Metaverse created by Meta gets trolled left, right and center

Horizon Worlds or Zuckerverse trolled left, right and center

Horizon Worlds is the ambitious project of the social media giant Meta, which they launched in Spain and France, progressing from their previous projects prevalent in the US, UK and Canada.

As soon as meta launched the Horizon Worlds, it fell prey in the hands of trollers and memers. Lets look at some of the most hilarious memes that came in:

metaverse graphics fit a little TOO well on old gpu boxes pic.twitter.com/19G0Az2Rck

Linus Tech Tips (@LinusTech) August 18, 2022

Looks great! pic.twitter.com/aFFcvLv4ES

james hennessy (@jrhennessy) August 16, 2022

Here, I fixed it for you now its def. worth $10 billion pic.twitter.com/6OWrMF4q2t

SMETTER. (@0xSmetter) August 17, 2022

Monopolistic Approach in Metaverse, a big failure

Ever since, Metaverse started gaining more popularity, Meta, has tried to monopolize the industry and keep the powers to itself. Recently, when one of the fitness companies, planned to make a fitness-oriented app in metaverse, Meta came in as a competition, firstly, building a similar app, and then went to the extent of buying the platform.

From Metaverses point of view, if the concept has to flourish and grow and reach billions of people, then it has to be decentralized and cannot be centralized. It is crucial for Meta to not centralize the metaverse and let the concept grow.

Metaverse is web3 while, Meta is anything but web3

Meta, is essentially a Web2 at its best! Social Media, Data Mining, Data Profits, No Privacy, Centralization are all the key factors that push meta into Web2 Technology. When we critically analyze, Metaverse is nothing like Meta, Metaverse is Web3 while, Meta if at all anything is Web2.

The concept of Metaverse gaining attraction

Credits: LeewayHertz

Metaverse is growing as every day passes by. The tech enabled, virtual reality is something, everyone wants to be a part of. Metaverse is actually much older than Facebook. The introduction of metaverse to the world happened in Snow Crash in the early 90s by Sci-Fi writer Neal Stephenson. In a sense, Metaverse is actually 50% bigger than Earth.

Writers views

I think the monopolistic approach that the Social Media giant is deploying is doing no good to both the company as well as metaverse. If the company has to grow, then it needs to come out of the possessive approach and think more practically about the industry.

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What do you think about Metas madness in regards to Metaverse? Share your thoughts in the comment section below. Also, if you like the content in this article, then please share it with your friends and family.

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Horizon World by Meta, gets trolled heavily on social media - Techstory

Doctors diagnose 10 million new cases of dementia yearly, and that number is projected to triple by 2050. Dementia is most often caused by Alzheimer's disease, and research has made little progress tackling it over more than a century. Now, using cutting-edge bioinformatics and computational biology, University of Arizona Health Sciences researchers have identified promising new candidates for Alzheimer's treatment as well as new strategies for optimizing prevention.

Despite studying Alzheimer's disease since its documentation in 1906, scientists have yet only a limited understanding of it, and there are no proven preventions or treatments for it today.

Tomorrow, however, there might be.

In just five years, Rui Chang, PhD, and Francesca Vitali, PhD, researchers at the UArizona Health Sciences Center for Innovation in Brain Science, have made incredible strides identifying molecular compounds that show significant potential for helping to prevent Alzheimer's disease and even reverse its effects.

Dr. Vitali, associate director of bioinformatics at the Center for Innovation in Brain Science, focused on the preclinical phase of Alzheimer's disease: the window in which disease is progressing undiagnosed, which can span 20 years. In a novel strategy shes named Targeted Risk Alzheimer's disease Prevention (TRAP), Dr. Vitali drew on scientific papers and drug information repositories to identify FDA-approved pharmaceuticals with promise for preventing Alzheimer's disease.

First, Dr. Vitali used natural language processing to mine information from more than 10,000 published medical studies and reports. In simple terms, natural language processing enables computers to "read" vast amounts of text, finding patterns and information that is otherwise obscured by the sheer scale of content. Through that process, she identified more than 300 diseases and conditions linked to higher risk for Alzheimer's disease.

