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Researchers in Bangalore, India, have created an integrated model of emotion-driven decisions and social interactions that takes into account the roles of emotion, mood, and memory biases.

Computational model helps understand social impacts of mood disorders and

Image credit: Pixabay (Free Pixabay license)

Mood disorders such as depression and bipolar disorder are prevalent in society, and studies indicate that it affects an estimated 310 million people worldwide [2]. Hence, models that capture them realistically are essential and relevant. There have been some models of various mood disorders, but most of these assume independent agents without any social interactions or social networks. The extent and frequency of social interactions are intricately linked to mood disorders and play a major role in decision making. Empirical studies also conclude that depressed phases are connected with lower energy, interest, and drive. In this work, the drive and size of the social network are modeled based on the extent of mood disorder in an agent.

It is well known that mood and memory are related, and the current mood determines which memories are more likely to be retrieved than the others. Remembering negative events and experiences in the past when we are depressed is a manifestation of mood- dependent memory retrieval. Despite its importance, there have been no computational models of this phenomenon before this work.

They use an agent-based model to understand the effects of various biases related to mood and memory on an agent’s performance. The biases are defined in line with the existing literature in areas of psychology and behavioral sciences. Therefore, the present model is much more realistic and detailed than prior works and would help in gaining a better understanding of these important facets of human decision-making.

As this is a computer-based simulation, parameters such as the extent of mood disorders, population mixes, etc., can be varied to understand various scenarios, which may not be feasible in clinical trials. This work can also be extended to study the effects of various traits or biases, some of which may not be easy to study empirically.

This research was done by Nanda Kishore Sreenivas and Shrisha Rao at IIIT-Bangalore. The paper has been recently published in Scientific Reports [1] on December 1, 2020.

Most prior models of decision-making in humans assume rational behavior and have neglected the critical roles of moods and memory biases. We know that not all memories are created equal. Events with a high emotional value are lasting, while more mundane experiences are forgotten quickly. Even among events with similar emotional value, some of us are more likely to remember the negative ones longer while others may experience the opposite. Such intricate aspects of memory biases are considered in this work.

Based on simulation of an agent society with agents of all four types—rational, manic, depressed, and bipolar—results are obtained about relative payoffs and other aspects. While a greater fraction of people in society being rational or depressed does not improve the average performance of those types of individuals, more people being manic results in a decreased average performance for such manic individuals; on the other hand, more people being bipolar increases their average performance. Bipolar people also perform better with slight forgetfulness than with perfect memory, in contrast with the other types.

Among manic and bipolar people, those with a positive emotional bias perform better, while it is the opposite among depressed people. Also, a moderate level of mood dependence brings out the best performance in manic individuals and the worst performance in depressed people. Due to the fluctuating nature of moods in bipolar people, weak mood dependence offers the best performance.

The results concur with psychological studies that show a relationship between severity of depression and lower performance, and also suggest diminished performance in depressed individuals and improved performance in cases of mania. However, the findings also significantly extend the findings from clinical assessments, which cannot arrange special circumstances like proportions of people of each type in a society, the rate of forgetfulness and bias, etc.

“This work is broadly in the field of computational social science, and specifically uses an agent-based model carefully constructed in line with studies in psychology. This also illustrates that agent-based modeling is a powerful, though relatively new tool in the study of social psychology.”, says Shrisha Rao, professor at IIIT-Bangalore. “While the model cannot yet directly derive outcomes that can definitively guide treatments of clinical disorders, it does permit new insights that are not possible using mathematical studies and clinical experiments.”

References:

[1] Analyzing the Effects of Memory Biases and Mood Disorders on Social Performance. Scientific Reports, December 1, 2020. doi:10.1038/s41598-020-77715-6.
[2] WHO. Mental Disorders (2019). https://www.who.int/news-room/fact-sheets/detail/ mental-disorders

Source: Nanda Kishore Sreenivas, Shrisha Rao. Analyzing the Effects of Memory Biases and Mood Disorders on Social Performance. Scientific Reports, December 2020. doi.org/10.1038/s41598-020-77715-6




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Diamonds may help measuring thermal conductivity in living cells

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Scientists have very precise instruments, but measuring properties of tiny little cells is still very difficult. Now researchers at the University of Queensland have developed a new tool to measure heat transfer inside living cells. It includes actual diamonds and it can work as both a heater and a thermometre. Someday it can improve cancer diagnosis.

