Kyoto, Japan -- Citizen science has allowed regular citizens to participate in data collection as well as expanded biodiversity monitoring. Yet many datasets are still limited to the coverage of certain regions and habitats in particular seasons. In bird research, for example, traditional point‑count surveys often have strict rules regarding the location, timing, and spacing between observation points, making it challenging for citizen volunteers to participate casually.

This inspired Masumi Hisano, formerly of Kyoto University and now at Hiroshima University, to try a more flexible approach by conducting counts whenever and wherever possible, as part of his daily routines. As someone who hates waking up early, Hisano tried to bend the traditional time rules to suit his desired schedule.

"I thought it was a wasted opportunity to not record birds I encounter in daily life, like in the supermarket parking lot or at the train station," says Hisano.

Collaborative research by the University of Tokyo and RIKEN Center for Biosystems Dynamics Research has led to the development of a new method for simultaneously synthesizing all transfer RNA (tRNA) required for protein synthesis in a reconstituted translation system in vitro.

Lifestyle-related diseases are rapidly increasing, particularly among the lower socioeconomic brackets of the society. To address this public health concern, Japan introduced the Specific Health Checkups and Specific Health Guidance policy in 2008. The policy mandates municipalities across Japan to standardize health checkups for all populations. This study explored how the policy and its resultant expansion in municipal healthcare funds have impacted health outcomes and lifestyle behaviors among self-employed and unemployed individuals.

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as variational autoencoders with infinitely many latent variables, reducing computational costs and preventing overfitting. By appropriately interrupting the training of the encoder, this approach enabled development of more efficient generative AI, with broad applicability beyond standard diffusion models.

A new class of highly efficient and scalable quantum low-density parity-check error correction codes, capable of performance approaching the theoretical hashing bound, has been developed by scientists at Institute of Science Tokyo, Japan. These novel error-correction codes can handle quantum codes with hundreds of thousands of qubits, potentially enabling large-scale fault-tolerant quantum computing, with applications in diverse fields, including quantum chemistry and optimization problems.

High-Density Lipoproteins (HDL), also known as “good cholesterol”, remove excess cholesterol from the body’s tissues and transport it to the liver. This process is known to prevent atherosclerosis, the build-up of plaque in the walls of arteries. Atherosclerosis is associated with deadly symptoms, including heart attacks, strokes, aneurysms, and blood clots. Despite the importance of HDLs, scientists still have a limited understanding of how they are made.