Dr. Vitali then employed data mining across drug information repositories to identify more than 600 approved medicines used to treat those conditions. Through further evaluation, she ultimately focused on 46 drugs for a system biology analysis that revealed the complex ways they work in the body unique effects as well as interconnected biological mechanisms.

"Based on these findings, we believe that early interventions that strategically target known risks for developing Alzheimer's could effectively make this a preventable disease by 2025," said Dr. Vitali, who is an assistant research professor in the College of Medicine Tucsons Department of Neurology and a member of the BIO5 Institute.

Her analysis also showed which therapeutics, alone or in combination, might work best for patients with specific genetic profiles: a platform for a precision medicine approach to preventing Alzheimer's disease. And while Dr. Vitali developed the TRAP strategy for Alzheimer's, it can also be applied to other diseases lacking prevention and cures, such as Parkinsons disease, multiple sclerosis and Lou Gehrigs disease, also known as amyotrophic lateral sclerosis or ALS.

In a similar strategy, Dr. Chang, a computational biology investigator at the Center for Innovation in Brain Science, used artificial intelligence (AI) to analyze multiomic data sets: information on DNA, proteins, the microbiome and more. The data was drawn from thousands of postmortem brain tissue samples provided by the Accelerating Medicines Partnership Program for Alzheimer's Disease, a consortium recently established by the National Institutes of Health.

The key innovation in Dr. Chang's research, however, is the network model he created for the extensive ways that genes and proteins influence one another. Dysregulation of a single gene, for example, has ripple effects throughout the body, changing disease pathways. Scientists studying brain tissues see only terminal, downstream gene expressions, with no insight into how those states came about. Because the samples are from people who had lived with Alzheimer's disease for varying lengths of time, collectively they represent rich timelines of disease progression.

"My network model is able to pinpoint the upstream causes of disease pathology," explained Dr. Chang, who is an associate professor of neurology in the College of Medicine Tucson. "Im able to show exactly which gene in the upstream became dysregulated, the network changes it caused and therefore what could be a remedy what gene or genes to perturb to return the whole network to the healthy state."

The analyses identified 6,000 potential targets and more than 3,000 potential compounds for treatment. Those were narrowed to 170 compounds that protect neurons from death or activate the brain's innate defense system to consume amyloid plaques and neurofibril tangles, which have been the focus of Alzheimer's disease research for the past two decades.

Ultimately, Dr. Chang's study converged on three treatments that significantly improved the working memory of mice with Alzheimer's impairments. Two of the compounds are substances naturally produced in all mammals and one is derived from plants. All reduce the brain plaques and protein tangles that have been the focus of Alzheimer's disease research for the past two decades.

But while other compounds might also reduce plaques and tangles (the landmark study in this line of inquiry was recently called into question), they have never been shown to improve cognitive deficits. In contrast, Dr. Chang's treated mice improved so dramatically their brain function nearly "caught up" with the control group of mice with no disease.

Natural language processing, AI and network analyses can accelerate discovery by overcoming the natural biases and blind spots intrinsic to human analysis, revealing connections that are often only logical in hindsight.

All three compounds are now on track for clinical trials, and because neurodegenerative diseases seem to have overlapping mechanistics, Dr. Chang believes they could also lead to treatments for other diseases, including Parkinson's and Lewy body dementia. He also believes his methodology could lead to cures for comparably complex challenges like cancer, now recognized as 100-plus similar diseases.

Typically, therapeutics begin with discoveries in labs. Pharmaceutical scientists learn that a compound has a biological effect, then try to match that effect to the known causes and symptoms of health conditions.

Researchers like Drs. Chang and Vitali are flipping that model, seeking treatments and cures by first considering known factors underlying diseases. They then use technologies to scan profusions of data for patterns that suggest certain compounds may impact those biological underpinnings.

