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Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations

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arXiv 2024年

作者： Lee, Jun-Young Kim, Ji-Hoon Jung, Minyong Oh, Boon Kiat Jo, Yongseok Park, Songyoun Lee, Jaehyun Ting, Yuan-Sen Hwang, Ho Seong Institute for Data Innovation in Science Seoul National University Seoul08826 Korea Republic of Center for Theoretical Physics Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Seoul National University Astronomy Research Center Seoul08826 Korea Republic of Department of Physics University of Connecticut StorrsCT06269 United States Columbia Astrophysics Laboratory Columbia University New YorkNY10027 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Korea Astronomy and Space Science Institute Daejeon34055 Korea Republic of Research School of Astronomy & Astrophysics Australian National University CanberraACT2611 Australia School of Computing Australian National University ActonACT2601 Australia Department of Astronomy The Ohio State University ColumbusOH43210 United States The Ohio State University ColumbusOH43210 United States Astronomy Program Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of

We present a proof-of-concept simulation-based inference on Ωm and σ8 from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid lightcone simulations, L-PICOLA, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network, Minkowski-PointNet. We also add relatively more accurate GADGET mocks to obtain robust and generalizable neural networks. By explicitly learning the representations which reduces the discrepancies between the two different datasets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find Ωm=0.339±0.056 and σ8=0.801±0.061, inferred only from the distribution of galaxies in the lightcone slices without relying on any indirect summary statistics. A single machine that best adapts to the GADGET mocks yields a tighter prediction of Ωm=0.282±0.014 and σ8=0.786±0.036. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data. © 2024, CC BY.

关键词： Cosmology

Assessing the reliability of wind power operations under a changing climate with a non-Gaussian bias correction

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arXiv 2020年

作者： Zhang, Jiachen Crippa, Paola Genton, Marc G. Castruccio, Stefano Department of Applied and Computational Mathematics and Statistics University of Notre Dame United States Department of Civid and Environmental Engineering and Geoscience University of Notre Dame United States Statistics Program King Abdullah University of Science and Technology Saudi Arabia

Facing increasing societal and economic pressure, many countries have established strategies to develop renewable energy portfolios, whose penetration in the market can alleviate the dependence on fossil fuels. In the case of wind, there is a fundamental question related to the resilience, and hence profitability, of future wind farms to a changing climate, given that current wind turbines have lifespans of up to thirty years. In this work we develop a new non-Gaussian method to adjust assimilated observational data to simulations and to estimate future wind, predicated on a trans-Gaussian transformation and a cluster-wise minimization of the Kullback-Leibler divergence. Future winds abundance will be determined for Saudi Arabia, a country with a recently established plan to develop a portfolio of up to 16 GW of wind energy. Further, we estimate the change in profits over future decades using additional high-resolution simulations, an improved method for vertical wind extrapolation and power curves from a collection of popular wind turbines. We find an overall increase in daily profit of $272,000 for the wind energy market for the optimal locations for wind farming in the country. Copyright © 2020, The Authors. All rights reserved.

关键词： Wind power

Inhibition of topoisomerase IIα and induction of DNA damage in cholangiocarcinoma cells by altholactone and its halogenated benzoate derivatives

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Biomedicine and Pharmacotherapy 2020年 127卷 110149-110149页

作者： Kitdumrongthum, Sarunya Reabroi, Somrudee Suksen, Kanoknetr Tuchinda, Patoomratana Munyoo, Bamroong Mahalapbutr, Panupong Rungrotmongkol, Thanyada Ounjai, Puey Chairoungdua, Arthit Toxicology Graduate Program Faculty of Science Mahidol University Bangkok Thailand Excellent Center for Drug Discovery (ECDD) Mahidol University Bangkok Thailand Department of Pharmacology Faculty of Science Mahidol University Bangkok Thailand Department of Physiology Faculty of Science Mahidol University Bangkok Thailand Department of Chemistry Faculty of Science Mahidol University Bangkok Thailand Structural and Computational Biology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok Thailand Department of Biology Faculty of Science Mahidol University Bangkok Thailand

