completed over a period of six months and the advanced certificate programme will be covered in nine months and is scheduled to start in the first week of November, 2022.
The courses will be run through live-streaming sessions conducted by the faculty members of Mandi. Interested candidates will be selected on the basis of an eligibility test which will be held on October 15 and 16. On completion of the course, programme certificate will be issued by IIT Mandi and NSDC collectively. More details about the same can be obtained from the website of IIT Mandi.
Describing the new courses, Prof Tushar Jain, Head, Centre for Continuing Education (CCE) said : "The global demand for data science and machine learning experts is growing rapidly. The certificate programmes being launched by IIT Mandi are designed in such a way to provide skills in demand by industries all over the world," adding, "In this era of skill development initiated by other IITs, we have adopted a new model, where students or working professionals will be given a unique opportunity to learn cutting-edge concepts in Data Science and Machine Learning like our B.Tech students. It will be highly beneficial for the students enrolled in these programmes to upgrade their skills as per the increasing demands of the industries."
The programme will involve live online sessions from IIT Mandi's faculty members and industry experts and will provide learners with expertise in machine learning, in building a strong foundation in data science and in data-driven decision making with Python. Learners of the course can further build their careers as data analysts, data scientists, business analysts, business intelligence professionals and consultants.
According to IIT Mandi, there is a growing demand for trained professionals who can collect, process and study large data sets and reveal underlying trends and other insights in the industry. As a result, the study of Data Science as a discipline has become essential to meet the growing needs and challenges of future. This online certification course taught by IIT Mandi professors aims to teach learners all fundamental and advanced skills in tools and technologies used in the fields of Data Science, Machine Learning, Deep Learning and Image Processing. -- IANS

 Indian Institute of Technology (IIT) Mandi and National Skill Development Corporation (NSDC) have introduced a Certificate and an Advanced Certificate programme in the fast growing domain of Data Science and Machine Learning.

'Data Science' And 'Machine Learning' At IIT Mandi

New Delhi: Most of the Opposition parties have decided to oppose the Election Commission's recommendation on remote electronic voting machine (RVM) as it is vague and not definite, senior Congress leader Digvijaya Singh said on Sunday.
Following a conference of Opposition parties, at which the heads of the Congress, JD(U), CPI, CPI(M), National Conference, and JMM were all present, he made these comments.
According to Singh, there are significant political flaws in the plan for remote voting machines, such as the unclear definition of migratory labourers.—Inputs from Agencies

Most of the Opposition parties have decided to oppose the Election Commission's recommendation on remote electronic voting machine (RVM) as it is vague and not definite, senior Congress leader Digvijaya Singh said on Sunday

Most opposition parties dispute EC's remote voting machine proposal: Digvijay Singh

Varanasi News: Four doctors from Varanasi have landed in jail for their involvement in the theft of advanced medical equipment worth over Rs 20 lakhs from a hospital to upgrade their establishments located in the city's outskirts.

The accuded took help of the nursing staff of a prominent hospital of the city to procure advanced BiPap, electrocardiography (ECG), arterial blood gas (ABG) analyser and infusions machines, stolen from a city hospital.

All the five, including the hospital staffer, have been arrested and sent to jail.

Police have seized 14 infusion machines with 10 cables, six BiPap, one ECG and one ABG machine.

The cost of the recovered equipment has been estimated as over Rs 20 lakh and all four doctors have been arrested said, Deputy Commissioner of Police Kashi zone, R.S. Gautam. IANS

Four Varanasi doctors were imprisoned for stealing advanced medical equipment worth over Rs 20 lakhs.