The approach offers advantages evidenced in their successes: the sheer size of the data sets would take decades to process without these technologies and working with so much data has the added advantage of establishing greater confidence in findings. The flipped model also accelerates discovery: Dr. Chang's findings were derived in just five years, Dr. Vitali's in two.

Perhaps most importantly, natural language processing, AI and network analyses can accelerate discovery by overcoming the natural biases and blind spots intrinsic to human analysis, revealing connections that are often only logical in hindsight. The 6,000 initial targets surfaced by Dr. Chang, for example, certainly included many that hadn't been considered relevant to Alzheimer's disease.

"Today, there are two camps in medical research," Dr. Chang said. "One is traditional biology, the other is AI and data science, but it's critical that these two camps are collaborating, not competing."

Data scientists can come up with hypotheses, but biologists are essential in validating those hypotheses, Dr. Chang said. And even the most advanced computers are no substitute for insight, intuition and imagination. Biologists bring and inspire new ideas, and no level of computing power today can replace that.

"It all boils down to the fact that AI is data-driven, and biologists are knowledge-driven," Dr. Chang said. "Our research works best when we bring those two approaches together. We need each other, and I hope to see even more collaboration going forward."

Read more here:

Datasets and 'Flipped' Research Drive Alzheimer's Advances | UArizona Health Sciences - University of Arizona

Pattern Computers ProSpectral device for detecting COVID-19. (Pattern Computer Photo)

A Seattle-area startup calledPattern Computeris developing a rapid COVID-19 test based on patterns in light from spit, one of several projects moving ahead from the 7-year-old company that designed its own computer from scratch.

The companys Pattern Discovery Engine was created specifically to discover and analyze patterns and excels at the task, said CEO and co-founderMark Anderson.

Pattern Computer keeps the workings of its system closely guarded, and has not published its AI models in peer-reviewed journals. Outside researchers say its hard to know whats under the hood.

But its approach has attracted seasoned computer science talent and biotech heavyweights to the startup.

The companys chief technology officer, co-founder Ty Carlson, previously managed the Amazon team that launched products such as the Amazon Echo. Its advisory board includes Leroy Hood, a co-founder of the Institute for Systems Biology, genome pioneer Craig Venter, and serial biotech startup founder George Church, a Harvard professor.

Anderson is founder and CEO of technology newsletterStrategic News Service, read by Bill Gates, Jeff Bezos, Michael Dell and Elon Musk, he said. Hes known as a tech prognosticator and each year brings together an eclectic mix of tech leaders and scientists at his Future in Review conference (he also co-founded the Whale Museum in Friday Harbor, Wash., where he lives).

At his 2015 conference, Anderson hosted a chief technology officer challenge, where participants designed a desktop supercomputer. The resulting system formed the seed for Pattern Computer. Participants included the other company co-founders, entrepreneurBrad Holtz and Michael Riddle, who previously co-founded Autodesk, makers of AutoCAD and other industrial software.

Pattern Computer focuses on biomedicine. But it also addresses problems in materials design, veterinary medicine, finance, mathematics, and aerospace with its partners, such as an analysis of ways to reduce flight delays.

Pattern Computer has raised $26 million to date, all from individual investors, including Venter and Ken Goldman, former chief financial officer of Yahoo and Patterns consulting CFO. The startup is now seeking to raise $40 million with a valuation of $1.2 billion, said Anderson.

Its a company that is taking an intriguing new approach to manipulate and analyze big data, said Hood. And when the pandemic hit, it thought deeply about the COVID problem, said Hood.

Gearing up a spit test

Pattern Computer takes a unique approach to COVID-19 testing. The company analyzes patterns of light that pass through and are absorbed by spit.

The test takes only two drops of saliva and reads off a result from the companys ProSpectral device within three seconds. The device harnesses an approach called hyperspectral sensing, which involves the analysis of light across all spectrums.

Instead of measuring the virus directly, the test captures the jumbled immune and metabolic response to disease. Theres a fingerprint for that in light, said Anderson.