Topoisomerase IIα enzyme (Topo IIα) plays a critical function in DNA replication process and is considered to be a promising target of anti-cancer drugs. In the present study, we reported that the altholactone derivatives modified by adding a halogenated benzoate group showed greater inhibitory activity on Topo IIα enzyme in cell-free system concomitant with cytotoxicity against the CCA cell lines (KKU-M055 and KKU-M213) than those of the parent altholactone. However, the cytotoxic activities of four halogenated benzoate altholactone derivatives including iodo-, fluoro-, chloro-, and bromobenzoate derivatives (compound 1, 2, 3, and 4, respectively) were of equal potency. The fluorobenzoate derivative (compound 2) was chosen for investigating the underlying mechanism in CCA cells. Compound 2 arrested CCA cell cycle at sub G1 phase and induced apoptotic cell death. It markedly inhibited Topo IIα protein expression in both KKU-M055 and KKU-M213 cells, which was accompanied by DNA double-strand breaks demonstrated by an increase in phosphorylated H2A.X protein. Interestingly, KKU-M055 cells, which express higher Topo IIα mRNA compared to KKU-M213 cells, showed greater sensitivity to the compound, indicating the selectivity of the compound to Topo IIα enzyme. By computational docking analysis, the binding affinity of altholactone (-52.5 kcal/mol) and compound 2 (-56.7 kcal/mol) were similar to that of the Topo II poison salvicine (-53.7 kcal/mol). The aromatic moiety of both altholactones embedded in a hydrophobic pocket of Topo II ATPase domain. In addition, compound 2 induced the formation of linear DNA in Topo II-mediated cleavage assay. Collectively, our results demonstrate that the addition of fluorobenzoyl group to altholactone enhances potency and selectivity to inhibit type IIα topoisomerases. Atholactone and fluorobenzoate derivative act as Topo II cleavage complexes stabilizing compounds or Topo II poisons preferentially through binding at ATPase domain of Topo

关键词： Altholactone Cholangiocarcinoma Halogenated benzoate Topoisomerase IIα

Hopper flows of deformable particles

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arXiv 2022年

作者： Cheng, Yuxuan Treado, John D. Lonial, Ben Habdas, Piotr Weeks, Eric R. Shattuck, Mark D. O'Hern, Corey S. Department of Physics Yale University New HavenCT06520 United States Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Department of Physics Emory University AtlantaGA30322 United States Department of Physics Saint Joseph's University PhiladelphiaPA19131 United States Benjamin Levich Institute Physics Department The City College of New York New YorkNY10031 United States Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States

Numerous experimental and computational studies show that continuous hopper flows of granular materials obey the Beverloo equation that relates the volume flow rate Q and the orifice width w: Q ∼ (w/σavg − k)β, where σavg is the average particle diameter, kσavg is an offset where Q ∼ 0, the power-law scaling exponent β = d − 1/2, and d is the spatial dimension. Recent studies of hopper flows of deformable particles in different background fluids suggest that the particle stiffness and dissipation mechanism can also strongly affect the power-law scaling exponent β. We carry out computational studies of hopper flows of deformable particles with both kinetic friction and background fluid dissipation in two and three dimensions. We show that the exponent β varies continuously with the ratio of the viscous drag to the kinetic friction coefficient, λ = ζ/µ. β = d−1/2 in the λ → 0 limit and d− 3/2 in the λ → ∞ limit, with a midpoint λc that depends on the hopper opening angle θw. We also characterize the spatial structure of the flows and associate changes in spatial structure of the hopper flows to changes in the exponent β. The offset k increases with particle stiffness until k ∼ kmax in the hard-particle limit, where kmax ∼ 3.5 is larger for λ → ∞ compared to that for λ → 0. Finally, we show that the simulations of hopper flows of deformable particles in the λ → ∞ limit recapitulate the experimental results for quasi-2D hopper flows of oil droplets in water. © 2022, CC BY.

