Why Japan chose to promote AI rather than regulate it — and where that strategy hits its limits
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Updates every hour. Last Updated: 20-Oct-2026 18:16 ET (20-Oct-2026 22:16 GMT/UTC)
Japan's first comprehensive AI law puts "promotion" rather than regulation at its core. A new study in Risk Sciences traces this choice to Japan's distinctive social conditions – low AI adoption, low public trust, an ageing population and ageing corporate IT systems – and finds that promotional measures have boosted individual use and corporate trials, but have not yet driven deep integration of AI inside organisations.
Researchers find rutin alleviates acrylamide‑triggered cerebellar neuron injury and movement disorders in rats. Protection works by reducing oxidative stress and activating PI3K/AKT signaling, offering clues for preventing food‑linked neurotoxicity.
Researchers have developed a dynamic approach to improve the deployment of healthcare workers during disease outbreaks. By considering uncertain medical demand, changing healthcare capacity, and infection risks among healthcare staff, the model helps decision-makers allocate medical resources more effectively across regions. The study provides a practical framework for improving healthcare system resilience and supporting timely responses to public health emergencies.
This study proposes a novel transmission framework that integrates a nonlinear companding-based PAPR reduction method with the Digital Post-Distortion (DPoD) technique to balance power efficiency and Bit Error Rate (BER) performance. To recover the transmitted signals, a Successive Decision Feedback Nonlinearity Equalizer (SDFNE) is developed at the receiver side. The SDFNE employs a time-domain least squares equalizer with closed-loop iterative feedback to jointly mitigate companding distortion and PA nonlinearity. The proposed framework balances transmitter-side PAPR suppression and receiver-side nonlinear equalization. This enables the PA to operate closer to its saturation point while achieving excellent BER performance. Meanwhile, compliance with spectral emission mask requirements is maintained. Numerical results on diverse PA models demonstrate that the proposed transmission framework with the SDFNE method significantly outperforms conventional nonlinear signal processing methods, including nonlinear companding, digital predistortion, and DPoD. Superior BER performance is achieved in a power-efficient manner, making the proposed framework particularly suitable for resource-constrained communication systems.
This study proposes a novel Alamouti-Orthogonal Frequency Division Multiplexing (OFDM) system that mitigates constructive and destructive interference in practical multi-antenna wireless communications. Experimental results across multiple scenarios demonstrate that, under spatial misalignment, the Alamouti-OFDM system provides a maximum Signal-to-Noise Ratio (SNR) gain of 3.45 dB over traditional diversity transmission systems; in scenarios where traditional methods exhibit > 10 dB spectral fluctuations, our system confines the spectral variations of the received signals within 2 dB.
A new study examines how limited parking affects electric vehicle commuters and shows that parking permit schemes can reduce inefficient competition for spaces. By modelling commuting, charging and parking decisions across multiple travel corridors, the researchers find that carefully designed permit allocation can lower system-wide travel costs while revealing important trade-offs between efficiency and equity.
Researchers created a nationwide pollution snapshot of 4 diamide insecticides (DAIs) across 47 cities and 9 major Chinese river basins. Cyantraniliprole (CYTP) was the most abundant, but broflanilide (BFA) produced the highest screening-level concern for benthic midges because its species-specific chronic threshold was lower. Crop-use patterns shaped regional composition patterns. Children’s modeled cumulative exposure from raw surface-water ingestion was 2.4 times the adults’ value, although all hazard quotients remained below 1.
Under universal health coverage, allocating antidepressant benefits requires balancing health costs, clinical efficacy, and patient financial protection. We propose a dual societal–household disease-burden optimization framework and a triple-population cooperative particle swarm algorithm. Validated on real-world data from City S, China, the optimized reimbursement package cuts household out-of-pocket spending by up to 48.97% per unit treatment effect, offering a transferable decision-support tool for mental health financing and health equity in low- and middle-income countries.