Company researchers trained and assessed their model using spit from 470 samples roughly equally divided between those that were COVID-19 positive and negative on a PCR test, a conventional way to detect the disease.

Patterns test could detect 100% of people with the disease, with 8% of individuals without the disease showing a false-positive result, Andersonreportedat the Life Sciences Innovation Northwest meeting this April. Shifting the tests parameters enabled some COVID-19 cases to slip through undetected but yielded fewer false-positive results.

The test is also inexpensive: the in-house cost of running it is about 50 cents.

The testing approach is very smart, said Taran Gujral, a systems biologist and associate professor at Fred Hutchinson Cancer Center. Gujral, who does not have a financial or collaboration relationship with the company, said the method also holds promise for detecting other diseases, potentially enabling rapid testing in airports, hospitals, and in the field.

We think it will change diagnostics, said Anderson.

Keeping company secrets

Other outside researchers said they need more information to assess the companys approach to COVID-19 testing.

The company does not divulge whether it captures data using a standard type of spectrophotometer that measures light in biological samples, or another instrument. They are not sharing any information on how the signal is generated, said Dan Fu, an assistant professor of chemistry at the University of Washington.

University of Washington microbiology professor Evgeni Sokurenko, who is developing a rapid test for COVID-19 variants as co-founder of ID Genomics, said its important to look closely at Pattern Computers data in particular, the PCR data it used to train and test its models.

PCR tests work by replicating DNA derived from the virus through multiple cycles to detect a signal. Different labs use different cycle numbers for COVID-19 testing, he said. Higher cycle numbers detect lower levels of virus.

The majority of Pattern Computers COVID-19 positive samples had a cycle threshold below 30, said company researcher Matt Keener whereas the typical threshold is set higher, said Sokurenko (at 35-40 cycles).

That raises the possibility that the companys models may not be geared to pick up low levels of the virus, and could therefore miss some asymptomatic infections, said Sokurenko.

Keener countered that the companys data are consistent across all PCR thresholds. The results dont show any statistical sensitivity to the PCR value, said Keener. Our accuracy holds no matter what the PCR value for an individual test sample is. In addition, the accuracy of the companys test held true whether the samples came from asymptomatic or symptomatic individuals, he said.

The U.S. Food and Drug Administration will be the final judge of the companys COVID-19 test.

Pattern Computer has applied to the agency for emergency use authorization. Its also identified four other countries for potential launch and has arranged for partners to help it scale up and produce the test.

Were looking forward to being able to discuss more once we are comfortably down the road to regulatory approvals and such, said Keener.

Pattern Computers other bioscience projects include mining databases on gene activity in cancer cells to identify potential treatments, based on drugs already approved for other diseases though its hard to tell how the companys approach to this and other data-mining problems compares to others, said Gujral, who does similar research.

The company has identified two drug combinations that kill breast cancercell lines in culture, and is moving them through animal testing for hard-to-treat triple-negative tumors. It also is investigating treatments forovarian cancerand other tumor types.

Speaking at an investor presentation earlier this year, Omid Moghadam, CEO of diagnostics startup Namida Lab, said Patterns discovery engine substantially increased the predictive accuracy of an experimental test for breast cancer based on tear samples. Moghadam is a Pattern Computer customer and advisor.

And while Pattern has not published its bioscience projects in peer-reviewed journals, their first priority has been to get everything going, which theyve really had to put an enormous amount of time into, said Hood. I suspect they will be publishing comparative papers in the future.

The team has been refining its system and mathematical tools over the last several years, with a lean crew of 21 employees. Weve been very heads down, said Anderson.

Next generation computing

Pattern Computer is following the path of other groups, from academic labs to tech companies like Alphabet, that are changing how computers are constructed and programmed. The advent of artificial intelligence is spurring a surge of innovation.

AI models need to process vast numbers of calculations simultaneously. And current computing architecture designs are becoming a bottleneck for computing speed, infrastructure cost, and power consumption, said University of Chicago assistant professor of molecular engineering Sihong Wang.