关键词： Stiffness

Hyperuniformity of generalized random organization models

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Physical Review E 2019年第2期99卷 022115-022115页

作者： Zheng Ma Salvatore Torquato Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Studies of random organization models of monodisperse (i.e., identical) spherical particles have shown that a hyperuniform state is achievable when the system goes through an absorbing phase transition to a critical state. Here we investigate to what extent hyperuniformity is preserved when the model is generalized to particles with a size distribution and/or nonspherical shapes. We begin by examining binary disks in two dimensions and demonstrate that their critical states are hyperuniform as two-phase media, but not hyperuniform nor multihyperuniform as point patterns formed by the particle centroids. We further confirm the generality of our findings by studying particles with a continuous size distribution. Finally, to study the effect of rotational degrees of freedom, we extend our model to noncircular particles, namely, hard rectangles with various aspect ratios, including the hard-needle limit. Although these systems exhibit only short-range orientational order, hyperuniformity is still preserved. Our analysis reveals that the redistribution of the “mass” of the particles rather than the particle centroids is central to this dynamical process. The consideration of the “active volume fraction” of generalized random organization models may help to resolve which universality class they belong to and hence may lead to a deeper theoretical understanding of absorbing-state models. Our results suggest that general particle systems subject to random organization can be a robust way to fabricate a wide class of hyperuniform states of matter by tuning the structures via different particle-size and -shape distributions. This in turn potentially enables the creation of multifunctional hyperuniform materials with desirable optical, transport, and mechanical properties.

关键词： Classical statistical mechanics

Global genetic diversity, introgression, and evolutionary adaptation of indicine cattle revealed by whole genome sequencing

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NATURE COMMUNICATIONS 2023年第1期14卷 1-13页

作者： Chen, Ningbo Xia, Xiaoting Hanif, Quratulain Zhang, Fengwei Dang, Ruihua Huang, Bizhi Lyu, Yang Luo, Xiaoyu Zhang, Hucai Yan, Huixuan Wang, Shikang Wang, Fuwen Chen, Jialei Guan, Xiwen Liu, Yangkai Li, Shuang Jin, Liangliang Wang, Pengfei Sun, Luyang Zhang, Jicai Liu, Jianyong Qu, Kaixing Cao, Yanhong Sun, Junli Liao, Yuying Xiao, Zhengzhong Cai, Ming Mu, Lan Siddiki, Amam Zonaed Asif, Muhammad Mansoor, Shahid Babar, Masroor Ellahi Hussain, Tanveer Silva, Gamamada Liyanage Lalanie Pradeepa Gorkhali, Neena Amatya Terefe, Endashaw Belay, Gurja Tijjani, Abdulfatai Zegeye, Tsadkan Gebre, Mebrate Genet Ma, Yun Wang, Yu Huang, Yongzhen Lan, Xianyong Chen, Hong Migliore, Nicola Rambaldi Colombo, Giulia Semino, Ornella Achilli, Alessandro Sinding, Mikkel-Holger S. Lenstra, Johannes A. Cheng, Haijian Lu, Wenfa Hanotte, Olivier Han, Jianlin Jiang, Yu Lei, Chuzhao Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi Province College of Animal Science and Technology Northwest A&F University Yangling 712100 China Institute of Animal Science and Veterinary Medicine Shandong Academy of Agricultural Sciences Shandong Key Lab of Animal Disease Control and Breeding Jinan 250100 China Key Laboratory of Livestock Biology Northwest A&F University Yangling 712100 China National Institute for Biotechnology and Genetic Engineering Faisalabad 38000 Pakistan CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources Institute of Animal Science Chinese Academy of Agricultural Sciences (CAAS) 100193 Beijing China Livestock Genetics Program International Livestock Research Institute (ILRI) 00100 Nairobi Kenya Yazhouwan National Laboratory Sanya 572024 China Yunnan Academy of Grassland and Animal Science Kunming 650212 China Institute for Ecological Research and Pollution Control of Plateau Lakes School of Ecology and Environment Science Yunnan University Kunming 650500 China Academy of Science and Technology Chuxiong Normal University Chuxiong 675000 China Guangxi Vocational University of Agriculture Nanning 530007 China Guangxi Veterinary Research Institute Guangxi Key Laboratory of Veterinary Biotechnology Nanning 530001 China College of Landscape and Horticulture Southwest Forestry University Kunming 650224 China Genomics Research Group Department of Pathology and Parasitology Faculty of Veterinary Medicine Chattogram Veterinary and Animal Sciences University (CVASU) Chattogram 4225 Bangladesh The University of Agriculture Dera Ismail Khan Khyber Pakhtunkhwa 29050 Pakistan Department of Molecular Biology Virtual University of Pakistan Islamabad 44100 Pakistan Department of Animal Science University of Peradeniya Peradeniya 20400 Sri Lanka National Animal Breeding and Genetics Centre National Animal Science Research Institute Nepal Agriculture Research Council Khumaltar Lalitpur 45200