Diamonds may help measuring thermal conductivity in living cells

Diamonds are essentially very hard pieces of carbon, which makes them great for some scientific applications. Image credit: En-cas-de-soleil via (Wikimedia(CC BY-SA 4.0)

Cancer cells are different – they behave differently and exhibit different properties. Scientists have long speculated that in some cases precisely targeted thermal therapies could be very effective against cancer. However, in order for this to become reality scientists needed to know thermal conductivity of living cells. With current technology it is literally impossible to measure thermal conductivity – the rate that heat can flow through an object if one side is hot and another is cold – inside of such tiny living things as cells.

Scientists from Australia, Japan and Singapore now employed nanodiamonds (just tiny little diamonds) to act as minute sensors in a new system. Diamonds are great, because they are very hard and because they are just a different form of carbon, which is very well-known to us. Scientists coated their nanodiamonds with a special heat-releasing polymer. This resulted in a sensor, which can act as a heater or a thermometre, depending on what kind of laser light is applied. This sensor allows measuring thermal conductivity in living cells with a resolution of 200 nanometres.

Associate Professor Taras Plakhotnik, lead author of the study, said that this new method already revealed some new interesting information about cells. He said: “We found that the rate of heat diffusion in cells, as measured in our experiments, was several times slower than in pure water, for example.”

If cancer cells and healthy cells exhibit different thermal conductivity, this kind of measurement could become a very precise diagnostic technique. Also, because these particles are not toxic and can be used in living cells, scientists think they could open the door for  improving heat-based treatments for cancer. Measuring head conductivity could help monitor biochemical reactions in real time in the cell. But that’s not all. Scientists think that this method could lead to a better understanding of metabolic disorders, such as obesity.

Diamonds are commonly used in science and industry. People oftentimes see them as something from the jewelry world, but they are much more common elsewhere. And they are not even that expensive. Hopefully, this study will result in a new method to research living cells and maybe some novel therapies as well.

 

Source: University of Queensland




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Redmi Note 10 Launch Teased Officially After Rumours Tipping February Debut in India

Redmi Note 10 launch has been officially teased on Weibo. The new development comes just weeks after the rumour mill suggested the existence of the Redmi Note 10 series that could include the Redmi Note 10, the Redmi Note 10 Pro, and the Redmi Note 10 Pro 5G. The new series is expected to succeed the Redmi Note 9 family that debuted with the launch of the Redmi Note 9 Pro and the Redmi Note 9 Pro Max in India in March last year.

Redmi General Manager Lu Weibing has teased the launch of the Redmi Note 10 on Weibo. Instead of giving away details of the phone directly, Weibing has posted an image of the Redmi Note 9 4G asking users about their expectations with the Redmi Note 10.

The Redmi Note 10 is speculated to launch in India alongside the Redmi Note 10 Pro in February. Both phones will be priced aggressively, according to tipster Ishan Agarwal. The Redmi Note 10 in the series is tipped to come in Gray, Green, and White colour options.

Although Xiaomi hasn’t provided any specifics about the phone yet, the Redmi Note 10 Pro 5G purportedly received a certification from the Bureau of Indian Standards (BIS) earlier this month. The phone is also said to have surfaced on the US

Federal Communications Commission (FCC) website with the model number M2101K6G. It has also reportedly appeared on the websites of other regulatory bodies including the European Economic Commission (EEC), Singapore’s IMDA, and Malaysia’s MCMC.

Redmi Note 10 series specifications (expected)

The Redmi Note 10 Pro is rumoured to come with a 120Hz display and include the Qualcomm Snapdragon 732G SoC. However, the 5G variant of the Redmi Note 10 Pro is said to come with the Snapdragon 750G SoC. It is speculated to have 6GB and 8GB RAM options as well as 64GB and 128GB storage versions. The Redmi Note 10 Pro models will come with a 64-megapixel primary camera sensor and include a 5,050mAh battery, according to a recent report.

Similar to the Redmi Note 10 Pro models, the Redmi Note 10 is also rumoured to have both 4G and 5G versions. The smartphone is tipped to have a 48-megapixel primary camera sensor and include a 6,000mAh battery.