UP: 4 doctors arrested for theft of medical equipment

Chennai (The Hawk): Indian Institute of Technology Madras (IIT Madras) Researchers have developed a Machine Learning-based computational tool for better detection of cancer-causing tumours in the brain and spinal cord. Called ‘GBMDriver’ (GlioBlastoma Mutiforme Drivers), this tool is publicly available online. Glioblastoma is a fast and aggressively growing tumour in the brain and spinal cord. Although there has been research undertaken to understand this tumour, therapeutic options remain limited with an expected survival rate of less than two years from the initial diagnosis. It is important to evaluate the functional consequences of variants in proteins, which are involved in Glioblastoma to advance the therapeutic options for patients. However, functional validations to identify driver mutations (disease-causing mutations) from all the observed variants would be strenuous work. The GBMDriver was developed specifically to identify driver mutations and passenger mutations (passenger mutations are neutral mutations) in Glioblastoma. GBMDriver can be accessed using the following link - https://web.iitm.ac.in/bioinfo2/GBMDriver/index.html. In order to develop this web server, a variety of factors such as amino acid properties, di- and tri-peptide motifs, conservation scores, and Position Specific Scoring Matrices (PSSM) were taken into account. In this study, 9386 driver mutations and 8728 passenger mutations in glioblastoma were analysed. Driver mutations in glioblastoma were identified with an accuracy of 81.99 percent, in a blind set of 1809 mutants, which is better than existing computational methods. This method is completely dependent on protein sequence. This research was led by Prof. M. Michael Gromiha, Department of Biotechnology, IIT Madras. His team included Ms. Medha Pandey, PhD Student, IIT Madras and two IIT Madras alumni Dr. P. Anoosha currently in The Ohio State University, Columbus, U.S., and Dr. Dhanusha Yesudhas who is now at the National Institute of Health, U.S. Their findings were published in the reputed peer-reviewed journal Briefings in Bioinformatics (https://doi.org/10.1093/bib/bbac451). Explaining the key findings of their research, Prof. M. Michael Gromiha, Department of Biotechnology, IIT Madras, said, “We have identified the important amino acid features for identifying cancer-causing mutations and achieved the highest accuracy for distinguishing between driver and neutral mutations. We hope that this tool (GBMDriver) could help to prioritize driver mutations in glioblastoma and assist in identifying potential therapeutic targets, thus helping to develop drug design strategies.” The Key Applications of this research include: Ø The methodology and features are portable to apply for other diseases. Ø This method could serve as one of the important criteria for disease prognosis. Ø Valuable resource to identify mutation-specific drug targets to design therapeutic strategies. Ms. Medha Pandey, a PhD Student at IIT Madras, said, “Our method showed an accuracy and AUC of 73.59% and 0.82 respectively on 10-fold cross-validation and 81.99% and 0.87 in a blind set of 1809 mutants. We envisage that the present method is helpful to prioritize driver mutations in glioblastoma and assist in identifying therapeutic targets.”

Indian Institute of Technology Madras (IIT Madras) Researchers have developed a Machine Learning-based computational tool for better detection

IIT Madras Researchers Develop Machine Learning Tool To Detect Tumour In The Brain & Spinal Cord

