The 1% Rule

The following image showcases a powerful concept that states that if you strive to improve your work with only 1% every day, you will make considerable improvements in a year, as compared to staying the same – which doesn’t change anything, or in a more pessimist scenario, performing worse each day.

If you get one percent better each day for one year, you’ll end up thirty-seven times better by the time you’re done. Source

This is the concept of continuous improvement – dedication to making small changes and improvements every day, with the expectation that those small improvements will add up to something significant. Focusing on taking little steps towards your goal in a consistent fashion is the most efficient way of getting good at something. It also has the advantage of removing burnout, frustration, and failure.

Some steps that can aid in the process are:

  1. Do more of what already works. Start with what you have, and identify one area that you can work on to improve. For example, let’s suppose that you wanted to read a certain book, but never found time. Start small, try reading one page. Tomorrow maybe try two pages. And so on, until you find a comfortable reading and understanding pace that you can keep up with.
  2. Avoid tiny losses. Eliminate mistakes, reduce complexity, and stripe away the inessential. For example, if your goal is to improve your mathematical skills, pay attention to the theory, practice with more examples, and repeat the concepts over time.
  3. Measure backward. While being focused on future goals, we often forget to take a look back on the progress that we just made. Therefore you should keep a log or a journal tracking your steps. For example, while working out, you can see that if last week you were able to easily squat with 17.5kg, this week you can push for 20kg. Or if your goal is to lose weight, from your calorie tracker you can see that you ate 2,400 calories on average last week, therefore this week strive for 2,300 calories.

Don’t be afraid to experiment and see what works best for your goals. After overcoming the mental barrier and making this a habit, you can start being more creative and having fun with the process.

Source – abridged and adapted

Miniature antenna for improved robotic teaming in complex environments

A new, miniature, low-frequency antenna with enhanced bandwidth will enable robust networking among compact, mobile robots in complex environments. In a collaborative effort between the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory and the University of Michigan, researchers developed a novel design approach that improves upon limitations of conventional antennas operating at low frequencies — demonstrating smaller antennas that maintain performance.

Active matching network consisting of a cross-coupled transistor pair
and the designed antenna impedance model 𝑍’_𝑀(𝜔) Source

Impedance matching is a key aspect of antenna design, ensuring that the radio transmits power through the antenna with minimal reflections while in transmit mode — and that when the antenna is in receive mode, it captures power to efficiently couple to the radio over all frequencies within the operational bandwidth.

“Conventional impedance matching techniques with passive components — such as resistors, inductors and capacitors — have a fundamental limit, known as the Chu-Wheeler limit, which defines a bound for the maximum achievable bandwidth-efficiency product for a given antenna size,” said Army researcher Dr. Fikadu Dagefu. “In general, low-frequency antennas are physically large, or their miniaturized counterparts have very limited bandwidth and efficiency, resulting in higher power requirement.”

With those challenges in mind, the researchers developed a novel approach that improves bandwidth and efficiency without increasing size or changing the topology of the antenna.

You can read more in the original paper (this version is adapted and abridged from Source).

Choi, J., Dagefu, F.T., Sadler, B.M. and Sarabandi, K., 2020. A Miniature Actively Matched Antenna for Power-Efficient and Bandwidth-Enhanced Operation at Low VHF. IEEE Transactions on Antennas and Propagation.

Moschino Spring Summer 2021 collection

Enjoy this presentation of the new Moschino Spring/Summer 2021 collection, by Jeremy Scott, entitled “No strings attached”.

It is a beautiful example of how creativity works. You take multiple elements such as clothes, puppets, cinematography and music, and create a unique fashion show that enhances each ingredient and merges them together to create a brilliant and mesmerizing effect!

Planar to spatial geodesic grids

At the Center for Geometry and Computational Design (GCD) (Institute for Discrete Mathematics and Geometry) at TU Wien, Musialski and his team developed a method that can be used to calculate what the flat, two-dimensional grid must look like in order to produce exactly the desired three-dimensional shape when it is unfolded. “Our method is based on findings in differential geometry, it is relatively simple and does not require computationally intensive simulations,” says Stefan Pillwein, first author of the current publication.

Suppose you screw ordinary straight bars together at right angles to form a grid, so that a completely regular pattern of small squares is created. Such a grid can be distorted: all angles of the grid change simultaneously, parallel bars remain parallel, and the squares become parallelograms. But this does not change the fact that all bars are in the same plane. The structure is still flat.

The crucial question now is: What happens if the bars are not parallel at the beginning, but are joined together at different angles? “Such a grid can no longer be distorted within the plane,” explains Przemyslaw Musialski. “When you open it up, the bars have to bend. They move out of the plane into the third dimension and form a curved shape.”

At the Center for Geometry and Computational Design (GCD) (Institute for Discrete Mathematics and Geometry) at TU Wien, Musialski and his team developed a method that can be used to calculate what the flat, two-dimensional grid must look like in order to produce exactly the desired three-dimensional shape when it is unfolded. “Our method is based on findings in differential geometry, it is relatively simple and does not require computationally intensive simulations,” says Stefan Pillwein, first author of the current publication.