People working on the hardware side have started to develop a completely different type of computing platform that processes information by emulating the operation of neurons in the brain, said Wang, who recently developed a flexible computing chip for wearable health tech, and is not familiar with Pattern Computers system.

Anderson said Pattern Computers approach is unique. The company created an AI system that is distinct from the neural network approached leveraged by others, he said. This is qualitatively very different from where someone has a neural network and theyre pushing it and modifying it, he said.

Pattern Computers explainable AI enables it to counteract bias that can be baked into more conventional machine learning models by skewed training datasets, said Anderson.

It allows us to see how and why the system was successful in getting high prediction rates, he said. Knowing how and why the system works provides the type of knowledge required to make major pattern discoveries, improve research, and solve real business problems.

Building that new way to make sense of patterns is a challenging problem, said Neeraj Kumar, a senior data scientist at Pacific Northwest National Laboratory.

In a recent preprint with outside researchers, company researchers published their view of how explainable AI could be applied to health data.

The publication does not specify how the companys system works, said Vijay Janapa Reddi, a Harvard associate professor who directs the universitys Edge Computing Lab. It is hard to glean much about the startup from the preprint, said Reddi, who was not familiar with the company.

But Kumar has seen enough to be convinced.

Pattern Computers computational approach is very robust, said Kumar, an author on the paper. And it is the first step for developing an explainable AI by extracting novel patterns in complex data that cannot be discovered using conventional analytical techniques and algorithms, he said.

Meanwhile, the company is turning its attention to securing regulatory approval for its COVID-19 test and planning for scale up.

Weve created a different kind of company, said Anderson.Weve done it in a different way.

Continue reading here:

Startup detects COVID-19 using spit, light, and a computer built to analyze patterns - GeekWire

Participants

This study was conducted as part of the ongoing Study on the Design of a Comprehensive Medical System for Chronic Kidney Disease (CKD) Based on Individual Risk Assessment by Specific Health Examination (J-SHC Study). A specific health checkup is conducted annually for all residents aged 4074years, covered by the National Health Insurance in Japan. In this study, a baseline survey was conducted in 685,889 people (42.7% males, age 4074years) who participated in specific health checkups from 2008 to 2014 in eight regions (Yamagata, Fukushima, Niigata, Ibaraki, Toyonaka, Fukuoka, Miyazaki, and Okinawa prefectures). The details of this study have been described elsewhere11. Of the 685,889 baseline participants, 169,910 were excluded from the study because baseline data on lifestyle information or blood tests were not available. In addition, 399,230 participants with a survival follow-up of fewer than 5years from the baseline survey were excluded. Therefore, 116,749 patients (42.4% men) with a known 5-year survival or mortality status were included in this study.

This study was conducted in accordance with the Declaration of Helsinki guidelines. This study was approved by the Ethics Committee of Yamagata University (Approval No. 2008103). All data were anonymized before analysis; therefore, the ethics committee of Yamagata University waived the need for informed consent from study participants.

For the validation of a predictive model, the most desirable way is a prospective study on unknown data. In this study, the data on health checkup dates were available. Therefore, we divided the total data into training and test datasets to build and test predictive models based on health checkup dates. The training dataset consisted of 85,361 participants who participated in the study in 2008. The test dataset consisted of 31,388 participants who participated in this study from 2009 to 2014. These datasets were temporally separated, and there were no overlapping participants. This method would evaluate the model in a manner similar to a prospective study and has an advantage that can demonstrate temporal generalizability. Clipping was performed for 0.01% outliers for preprocessing, and normalization was performed.

