Lifeboat Foundation

When humans make decisions, such as picking what to eat from a menu, what jumper to buy at a store, what political candidate to vote for, and so on, they might be more or less confident with their choice. If we are less confident and thus experience greater uncertainty in relation to their choice, our choices also tend to be less consistent, meaning that we will be more likely to change our mind before reaching a final decision.

While neuroscientists have been exploring the neural underpinnings decision-making for decades, many questions are still unanswered. For instance, how neural network computations support decision-making under varying levels of certainty remain poorly understood.

Researchers at the National Institute of Mental Health in Bethesda, Maryland recently carried out a study on rhesus monkeys aimed at better understanding the neural network dynamics associated with decision confidence. Their paper, published in Nature Neuroscience, offers evidence that energy landscapes in the prefrontal cortex can predict the consistency of choices made by monkeys, which is in turn a sign of the animals’ confidence in their decisions.

An international team of interdisciplinary researchers has successfully created a method for better 3D modeling of complex cancers. The University of Waterloo-based team combined cutting-edge bioprinting techniques with synthetic structures or microfluidic chips. The method will help lab researchers more accurately understand heterogeneous tumors: tumors with more than one kind of cancer cell, often dispersed in unpredictable patterns.

The research, “Controlled tumor heterogeneity in a co-culture system by 3D bio-printed tumor-on-chip model,” appears in Scientific Reports.

Traditionally, medical practitioners would biopsy a patient’s tumor, extract cells, and then grow them in flat petri dishes in a lab. “For 50 years, this was how biologists understood tumors,” said Nafiseh Moghimi, an applied mathematics post-doctoral researcher and the lead author of the study. “But a decade ago, repeated treatment failures in human trials made scientists realize that a 2D model does not capture the real tumor structure inside the body.”

The simulated universe theory implies that our universe, with all its galaxies, planets and life forms, is a meticulously programmed computer simulation. In this scenario, the physical laws governing our reality are simply algorithms. The experiences we have are generated by the computational processes of an immensely advanced system.

While inherently speculative, the simulated universe theory has gained attention from scientists and philosophers due to its intriguing implications. The idea has made its mark in popular culture, across movies, TV shows and books—including the 1999 film “The Matrix.”

The earliest records of the concept that reality is an illusion are from ancient Greece. There, the question “What is the nature of our reality?” posed by Plato (427 BC) and others, gave birth to idealism. Idealist ancient thinkers such as Plato considered mind and spirit as the abiding reality. Matter, they argued, was just a manifestation or illusion.

Researchers from the University of Southampton, together with colleagues from the universities of Cambridge and Barcelona, have shown it’s theoretically possible for black holes to exist in perfectly balanced pairs—held in equilibrium by a cosmological force—mimicking a single black hole.

Black holes are massive astronomical objects that have such a strong gravitational pull that nothing, not even light, can escape. They are incredibly dense. A black hole could pack the mass of the Earth into a space the size of a pea.

Conventional theories about black holes, based on Einstein’s theory of General Relativity, typically explain how static or spinning black holes can exist on their own, isolated in space. Black holes in pairs would eventually be thwarted by gravity attracting and colliding them together.

As it lay buried for two millennia, a fragment of glass gradually acquired a nanostructured surface that reflects light like a butterfly’s wings.

The ancient Roman city of Aquileia was situated close to Italy’s modern border with Slovenia. Over the centuries since its founding in 181 BCE, Aquileia suffered floods, earthquakes, sieges, and sackings. Little remains of this ancient city of 100,000 inhabitants, but archaeologists have uncovered relics from that early period. One such specimen is a glass shard discovered in 2012 on farmland in the outskirts of the modern city of Aquileia. The shard is striking in its coloration: an iridescent surface of deep blue and shiny gold atop a substrate of dark green. Now, after subjecting the shard to a string of chemical and physical tests, Giulia Guidetti of Tufts University, Massachusetts, and her collaborators have identified the origin of the shard’s appearance: a chemical transformation of the amorphous glass into a nanolayered material, a photonic crystal [1].

Glassmaking was invented independently by several Bronze Age civilizations (3300 BCE to 1,200 BCE), including those of ancient Egypt and the Indus Valley. Glass beads, vessels, and figurines remained luxury items until the Romans invented the technique of glassblowing in the first century CE. As blowing technology spread, glassware became cheaper and faster to produce in a greater variety of shapes. Items manufactured in the Roman Empire included jars for cosmetics, jugs for condiments, and cups for wine.

Trapping a Bose-Einstein condensate (BEC) in an optical lattice, researchers confirm a 53-year-old theory that connects BECs to superfluids and supersolids.

The headline challenge for building a quantum computer is well known: the quantum states exhibited by such a computer’s computational building blocks—its qubits—must be long-lived and robust against disruption by the environment. But even the most resilient qubits are useless for quantum computing if they can’t be combined in sufficient numbers. Maciej Malinowski at Oxford Ionics, UK, and his colleagues have now tackled this problem through a more efficient architecture for controlling qubits [1]. Applying their “Wiring using Integrated Switching Electronics” (WISE) approach to trapped-ion qubits specifically, they present a design for a quantum computer with 1,000 qubits—far more than the few tens of qubits that make up the largest commercially available trapped-ion device currently available.

Trapped-ion quantum computers share much of their solid-state chip technology with modern classical computers, but they have added complexity. Whereas the bits in a classical computer are written and read using simple signals sent via a small number of electrodes, the qubits in a trapped-ion computer are controlled using subtler, more varied signals, which are delivered by as many as ten separate electrodes per qubit. As the number of qubits in a quantum computer increases, fitting these electrodes and signal generators on the chip—not to mention dissipating the heat that they generate—gets more difficult.

In their WISE approach, Malinowski and his colleagues use fewer signal generators and move them off the chip. Instead of every individual qubit having its own dedicated control structure, the signal from one signal generator is relayed to multiple qubits via a small number of local switches. Malinowski says that a trapped-ion quantum computer employing their control method could be built using existing semiconductor fabrication techniques.

A new thermometer allows thermal mapping of surfaces with microscale resolution and enables studies of heat flow through materials at cryogenic temperatures.

To study tiny systems such as microelectronic components, researchers would like to map cryogenic temperatures of structures at the nanoscale. But current techniques involve some heating that can spoil the measurements. Now a research team has demonstrated a cryogenic thermometer that provides microscale resolution and that has little effect on the temperature of the system being measured [1]. Single molecules embedded in tiny crystals are the sensors, and they have millikelvin sensitivity. The team says that the technique could be useful for a wide range of cryogenic studies of the thermal properties of surfaces having nanoscale structures.

Understanding and controlling heat flow through materials is essential for developing a wide range of technologies. For example, researchers have begun to use two-dimensional materials, such as graphene, cooled to cryogenic temperatures, to conduct heat away from hot spots in microelectronic devices. In these materials and at these low temperatures, heat can travel long distances without dissipation, which makes these materials extremely effective heat conductors. However, the precise mechanisms for this heat transport are still poorly understood. More generally, researchers would also like to better understand other anomalous thermal properties of materials that apply at these temperatures, such as a regime where heat flows as waves.

Researchers have predicted—and confirmed—a secondary pattern on the ocellated lizard’s scales that is too subtle for our eyes to see.