Maryland (US): Researchers at Johns Hopkins University have created a technique that uses artificial intelligence to visualise and monitor changes in the strength of synapses, the junctions that allow nerve cells in the brain to communicate with one another, in living animals. The method, which is detailed in Nature Methods, should help researchers better understand how learning, ageing, injury, and disease affect these connections in human brains. "If you want to learn more about how an orchestra plays, you have to watch individual players over time, and this new method does that for synapses in the brains of living animals," says Dwight Bergles, Ph.D., the Diana Sylvestre and Charles Homcy Professor in the Solomon H. Snyder Department of Neuroscience at the Johns Hopkins University (JHU) School of Medicine. Bergles co-authored the study with colleagues Adam Charles, Ph.D., M.E., and Jeremias Sulam, Ph.D., both assistant professors in the biomedical engineering department, and Richard Huganir, Ph.D., Bloomberg Distinguished Professor at JHU and Director of the Solomon H. Snyder Department of Neuroscience. All four researchers are members of Johns Hopkins' Kavli Neuroscience Discovery Institute. Nerve cells transfer information from one cell to another by exchanging chemical messages at synapses ("junctions"). In the brain, the authors explain, different life experiences, such as exposure to new environments and learning skills, are thought to induce changes at synapses, strengthening or weakening these connections to allow learning and memory. Understanding how these minute changes occur across the trillions of synapses in our brains is a daunting challenge, but it is central to uncovering how the brain works when healthy and how it is altered by disease. To determine which synapses change during a particular life event, scientists have long sought better ways to visualize the shifting chemistry of synaptic messaging, necessitated by the high density of synapses in the brain and their small size -- traits that make them extremely hard to visualize even with new state-of-the-art microscopes. "We needed to go from challenging, blurry, noisy imaging data to extract the signal portions we need to see," Charles says. To do so, Bergles, Sulam, Charles, Huganir and their colleagues turned to machine learning, a computational framework that allows flexible development of automatic data processing tools. Machine learning has been successfully applied to many domains across biomedical imaging, and in this case, the scientists leveraged the approach to enhance the quality of images composed of thousands of synapses. Although it can be a powerful tool for automated detection, greatly surpassing human speeds, the system must first be "trained," teaching the algorithm what high quality images of synapses should look like. In these experiments, the researchers worked with genetically altered mice in which glutamate receptors -- the chemical sensors at synapses -- glowed green (fluoresced) when exposed to light. Because each receptor emits the same amount of light, the amount of fluorescence generated by a synapse in these mice is an indication of the number of synapses, and therefore its strength. As expected, imaging in the intact brain produced low quality pictures in which individual clusters of glutamate receptors at synapses were difficult to see clearly, let alone to be individually detected and tracked over time. To convert these into higher quality images, the scientists trained a machine learning algorithm with images taken of brain slices (ex vivo) derived from the same type of genetically altered mice. Because these images weren't from living animals, it was possible to produce much higher quality images using a different microscopy technique, as well as low quality images -- similar to those taken in live animals -- of the same views. This cross-modality data collection framework enabled the team to develop an enhancement algorithm that can produce higher resolution images from low quality ones, similar to the images collected from living mice. In this way, data collected from the intact brain can be significantly enhanced and able to detect and track individual synapses (in the thousands) during multiday experiments. To follow changes in receptors over time in living mice, the researchers then used microscopy to take repeated images of the same synapses in mice over several weeks. After capturing baseline images, the team placed the animals in a chamber with new sights, smells and tactile stimulation for a single five-minute period. They then imaged the same area of the brain every other day to see if and how the new stimuli had affected the number of glutamate receptors at synapses. Although the focus of the work was on developing a set of methods to analyze synapse level changes in many different contexts, the researchers found that this simple change in environment caused a spectrum of alterations in fluorescence across synapses in the cerebral cortex, indicating connections where the strength increased and others where it decreased, with a bias toward strengthening in animals exposed to the novel environment. The studies were enabled through close collaboration among scientists with distinct expertise, ranging from molecular biology to artificial intelligence, who don't normally work closely together. But such collaboration, is encouraged at the cross disciplinary Kavli Neuroscience Discovery Institute, Bergles says. The researchers are now using this machine learning approach to study synaptic changes in animal models of Alzheimer's disease, and they believe the method could shed new light on synaptic changes that occur in other disease and injury contexts. "We are really excited to see how and where the rest of the scientific community will take this," Sulam says. —ANI

 Researchers at Johns Hopkins University have created a technique that uses artificial intelligence to visualise and monitor changes 

Researchers 'See' How The Brain Adapts To Different Situations Using Machine Learning

Chandigarh (The Hawk): Chandigarh Region Innovation and Knowledge Cluster (CRIKC) mandate is to use science, technology and innovation for socio-economic change and one of its initiatives is “Shodh Samwad i.e. Research Forum” which is a platform to encourage young budding scientists to showcase their research to general society as a whole and provides initiative for collaborations and fostering partnerships among various research groups. This is the 5th event in the series of Shodh Samwad which was organized on the theme “Machine Learning: Methods and Approach”. The stage was set rolling by the expert talk by Prof. Prabha Garg from Pharmaco-informatics NIPER, Mohali where she discussed various applications in which biology can collaborate with Artificial Intelligence (AI) and Machine Learning (ML). She also highlighted how to use various algorithms for different kinds of data. Prof. Veena Puri from Bioinformatics Panjab University introduced everyone with a glimpse of her research on making precision medicines unique to a patient suffering from a particular disease. The event proceeded with a presentation delivered by two research scholars from the University of North Texas, Sarah Beaver and Yashu Vashishath where they enlightened the audience about various kinds of Machine Learning and their applications. They also explained about their research and various methodologies that they use like in making audiograms for cochlear implants and prediction of MCI state in Alzheimer’s disease patients. The research scholars from various CRIKC institutes interacted with the guests and made a fruitful session at global level. The CRIKC coordinator Prof. Gaurav Verma concluded the session by felicitating the guests.&nbsp;

Chandigarh Region Innovation and Knowledge Cluster (CRIKC) mandate is to use science, technology and innovation