You can read more in the original paper (this version is adapted and abridged from Source).

Pillwein, S., Leimer, K., Birsak, M. and Musialski, P., 2020. On elastic geodesic grids and their planar to spatial deployment. arXiv preprint arXiv:2007.00201.

OpenVisSim, a sight-loss simulator

Modern digital simulators are able to replicate and objectively quantify some of the key everyday difficulties associated with visual impairments.

First row: virtual rooms from the simulator. Bottom row: smartphone highlighted in the first pannel, while the last 2 showcase superior and inferior visual field loss. Source

Over 100 million people worldwide live with a chronic visual impairment (VI). The most common causes are glaucoma, agerelated macular degeneration (AMD), and cataracts. Simulations are often used to help communicate the day-to-day challenges that visually impaired individuals may experience. The authors used a Head Mounted Display (HMD) with integrated eyetracking to perform gaze-contingent digital manipulations in virtual or augmented reality (VR/AR). Their software is freely available online (OpenVisSim), and provides a description of multiple different symptoms that can be simulated simultaneously and in real-time.

The current work is focused on glaucoma, because it is often misunderstood. Individuals with this condition often report particular difficulty locating objects in cluttered visual scenes, and also exhibit reduced mobility and increased risk of falls. Additionally, these difficulties tend to be most pronounced when the loss occurs in the inferior visual field, compared to when the loss of vision occurs above the midline. The experimental setup implies 28 individuals that had to perform two tasks in the simulator: object search (locate a smartphone in a house) and visual mobility (navigation). The results show that participants were slower to perform everyday visual-search (VR) and mobility (AR) tasks when experiencing simulated Visual Field Loss (VFL), and as with real patients these difficulties were exacerbated when the VFL was inferior.

Many participants reported feeling anxious when the impairment was active. This was particularly the case when participants were ascending/descending the stairs that led to the AR mobility platform. Interestingly, “climbing stairs” is also a regular source of anxiety for many people with severe vision loss.

You can read more in the original paper (this version is adapted and abridged).

Jones, P.R., Somoskeöy, T., Chow-Wing-Bom, H. and Crabb, D.P., 2020. Seeing other perspectives: evaluating the use of virtual and augmented reality to simulate visual impairments (OpenVisSim). NPJ digital medicine3(1), pp.1-9.

Preparing for the sandworms

Since the trailers for the 2020 movie adaptation of the book “Dune” (written by Frank Herbert, and published in 1965) were released, it is a good moment to refresh our memories and read the original work. Below is a creative animated summary of the plot, to get you started reading the series if you haven’t already. On the same note, if you haven’t watched the first movie which appeared in 1984, a great comparison between the old and new teasers will incite your curiosity to better understand what has changed (or not) in cinematography and storytelling.

Overcome your fear of the unknown

Recent events made our lives unpredictable. They took us out of our comfort zone and into unknown territory, adding to our previous fears by making us tread uncharted waters. We might have been in a pleasant state, without a worry in the world. We had hopes and dreams and plans that are now uncertain. It changed the way in which we live by altering various aspects of our lives – we had to socially distance ourselves, we were bombarded with alarming news and statistics, some people faced unemployment, children lost access to education, and many more worrying examples. These made our anxiety peak. Fear of the unknown is truly one to rule them all.

In the end, you become what you give your attention to. If you focus only on the negative aspects of life, you will only see those. If you constantly worry about exams, that’s all you’ll be able to think about. If you are angry about the uncertainty of future events (for example, how school or university will be reopening), you will be caught in a loop of frustration. These will make you distrust yourself, others, your countries’ institutions, and life in general. Take advantage of the power of your thoughts and make a change.

While facing difficult times, it is better to be patient. Watch as events unfold, pay attention to people around you, research, and study to understand things that scare you. If you feel courageous, you can even come up with practical solutions to improve your situation. Just be aware that sometimes bad things are good at a higher level, these are the drivers of evolution. Be open to the unknown and to change, and see where it takes you.

Defeat procrastination

You know that feeling of dread when there is a long to-do list in front of you but somehow you can’t make yourself tackle it. This puts you in an unhealthy cycle of avoiding work by occupying your mind with other activities, while new tasks keep appearing. This emotional response is called procrastination, and it negatively affects your well-being. Fortunately for us, we are not alone in feeling this way, and there are ways to change our behaviour to become more productive and happy.

A good article on this topic is How to Stop Procrastinating: The Only Guide You’ll Ever Need. The main ideas are:

  1. Understand this is a normal response and forgive yourself for any shortcomings you notice (like avoiding to do work, finding distractions, or not completing work on time).
  2. Evaluate the importance and urgency of tasks from the to-do list, establishing deadlines, and evaluating your strengths and weaknesses. Then create a list based on these observations, considering putting first the most urgent and important tasks.
  3. Control your environment by removing distractions. Start by blocking so-called infinity pools (you know which ones, just think about how much time you spend on social media, YouTube, or video games for example) with apps and extensions (Freedom, Block Site, etc.).
  4. Create a schedule and track your focused working time (using Forest or Focus To-Do). At the end of the day, evaluate your expectations versus reality, and you will be surprised at how much you were able to accomplish.

