Breakthroughs, discoveries, and DIY tips sent six days a week. Ladybugs are famously harbingers of good luck, and the trait proved consistent at a university in Japan when researchers found a new species of the iconic insect directly on the campus. Ladybugs, also known as ladybird beetles or lady beetles, consist of the family within the order of beetles (). The newly identified member is a black, and researchers discovered it on a pine tree at Kyushu University's Hakozaki Satellite. In fact, its species name means "pine dweller."

Tinglesbar incorporates ASMR into elementary school and doctor's visits simulations, offering a social haven for introverts. "It's time for your lice check," a woman who goes by "Ms. K" whispers directly into my ear as she starts running her fingers into my scalp and through each strand of hair. I'm in a dark room, Eastern flute music playing in the background as I sit across from my partner who's also having his hair caressed by a stranger. We close our eyes so we don't burst out laughing.

We introduce SEKI, a novel large language model (LLM)-based neural architecture search (NAS) method. Inspired by the chain-of-thought (CoT) paradigm in modern LLMs, SEKI operates in two key stages: self-evolution and knowledge distillation. In the self-evolution stage, LLMs initially lack sufficient reference examples, so we implement an iterative refinement mechanism that enhances architectures based on performance feedback. Over time, this process accumulates a repository of high-performance architectures. In the knowledge distillation stage, LLMs analyze common patterns among these architectures to generate new, optimized designs. Combining these two stages, SEKI greatly leverages the capacity of LLMs on NAS and without requiring any domain-specific data. Experimental results show that SEKI achieves state-of-the-art (SOTA) performance across various datasets and search spaces while requiring only 0.05 GPU-days, outperforming existing methods in both efficiency and accuracy. Furthermore, SEKI demonstrates strong generalization capabilities, achieving SOTA-competitive results across multiple tasks.

Game solving is the process of finding the theoretical outcome for a game, assuming that all player choices are optimal. This paper focuses on a technique that can reduce the heuristic search space significantly for 7x7 Killall-Go. In Go and Killall-Go, live patterns are stones that are protected from opponent capture. Mutual life, also referred to as seki, is when both players' stones achieve life by sharing liberties with their opponent. Whichever player attempts to capture the opponent first will leave their own stones vulnerable. Therefore, it is critical to recognize seki patterns to avoid putting oneself in jeopardy. Recognizing seki can reduce the search depth significantly. In this paper, we enumerate all seki patterns up to a predetermined area size, then store these patterns into a seki table. This allows us to recognize seki during search, which significantly improves solving efficiency for the game of Killall-Go. Experiments show that a day-long, unsolvable position can be solved in 482 seconds with the addition of a seki table. For general positions, a 10% to 20% improvement in wall clock time and node count is observed.

Almost half a century after founding his pioneering motor-maker on the family farm, Japanese billionaire Shigenobu Nagamori is handing over leadership of Nidec Corp. to a former Nissan Motor Co. executive to lead an ambitious pivot into the electric-vehicle space. Jun Seki will take over from Nagamori as chief executive officer, the Kyoto-based company said last week as it announced better-than-projected annual results. The leadership change, which comes a little over a year after Seki's move from Nissan, will be finalized when Nidec's board meets June 22. Nagamori, who founded Nidec in a shack in 1973, will remain chairman. Seki, 59, was appointed president of Nidec after leaving Nissan, where he was vice chief operating officer and an unsuccessful contender for CEO after Hiroto Saikawa resigned amid a compensation scandal, following the shock arrest of former chairman Carlos Ghosn.

Almost half a century after founding his pioneering motor maker on the family farm, Japanese billionaire Shigenobu Nagamori is handing over leadership of Nidec Corp. to a former Nissan Motor Co. executive to lead an ambitious pivot into the electric-vehicle space. Jun Seki will take over from Nagamori as chief executive officer, the Kyoto-based company said last week as it announced better-than-projected annual results. The leadership change, which comes a little over a year after Seki's move from Nissan, will be finalized when Nidec's board meets June 22. Nagamori, who founded Nidec in a shack in 1973, will remain chairman. Seki, 59, was appointed president of Nidec after leaving Nissan, where he was vice chief operating officer and an unsuccessful contender for CEO after Hiroto Saikawa resigned amid a compensation scandal, following the shock arrest of former chairman Carlos Ghosn.

The first step to realize automatic experimental data analysis for fusion plasma experiments is fitting noisy data of temperature and density spatial profiles, which are obtained routinely. However, it has been difficult to construct algorithms that fit all the data without over- and under-fitting. In this paper, we show that this difficulty originates from the lack of knowledge of the probability distribution that the measurement data follow. We demonstrate the use of a machine learning technique to estimate the data distribution and to construct an optimal generative model. We show that the fitting algorithm based on the generative modeling outperforms classical heuristic methods in terms of the stability as well as the accuracy.

Wanda Tuerlinckx and Erwin R. Boer have fused their scientific and photographic interests in robots and traveled the world since 2016 to visit roboticists to discuss and photograph their creations. The resulting set of photographs documents the technical robot revolution that is unfolding before us. The portfolio of photographs below presents the androids from Wanda's collection of robot photographs. But first, here's a note from Erwin R. Boer, a scientist who connects humans and machines using symbiosis facilitating techniques mirrored after the way humans interact with each other in the here and now. Man has created machines in the form of mechanical humans since antiquity.