Information on 38 variables was obtained during the baseline survey of the health checkups. When there were highly correlated variables (correlation coefficient greater than 0.75), only one of these variables was included in the analysis. High correlations were found between body weight, abdominal circumference, body mass index, hemoglobin A1c (HbA1c), fasting blood sugar, and AST and alanine aminotransferase (ALT) levels. We then used body weight, HbA1c level, and AST level as explanatory variables. Finally, we used the following 34 variables to build the prediction models: age, sex, height, weight, systolic blood pressure, diastolic blood pressure, urine glucose, urine protein, urine occult blood, uric acid, triglycerides, high-density lipoprotein cholesterol (HDL-C), LDL-C, AST, -glutamyl transpeptidase (GTP), estimated glomerular filtration rate (eGFR), HbA1c, smoking, alcohol consumption, medication (for hypertension, diabetes, and dyslipidemia), history of stroke, heart disease, and renal failure, weight gain (more than 10kg since age 20), exercise (more than 30min per session, more than 2days per week), walking (more than 1h per day), walking speed, eating speed, supper 2h before bedtime, skipping breakfast, late-night snacks, and sleep status.

The values of each item in the training data set for the alive/dead groups were compared using the chi-square test, Student t-test, and MannWhitney U test, and significant differences (P<0.05) were marked with an asterisk (*) (Supplementary Tables S1 and S2).

We used two machine learning-based methods (gradient boosting decision tree [XGBoost], neural network) and one conventional method (logistic regression) to build the prediction models. All the models were built using Python 3.7. We used the XGBoost library for GBDT, TensorFlow for neural network, and Scikit-learn for logistic regression.

The data obtained in this study contained missing values. XGBoost can be trained to predict even with missing values because of its nature; however, neural network and logistic regression cannot be trained to predict with missing values. Therefore, we complemented the missing values using the k-nearest neighbor method (k=5), and the test data were complemented using an imputer trained using only the training data.

The parameters required for each model were determined for the training data using the RandomizedSearchCV class of the Scikit-learn library and repeating fivefold cross-validation 5000 times.

The performance of each prediction model was evaluated by predicting the test dataset, drawing a ROC curve, and using the AUC. In addition, the accuracy, precision, recall, F1 scores (the harmonic mean of precision and recall), and confusion matrix were calculated for each model. To assess the importance of explanatory variables for the predictive models, we used SHAP and obtained SHAP values that express the influence of each explanatory variable on the output of the model4,12. The workflow diagram of this study is shown in Fig.5.

Workflow diagram of development and performance evaluation of predictive models.

More:

Prediction of mortality risk of health checkup participants using machine learning-based models: the J-SHC study | Scientific Reports - Nature.com

Conference on Smart Computing and Information Security

Marwadi University (MU) will host an International Conference on Advancements in Smart Computing and Information Security (ASCIS) from November 25 to 27. The conference aims to bring together academicians, researchers, and industry practitioners of intelligent computing and information security ASCIS 2022 has also issued a call for research papers under different tracks including Artificial Intelligence, Data Science, Smart Computing, Cyber Security and Industry. The deadline to submit is August 31, 2022. For details visit https://ascisconf.org/ or email: registrations@ascisconf.org

Career Development Conclave

iSchoolConnect will host a Career Development Conclave on How technology is shaping career choices of students. This will be held virtually on August 27 and is meant for heads of institutions, heads of placements, training and placement officers, industry-relationship officers, and coordinators of higher-ed institutions. TO register visit https://bit.ly/3Axl6ON

MoUs and partnerships

Edverse recently signed an MoU with LM Thapar School of Management, Mohali, to enable students get fully immersed in a digital classroom environment and interact with the education experts.

Sattvik Council of India, in collaboration with IRCTC, recently launched SEED 2.0, a virtual internship programme designed to train and educate students on the concepts of Vegetarian Friendly Tourism and Vegetarian Friendly Railway Services (VFRS).

The Office of Learning Support, Ashoka University, recently organised a summit on inclusion of students with disabilities in higher education in partnership with Changeinkk, I-Stem and Inclusive University Alliance.

ConveGenius Insights recently conducted a state-wide assessment for the Himachal Pradesh Samagra Shiksha department in partnership with Michael and Susan Dell Foundation, to develop a remedial learning strategy after understanding the post-COVID student learning outcomes. Students of classes 4, 6 and 9 were assessed for Maths and Language abilities.

