Brain development during the initial years is critical, shaped by both environment and caregiver behaviors. To clarify the causal relationship between maternal psychological distress and neuropsychiatric developmental delays, researchers in Japan analyzed data from over 82,000 mother–child pairs in a large-scale nationwide cohort. They found that distress within 1 year postpartum had stronger effects on the toddler’s neurodevelopment than prenatal distress, emphasizing the importance of continuous maternal mental health support before and after childbirth.

An Osaka Metropolitan University researcher quantitatively evaluated the optimal approach for a tomato harvesting robot using image recognition and statistical analysis to maximize the success rate of fruit picking.

Insect pupae hiss like snakes for defense. A Kobe University team now reveals the mechanisms, opening the door to further studies involving predator reactions to defensive sounds.

Why does plastic turn brittle and paint fade when exposed to the sun for long periods? Scientists have long known that such organic photodegradation occurs due to the sun’s energy generating free radicals: molecules that have lost an electron to sunlight-induced ionization and have been left with an unpaired one, making them very eager to react with other molecules in the environment. However, the exact mechanisms for how and why the energy from the sun’s photons get stored and released in the materials over very long periods have eluded empirical evidence.  

The problem lies in the timeframe. While scientists have access to extremely sophisticated spectroscopy equipment capable of measuring the energy levels of individual electrons at femtosecond to millisecond scales in organic materials, they have paid little attention to time scales beyond seconds – and these are processes that can take years.  

As such, slow, transient charge accumulation has presented a disappointing data gap in both applied and theoretical optics. But now, researchers from the Organic Optoelectronics Unit at the Okinawa Institute of Science and Technology (OIST) have addressed this challenge with a new methodology that detects these faint signals. Their findings are published in Science Advances.

Poly(N-isopropylacrylamide) (PNIPAM) hydrogel undergoes significant but precise changes in size between 20 and 40 °C, making it an excellent candidate for use in variable-size deterministic lateral displacement (DLD) array devices. Researchers from Science Tokyo have built a tunable DLD cell-sorting platform and verified its ability to sort cancer cells of defined sizes from blood samples. This platform could offer high-resolution size-based cell sorting for a wide variety of biomedical applications

Game meat has traditionally been shunned by the Japanese population, Despite it being a sustainable food resource, vast amounts go to waste each year. A research team has dived deeper into the psychological barriers to game meat in Japan in an attempt to better market this underutilized resource.

Osaka Metropolitan University researchers investigated the causes of acute mountain sickness at the Mount Fuji Summit Hut. 

There is an important and unresolved tension in cosmology regarding the rate at which the universe is expanding, and resolving this could reveal new physics.  Astronomers constantly seek new ways to measure this expansion in case there may be unknown errors in data from conventional markers such as supernovae. Recently, researchers including those from the University of Tokyo measured the expansion of the universe using novel techniques and new data from the latest telescopes. Their method exploits the way light from extremely distant objects takes multiple pathways to get to us. Differences in these pathways help improve models on what happens at the largest cosmological scales, including expansion.

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both efficient and as accurate as possible at each step lest errors pile up. A Kobe University team now introduces a new method that uses deep learning for creating tailored, accurate simulations that respect physical laws, while also being more computationally efficient.

Every bit of technology fails eventually, whether time, wear-and-tear, adverse conditions, or perhaps a mixture of all three are the cause of its demise. Yet predicting when technology might fail is notoriously difficult. When designing equipment for clear-energy systems, engineers often over compensate for this by designing it to withstand more stress than needed. This generates waste, and can sometimes inadvertently increase the wear and tear on materials. Now, an international research team has developed a way to more accurately predict how long mechanical-equipment used in green technology will last, potentially leading to more efficient design processes.