CRIKC Shodh Samvad On Machine Learning And Artificial Intelligence

New Delhi: <span style="color: rgb(53,53,53);background-color: rgb(255,255,255);font-size: 14px;font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, "Noto Sans", sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji;">As Apple CEO Tim Cook bets big on generative AI, the tech giant has posted several job openings in the field of artificial intelligence (AI) globally .
The iPhone manufacturer has reportedly offered dozens of AI jobs in the United States, France, and China over the past several months in an effort to find people to fill positions that might contribute to the development of generative AI tools that make use of local processing on mobile devices.
"We are seeking a candidate with a proven track record in applied ML research. Responsibilities in the role will include training large scale language and multimodal models on distributed backends, deployment of compact neural architectures such as transformers efficiently on device, and learning policies that can be personalised to the user in a privacy preserving manner," read one such posting.
Apple's job postings have exposed some of the potential applications for generative AI in its devices.
The tech giant has been developing generative AI and other models for years, as Cook revealed.
He explained that Apple considers artificial intelligence (AI) and machine learning (ML) to be among its most important foundational technologies.
"And they are virtually embedded in every product that we build," Cook told CNBC last week, as the company reported strong June quarter results, driven by stronger services sales that grew 8 per cent (year-on-year).
"On a research basis, we've been doing research on AI and machine learning, including generative AI, for years," Cook was quoted as saying.
Apple doesn't talk much about generative AI, and its quarterly report barely mentioned the technology that has taken the world by storm.
Including all of its services, Apple now has more than 1 billion paying customers, an increase of 150 million in just the past year and roughly double the amount it had just three years ago.—Inputs from Agencies

As Apple CEO Tim Cook bets big on generative AI, the tech giant has posted several job openings in the field of artificial intelligence (AI) globally

Apple begins hunt for generative AI talent globally

Lucknow: Incidents of stubble burning in Uttar Pradesh have come down by almost 65 per cent in the past five years.
According to the government spokesman, a presentation made before chief secretary Durga Shankar Mishra highlighted data from the Promotion of Agricultural Mechanization for In-Situ Management of Crop Residue (CRM) scheme for the financial year 2022.
In 2022, a total of 3,017 incidents of crop residue burning were reported, marking a 65 per cent decrease from the 8,784 incidents recorded in 2017, as stated in the report.
In response, the chief secretary issued directives to halt the practice of crop residue burning. The agriculture department has been tasked with conducting awareness and publicity campaigns through IEC programs.
The directives stressed the importance of using print media for publicity and implementing awareness initiatives at various levels, including district, state, and Nyaya Panchayat levels.
Stubble management awareness programs should also be organised through village-level farmer schools. Additionally, radio jingles, television audio-visual clips, and scrolling messages on TV should be broadcast to raise awareness.
The directives also called for the dissemination of pamphlets for farmer training programs and the demonstration of agricultural equipment.
Public awareness campaigns should involve the use of vehicles, and farmers should be informed through wall writings and paintings.
Agricultural machinery designed for crop residue management should be made available through the Single Agricultural Machinery and Farm Machinery Bank.
Furthermore, the directives emphasised the need to establish teams at various levels, including the village, Nyaya Panchayat, development block, tehsil, and district, to work together in raising awareness and engaging the community.
—IANS

Incidents of stubble burning in Uttar Pradesh have come down by almost 65 per cent in the past five years.

UP: 65% dip in stubble burning incidents in five years

New Delhi: Elon Musk, on Monday, provided a glimpse of Tesla’s humanoid robot named ‘Optimus,’ which welcomed viewers with a ‘Namaste’ and effortlessly performed a series of Yoga poses.  As per IANS, initially unveiled during ‘Tesla AI Day’ in October 2022, Optimus was showcased in a new video posted by the X owner, demonstrating its improved capabilities.
Optimus can now self-calibrate its arms and legs, utilizing vision and joint position encoders to precisely determine the position of its limbs in space. The robot smoothly learns tasks, including sorting and unsorting colored blocks, with its neural network operating entirely on-board and relying solely on vision.
After a day of work, the humanoid robot takes time to stretch, concluding with a Namaste, as shown in the video.  Equipped with the same artificial intelligence (AI) software and sensors found in Tesla’s advanced driver assistance system ‘Autopilot,’ Optimus is estimated to cost around $20,000.
Tesla intends to mass-produce the humanoid robot in the millions of units. It features a 2.3-kilowatt-hour battery pack, suitable for a full day’s work, runs on a Tesla chip, and offers Wi-Fi and LTE connectivity, as reported by The Verge.  Optimus boasts human-like hands with a “Biologically Inspired Design,” making it capable of picking up objects of various shapes and sizes in factory and facility settings.
Elon Musk had previously stated that the robot could be priced “probably less than $20,000.” He emphasized its ability to carry a 20-pound bag, use tools, and possess a precision grip suitable for small robots.  Additionally, the robot comes with wireless connectivity, audio support, and hardware-level security features. Musk had described its potential impact as a “fundamental transformation for civilization as we know it” during the AI Day event.
—IANS