Executive Programme in Global Business Management

IIM Calcutta recently launched the 15th batch of the one-year Executive Programme in Global Business Management with Emeritus, to help learners develop future-ready business skills. For details visit https://bit.ly/3PywOx0

Events and launches

University of Essex recently announced Essex Preparation Programme (EPP), a special and free six-week online course to help incoming students become university-ready. It is offered at no cost to students, and open to anyone applying for undergraduate study at the institution. If they complete the course and register to study at Essex for the 2022-23 academic year, they will qualify for a 250 financial assistance.

Aakash BYJUS has launched Education For All, a nation-wide project to offer free NEET and JEE coaching to students from underprivileged families, especially girls. To identify the beneficiary students, Aakash will partner with select NGOs, who can nominate students.

JAIN Online recently launched #JAINOnlineCan, a brand campaign to educate, empower, and encourage informed decision-making among aspirants, when it comes to choosing their programmes.

New Zealand Institute of Skills and Technology announced its new international education strategy during an event held at the New Zealand High Commission, New Delhi. Participants included Dr. Leon de W Fourie, the Chief Executive of Te Pkenga International, and David Pine, New Zealands High Commissioner to India.

UPES Hackathon 3.0, a 24-hour coding marathaon held by UPES, Dehra Dun, concluded recently. The problem statements from industry and public sector revolved around themes such as Business Intelligence, Data Mining, Artificial Intelligence, Intelligent Transportation, Computational Optimisation, Cyber Security, Environment and Ecology, Healthcare, EdTech, and so on. Over 200 teams from India and the SAARC Nations participated and 28 made it to the finale.

Universal Business School recently organised HR and ESG Symposium 2022, which was attended by many senior Human Resource officers, CEOs and CXOs from companies such as Cadbury, TATA Consultancy Services, BNP Paribas, Deloitte, and more. The institute also welcomed a new batch of 375 students for its UG and PG programmes and hosted an induction ceremony for them.

EduBridge launched two new offerings for learners. Learn and Earn is a payment offering where a learner avails the interest-free, payment plan for upto 15 months. The next is the Secure Your Salary with Digit Groups Total Protect policy offering for learners in financial need. For details, visit, http://www.edubridgeindia.com

ARCH College of Design and Business recently organised a fashion show during the Global Educators Fest 2022 in which principals from several institutions walked the ramp. Under the Design Culture Initiative, ARCH partnered with Global Educators Fest 2022 and provided another platform to its students to showcase the design talent and creativity. The college, in association with Women Mentor Forum, also celebrated National Handloom Day 2022.

IMS Ghaziabad recently organised a talk on Marketing Management by Mohan Lal Agarwal, President, Indo-Gulf Management Association, Dubai for Term I students of PGDM Batch 2022-24. This was part of the Global Talk Series.

Celebrating Independence Day

The Academy School hosted an Independent Country, Independent Me initiative in which students pasted stickers of the national flag on homes around the school and conducted a survey on how people perceive India.

Students from multiple branches of Orchids - The International School, celebrated 75th Independence Day by hoisting the national flag and performing to some patriotic songs.

The Canadian International Schools celebration included flag hoisting and cultural performances. Students and teachers performed to A.R. Rahmans rendition of Vande Mataram.

K.N. Nehru, Tamil Nadu Minister for Municipal Administration, Urban and Water Supply hoisted a national flag measuring 75x50 feet, hand painted by 75 students of the Fashion Technology Department of Sona College of Technology and Textile Technology Department of Thiagarajar Polytechnic, Salem.

The NSS unit of Saveetha School of Management (SIMATS) recently conducted a competition to mark Independence Day. Debate and essay-writing in English and Tamil, painting, and a quiz on the theme of Independence were conducted.

IIM Bangalore recently hosted several special programmes and activities to mark 75 years of Indian Independence. The discussions were themed, India: Pioneering Past and Bright Future.