The Redmi Note 10 Pro and the Redmi Note 10 are both expected to run on Android 11 with MIUI 12 out-of-the-box.


What will be the most exciting tech launch of 2021? We discussed this on Orbital, our weekly technology podcast, which you can subscribe to via Apple Podcasts, Google Podcasts, or RSS, download the episode, or just hit the play button below.

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Cybersecurity: Blaming users is not the answer

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A punitive approach toward employees reporting data breaches intensifies problems.

Image: iStock/iBrave

Experts are warning, when it comes to cybersecurity, blaming users is a terrible idea. Doing so likely results in creating an even worse situation. Many organizations have defaulted to a blame culture when it comes to data security,” comments Tony Pepper, CEO of Egress Software Technologies, in an email exchange. “They believe actions have consequences and someone has to be responsible.”

“In cases where employees report incidents of data loss they accidentally caused, it’s quite common for them to face serious negative consequences,” continues Pepper. “This, obviously, creates a culture of fear, leading to a lack of self-reporting, which in turn, exacerbates the problem. Many organizations are therefore unaware of the scale of their security issues.”

Pepper’s comments are based on findings gleaned by the independent market research firm Arlington Research. Analysts interviewed more than 500 upper-level managers from organizations within the financial services, healthcare, banking, and legal sectors.

What the analysts found was published in the paper, Outbound Email Security Report. Regarding employees responsible for a loss of data, 45% of those surveyed would reprimand the employee(s), 25% would likely fire the employee(s).

SEE: Identity theft protection policy (TechRepublic Premium)

Pepper suggests while organizations may believe this decreases the chance of the offense reoccurring, it can have a different and more damaging effect. There’s a chance employees may not report security incidents, to avoid repercussions from company management. 

“Especially in these uncertain times, employees are going to be even less willing to self-report, or report others, if they believe they might lose their jobs as the result,” adds Pepper. 

It gets worse 

According to survey findings, a high percentage of organizations rely on their employees to be the primary data breach detection mechanism–particularly when it comes to email. “Our research found that 62% of organizations rely on people-based reporting to alert management about data breaches,” mentions Pepper. “By reprimanding employees who were only trying to do their job, organizations are undermining the reporting mechanism and ensuring incidents will go unreported.”

The lack of truly understanding why data is escaping the digital confines of an organization makes it hugely difficult for those in charge of cybersecurity to develop a defensive strategy that will effectively protect an organization’s data.

Overcome the blame game

Once it is understood that reprimanding employees is ineffective, organizations should look to create a more positive security culture. One immediate benefit is the increased visibility of heretofore unknown security risks.  

Another benefit is the ability to show regulatory bodies the organization has taken all reasonable steps to protect sensitive data. Pepper adds, “If you don’t know where your risks are, it’s hard to put reasonable measures in place. Regulators could surmise that during a data breach investigation and levy higher fines and penalties.” 

Technology has a role

Once the blame game is curtailed, it’s time to get technology involved. “The first step is to get reporting right, using technology, not people, which will remove the pressure of self-reporting from employees and place the responsibility firmly in the hands of those in charge of cybersecurity,” suggests Pepper. “Advances in contextual machine learning mean it’s possible for security tools to understand users and learn from their actions, so they can detect and mitigate abnormal behavior–for example, adding an incorrect recipient to an email.”

This is where technology makes all the difference. It prevents accidental data loss before it can happen. It empowers employees to be part of the solution, and technology gives the security team unbiased visibility of risks and emerging threats. 

What cybersecurity teams need to understand

Education about potential consequences is vital. Anyone working with the organization’s digital assets needs to understand the possible outcomes from a data breach–for example, regulatory fines or damage to the organization’s reputation. 

It’s a safe bet when users understand the consequences of emailing client data to the wrong recipient or responding to a phishing email, they’ll be much more likely to report the incident if and when it occurs. Remember: If an incident isn’t reported, there’s no way to remediate it or prevent it from happening again.

Pepper, in conclusion, offers advice to those managing cybersecurity. “The best way to engage employees with security, and ensure they understand its importance, is to create a ‘security-positive’ company culture,” explains Pepper. “Security teams need to reassure the wider organization that, while data breaches are to be taken seriously, employees who report accidental incidents will receive appropriate support from the business and not face severe repercussions.”

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