If you need an example, you can refer to the next video:

Heart disease diagnosis using selfies

Medical research has seen major advances during the past few years, particularly as big data have emerged in biomedical research. Implementation of AI technology in day-to-day clinical practice has already begun, with emerging applications using it to interpret medical images, read pathology slides, analyse electrocardiograms (ECGs), track vital signs, and many other uses.

Speedy diagnostic testing is rapidly becoming an important part of medical practice. Information extracted from analysis of an individual’s facial photo utilizing the proposed technology can unquestionably benefit the individual, the attending physician, and the healthcare system altogether. Early detection of individuals at risk for coronary artery disease (CAD) can initiate lifestyle and other personal mitigation approaches, guide medication treatment, and inspire a novel approach in diagnostic testing and screening algorithms for the general population. At the same time, such a technology may raise concerns about misuse of information for discriminatory purposes. Unwanted dissemination of sensitive health record data, that can easily be extracted from a facial photo, renders technologies such as that discussed here a significant threat to personal data protection, potentially affecting insurance options.

The authors of a new paper published in August 2020, called “Feasibility of using deep learning to detect coronary artery disease based on facial photo”, deploy a large training set of 5216 individuals to develop their deep learning algorithm which is tested on a group of 1013 individuals predominantly of Han Chinese ethnicity recruited in tertiary centres across China. All patients underwent a standardized protocol for acquisition of facial images, and a coronary computed tomography angiography (CCTA) was used as the reference method for dichotomizing the cohort into groups of CAD presence. Facial appearance has long been identified as a marker of cardiovascular risk, with features such as male pattern baldness, earlobe crease, xanthelasmata, and skin wrinkling being the most common predictors. The robustness of this approach lies in the fact that their deep learning algorithm requires simply a facial image as the sole data input, rendering it highly and easily applicable at large scale. Using selfies as a screening method can enable a simple yet efficient way to filter the general population towards more comprehensive clinical evaluation. Such an approach can also be highly relevant to regions of the globe that are underfunded and have weak screening programmes for cardiovascular disease.

There are still a few points, however, for consideration that make a practical application of the current algorithm challenging. The low specificity of the method raises a concern regarding false-positive results that may confuse both patient and clinician, and eventually overload the system with redundant and unnecessary testing. The photo pre-processing used may be another issue for consideration; resolution was reduced to 256 × 256 pixels, which hinders the detection of fine facial features, such as arcus lipoides, that may play a role in the diagnostic accuracy of the model. Moreover, proper external validation of deep learning models in populations that are independent is needed to ascertain their use and functionality. Finally, in an era that observes a record surge in cosmetic surgery, we should keep in mind that artificial facial alterations may severely discredit such screening tools.

Paper: Lin S , Li Z, Fu B, Chen S, Li X, Wang Y, Wang X, Lv B, Xu B, Song X, Zhang Y-J, Cheng X, Huang W, Pu J, Zhang Q, Xia Y, Du B, Ji X, Zheng Z. Feasibility of using deep learning to detect coronary artery disease based on facial photo. Eur Heart J 2020;doi:10.1093/eurheartj/ehaa640. 2020

Source – abridged and adapted

Spaced repetition using flash cards

Pierce J. Howard’s book “The Owner’s Manual for the Brain” starts with the following ideas:

Learning is memory; memory, learning. Learning entails two processes: acquiring and retaining. Psychologists and educators would call these processes short-term memory and long-term memory. Whether we are learning a telephone number, a chess strategy, a role in a play, a dance step, or how to recover from a computer mishap, in order to say that we have learned something we must be able to demonstrate that not only have we acquired the knowledge or skill, i.e., that we understand it and can use it properly, but that we also have retained that understanding so that we may continue to use it over time.

Another key point to keep in mind with respect to how we use the word memory is that it comes in different modes: memory for words (e.g., a poem), for numbers (e.g., telephone numbers or the times tables), for images (e.g., faces or artworks), for sounds (e.g., specific engine noises or melodies), for movements (e.g., dance steps), for nomenclatures and organizational schemes (e.g., an organization chart or the periodic table of elements), for interpersonal idiosyncrasies (e.g., what motivates different people), and for personal preferences (e.g., things I do and don’t like). These eight areas are called talents, or multiple intelligences.”

The two best strategies that anyone can apply to aid in the learning process are spaced repetition and flash cards. They imply dividing the material into smaller parts, then writing down definitions, formulas, vocabulary, dates etc. and repeatedly learning and testing over a longer period of time, with breaks in between. Another tip is creating categories, based on how well you know the content. For example, there can be 3 groups for when to review the cards: every day, once per week, or before test. This process can be done by pen and paper (see video below), but there are also apps like Anki, Tinycards, Brainscape or Quizlet. Happy learning!