Winners of SmartIDEAthon 2022 Challenge

The winners of the SmartIDEAthon 2022 Challenge conducted at Gitam University, Visakhapatnam were announced recently. Animesh Kumar and Hrithik Jaiswal, students from Netaji Subhash University of Technology, Hajipur, Bihar, came first for the idea of IoT-based solutions for early detection and monitoring of diabetes to prevent foot ulcers. The runners-up were Karthickjothi M and Mothish M, students, Madras Christian College, for their idea to use Assistive Technology and people with speech and hearing impairments break the communication and social barrier. Amirthalakshmi K and Carolin Mary X from Tamil Nadus Saranathan College of Engineering won a prize under the Best Woman-led Entrepreneurship Idea, for working on providing a smart wheelchair to help people with mobility disabilities caused due to Chronic Obstructive Pulmonary Disease (COPD). The Leben Johnson Peoples Choice Award went to Pravin Kumar and Nabeel of Rajalakshmi Engineering College, Tamil Nadu, for their solution enabling hands-free control of smart devices for amputees, people with neurological disorders, and people with hand fractures.

Awards

Dr. T. Jayanthi, a student of Diplomate of National Board (DNB) - Ophthalmology of Dr. Agarwals Eye Hospital, Chennai, was recently awarded the Gold Medal by the National Board of Examinations (NBE) in Medical Sciences, in her specialty, at the 21st convocation ceremony of NBE in Medical Sciences, New Delhi.

Kush Malpani of Cathedral and John Connon School recently won the Gold at the International Economics Olympiad 2022.

Convocations

O.P. Jindal Global University recently held its convocation and awarded UG, PG and doctoral degrees to 3,100 students from various schools and institutes. Justice D.Y. Chandrachud of the Supreme Court of India delivered the Convocation Address. The Rt Hon Patricia Scotland QC, Secretary-General, The Commonwealth also spoke at the event. The university also bestowed the Lifetime Achievement Award and the Global Justice Medal on them.

Dharmendra Pradhan, Union Minister of Education and Skill Development and Entrepreneurship, Government of India, awarded Blockchain-based Digital Degrees to 1,555 Students of NIT Rourkela during its 19th Convocation. These certificates will now be accessible from anywhere in the world since it is encrypted and stored digitally.

Corporate and cultural immersion programme for students

MQDC India recently organised a five-day immersion programme for Bennett University students to provide a hands-on experience and hone industry-relevant skills in an academically-stimulating environment.

Monsoon Maladies campaign

SRCC Children's Hospital, managed by Narayana Health, Mumbai, recently launched a campaign to create awareness among students about Monsoon Maladies: Seasonal water and vector-borne diseases.

First cohort of UN India YuWaah Advocates appointed

UN agencies in India marked International Youth Day by appointing the first cohort of UN India YuWaah Advocates and making a pact for youth centrality. Six young individuals from diverse backgrounds and geographies have been chosen to inspire action for SDGs across high-level decision-making platforms. In turn, they will receive access to information, skilling, and mentorship support, and will work in partnership with external experts across UN agencies and partner networks, celebrity advocates, ambassadors, and digital influencers to amplify and foreground young peoples priorities and perspectives towards shaping the 2030 Agenda.

McAfee Cyberbullying Report 2022

A global report titled Cyberbullying in Plain Sight, by McAfee, recently uncovered several new and consequential trends regarding cyberbullying including the types of bullying being reported, data around perpetrators and victims of online bullying, and the tensions between how parents and children define cyberbullying activity. Some findings included: extreme forms of cyberbullying reported besides racism (42%) include trolling (36%), personal attacks (29%), sexual harassment (30%), threat of personal harm (28%) and doxing (23%). India reported prominent acts of cyberbullying such as spreading false rumours at 39%, being excluded from groups and conversations at 35%, and name calling at 34% and 45% of Indian children said they hide their cyberbullying experiences from parents, perhaps due to the relative absence of conversation.

Read the original here:

News from the world of Education: August 19, 2022 - The Hindu