Institute of Natural Science (INS) is a university located inside the region of the National Academy of Science in Pyongyang, North Korea. INS is geographically located in Pyongsong, South Pyong'an Province, North Korea. However, North Korean government appointed the area of science district to belong to Pyongyang for giving some privileges of Pyongyang citizens to scientists of NAS and students of INS. As Kim Il-sung, a former leader of North Korea, emphasized the significance of education for gifted and talented students, INS originally started as a branch of Kim Il-sung University on January 17, 1962. It was separated from Kim Il-sung University in 1985. In North Korea, this university is known as "Sujae Daehark (University for talented students)". In South Korean mass media, this university is called "KAIST of North Korea".Top students of natural sciences or engineering in North Korea study at this university supported totally by North Korean government. Eighty percent of them is graduated from No.1 Middle Schools, which are science high schools for gifted and talented students in North Korea, and the rest twenty percent are medal winners in the National Science Olympiads (math, physics, chemistry, and biology) or national science quiz contests. Unlike other universities in North Korea, students entering UNS have age limit. Equal or younger than 17 people are eligible to take entrance exam for INS.It is known that many alumni of this university are involved in projects for developing missiles and launching artificial earth satellites.
Stereoselective construction of 1,2-cis beta-glycosidic linkages, especially beta-manno-/rhamnosidic bonds, is extremely challenging due to their unfavorable stereoelectronic nature and inapplicability of neighboring group participation. Herein, we disclose a convenient and highly stereoselective glycosylation protocol toward beta-manno-/rhamnosides employing tetrahydrofuran (THF) as a stereomodulating additive. This method features high yield and good to exclusive beta-selectivity, without resorting to the previous devices requiring stereodirecting groups or fixed anomeric configuration of the donors. Mechanistic studies indicate a novel THF participation mechanism in which the THF-derived alpha-mannosyl oxonium intermediate is rapidly formed and thus favors the following generation of beta-glycoside product in a stereoinvertive manner.
A structure-activity relationship (SAR) study employing multivariate image analysis (MIA) descriptors was performed to cluster benzothiazole derivatives, including herbicide-like compounds, by structural similarity and protoporphyrinogen oxidase IX (PPO) inhibition. Partial least-squares (PLS) models based on van der Waals radii and electronegativity descriptors identified substituents most influential for activity through MIA contour maps of regression coefficients and VIP scores. A genetic algorithm selected key descriptors for a simplified multiple linear regression (MLR) model enabling rapid pK i prediction. Both the PLS and MLR models were robust and predictive (r 2 = 0.85-0.88, q 2 = 0.75-0.83, r 2 pred = 0.77-0.86). A proposed compound (P12) showed predicted activity (pK i = 7.93) comparable to the most potent derivative (pK i = 8.14) but higher lipophilicity (log P = 5.45 vs 4.55), suggesting improved leaf membrane permeation. These results demonstrate the usefulness of MIA-based modeling for designing potent, permeable PPO inhibitors. In addition, a molecular docking study and molecular dynamics simulations were performed to investigate the PPO binding mode, validating the MIA-QSAR model specification. Key residues were identified, and strong thickness and stability of the candidates were observed. A proposed derivative showed greater potential than the library compounds, and a synthetic route for its production was suggested.
Niobium-based oxides are promising high-energy-density anodes (>300 mAh g(-1) at 1.0-2.0 V vs Li+/Li) but face challenges with conventional aqueous electrolytes. Herein, we develop a cost-effective, dilute aqueous electrolyte modulated by methylurea (MU), a nonflammable, low-toxicity cosolvent. Leveraging its donor-acceptor amphiphilicity and structural asymmetry, MU enhances miscibility with salt and water, enabling a 2.6 m solution with a distinctive solvation structure: an inner sheath dominated by MU and anions, and an outer layer where water is anchored by MU. This configuration reduces water activity and promotes a robust organic-inorganic interphase, effectively suppressing hydrogen evolution and extending the cathodic stability limit to 1.2 V vs Li+/Li. Pouch cells of NbO2|LiCoO2 and NbO2|LiMn2O4 show 96% capacity retention after 24 h at 100% state of charge, along with stable cycling over 150 cycles at 0.25 C. This strategy enhances aqueous battery performance while maintaining safety and cost-efficiency, advancing practical implementation.
Large language models (LLMs) have gained broad applications across various domains but still struggle with hallucinations. Currently, hallucinations occur frequently in the generation of factual content and pose a great challenge to trustworthy LLMs. However, hallucination detection is hindered by the laborious and expensive manual annotation of hallucinatory content. Meanwhile, as different LLMs exhibit distinct types and rates of hallucination, the collection of hallucination datasets is inherently model-specific, which also increases the cost. To address this issue, this paper proposes a method called AutoHall for Automatically constructing model-specific Hallucination datasets based on existing fact-checking datasets. The empirical results reveal variations in hallucination proportions and types among different models. Moreover, we introduce a zero-resource and black-box hallucination detection method based on self-contradiction to recognize the hallucination in our constructed dataset, achieving superior detection performance compared to baselines. Further analysis on our dataset provides insight into factors that may contribute to LLM hallucinations.
Ecosystem engineers impact ecosystems by changing the physical environment in which species interact. In Lake Mývatn, Iceland, larvae of the midge Tanytarsus gracilentus function as ecosystem engineers by building tubes in the sediment that solidify the benthic surface and create a 3-dimensional structure on which microalgae can grow. To assess the ecosystem-scale effect of midge engineering, we took advantage of the natural high-amplitude fluctuations in T. gracilentus over a 13-year time series. We combined larval abundance data with benthic primary production under saturating light conditions (Pmax) and pelagic in situ gross primary production (GPP) measured on average 8.4 times per summer. T. gracilentus abundance had a positive effect on benthic Pmax, as expected from their ecosystem engineering, while pelagic GPP had a negative effect on benthic Pmax, reflecting competition from phytoplankton. A complementary analysis of five replicate sediment cores taken on each of 26 sampling days of the time series shows a quantitatively similar positive effect of local-scale variation in larval midge abundance on benthic net ecosystem production (NEP) in space. Finally, we reanalyzed data from an experiment manipulating light levels and the presence/absence of midge larvae to show that larval engineering increased benthic NEP more at low than at high light levels. This indicates that at least part of the positive engineering effect of midges on benthic Pmax arises from amelioration of light limitation through self-shading, likely due to the structure created by midge tubes. These results show that Mývatn's high benthic primary productivity is due not only to high inputs of nutrients but also to the ecosystem engineering of tube-forming midges.