Elon Musk, on Monday, provided a glimpse of Tesla’s humanoid robot named ‘Optimus,’ which welcomed viewers with a ‘Namaste’ and effortlessly performed

Musk showcases Tesla humanoid robot performing Yoga, Namaste

Uttarkashi: The International Tunnelling and Underground Space Association has offered assistance to the Indian rescue team engaged in the evacuation operation of 40 labourers trapped after a tunnel collapse in Uttarakhand's Uttarkashi. A portion of the tunnel that is being constructed between Silkyara and Dandalgaon on the Brahmakhal-Yamunotri National Highway collapsed in the early hours of November 11 following a landslide, trapping 40 workers inside. Continuous operations have been going on in the area to rescue the labourers. Anshu Manish Khulko, the tunnel project director of National Highways &amp; Infrastructure Development Corporation Limited (NHIDCL), said that at present, teams from Norway and Thailand have been kept on standby for rescue operations. "The work of pipe pushing with the help of an auger machine is in progress to safely take out the workers trapped in the Silkyara Tunnel. So far, a distance of 24 metres of pipe has been laid inside the debris. To increase the retention capacity of the rescue operation, arrangements have also been made to airlift one more auger machine from Indore for backup so that the rescue operation continues uninterrupted," Khulko said while speaking to the media. Earlier, heavy auger drilling machines were airlifted from Delhi to ease rescue operations at war footing. Rescuers had prepared a platform for the auger drilling machine to insert large-diameter steel pipes into the debris-filled tunnel, which aimed to create a passage through which labourers could be brought out safely. "American augur machine is a highly advanced machine. Its work is going on in full swing. As per the latest update, four pipes have been inserted and the welding of a fifth one is underway. We can say that the auger machine is going well. If there are no hindrances by the debris, we will be able to make the tunnel and rescue them at the earliest," Uttarkashi SP Arpan Yaduvanshi said. "We can't give you a deadline as to when the operation will be complete but the technical workers are working hard round the clock and this will conclude at the earliest. All of them will be rescued," he added. There have been sporadic strikes outside the Silkyara-Barkot tunnel in Uttarakhand's Uttarkashi as workers remain concerned over the delay in rescuing 40 workers who have been trapped inside after a portion of the under-construction tunnel collapsed. —ANI

The International Tunnelling and Underground Space Association has offered assistance to the Indian rescue team engaged

International Tunnelling Association Offers Assistance To Rescue 40 Stranded Labourers

Pantnagar: Uttarakhand Chief Minister Pushkar Singh Dhami on Wednesday said the drilling process with the auger machine at the Silkyara tunnel had resumed and that all the 41 workers trapped inside the collapsed Uttarkashi tunnel would be safely rescued. "The auger machine is working today. I am hopeful that all workers will come out safely," said Dhami at the sidelines of an event in Patnagar. Earlier today, Dhami spoke with Prime Minister Narendra Modi on the phone and briefed him about the ongoing rescue operations at the tunnel. A portion of the under-construction tunnel between Siklyara and Barkot had collapsed on November 12 and the debris trapping 41 workers inside. In a series of posts on microblogging site X, chief minister Dhami said, "Respected Prime Minister Narendra Modi spoke on the phone today and took information about the ongoing rescue operations to provide food, medicines and other essential items to the workers trapped in the tunnel under construction in Silkyara, Uttarkashi and to get them out safely". The Uttarakhand CM said that he had informed the Prime Minister about the rescue operations conducted with mutual coordination between central agencies, international experts and the state administration. "During this, he was also informed about the positive progress made in the last 24 hours and the morale boosted by the talks between the workers and their families," Dhami tweeted. "We are receiving continuous guidance from the PM to deal with this difficult situation, which provides new energy to all of us every day to take out the labour brothers quickly and safely with full strength," the chief minister said. —ANI

Uttarakhand Chief Minister Pushkar Singh Dhami on Wednesday said the drilling process with the auger machine at the Silkyara tunnel 

The Hawk

Tag : Machine

Scientists Use Machine-Learning Approach To Predict Risk Factors Of Conduct Disorder In Kids

Rishab

Tag : Machine

Scientists Use Machine-Learning Approach To Predict Risk Factors Of Conduct Disorder In Kids

Rishab

More about Machine