Indicine cattle, also referred to as zebu (Bos taurus indicus), play a central role in pastoral communities across a wide range of agro-ecosystems, from extremely hot semiarid regions to hot humid tropical regions. However, their adaptive genetic changes following their dispersal into East Asia from the Indian subcontinent have remained poorly documented. Here, we characterize their global genetic diversity using high-quality whole-genome sequencing data from 354 indicine cattle of 57 breeds/populations, including major indicine phylogeographic groups worldwide. We reveal their probable migration into East Asia was along a coastal route rather than inland routes and we detected introgression from other bovine species. Genomic regions carrying morphology-, immune-, and heat-tolerance-related genes underwent divergent selection according to Asian agro-ecologies. We identify distinct sets of loci that contain promising candidate variants for adaptation to hot semi-arid and hot humid tropical ecosystems. Our results indicate that the rapid and successful adaptation of East Asian indicine cattle to hot humid environments was promoted by localized introgression from banteng and/or gaur. Our findings provide insights into the history and environmental adaptation of indicine cattle.

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Heterogeneous photocatalytic degradation of diuron on zinc oxide: Influence of surface-dependent adsorption on kinetics,degradation pathway,and toxicity of intermediates

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Journal of Environmental sciences 2019年第10期31卷 97-111页

作者： Sutaporn Meephon Thanyada Rungrotmongkol Somchintana Puttamat Supareak Praserthdam Varong Pavarajarn Center of Excellence in Particle Technology Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok 10330 Thailand Biocatalyst and Environmental Biotechnology Research Unit Department of Biochemistry Faculty of Science Chulalongkorn UniversityBangkok 10330 Thailand Bioinformatics and Computational Biology Program Graduated School Chulalongkorn University Bangkok 10330 Thailand Department of Chemistry Faculty of Science Thammasat University Pathumthani 12120 Thailand Center of Excellence on Catalysis and Catalytic Reaction Engineering Department of Chemical Engineering Faculty of EngineeringChulalongkorn University Bangkok 10330 Thailand Research Program in Hazardous Substance Management in Agricultural Industry Center of Excellence on Hazardous Substance Management(HSM) Bangkok 10330 Thailand

Heterogeneous photocatalytic reaction has been generally applied for degradation of toxic *** of a compound using the same kind of catalyst that was synthesized differently are commonly found in ***,the reported degradation intermediates are normally *** issue is especially important for the degradation of toxic compounds because intermediates may be more toxic than their parent compounds and understanding the reason is necessary if appropriate catalysts are to be *** work systematically compares the photocatalytic degradation of diuron,a toxic recalcitrant herbicide,on two forms of zinc oxide(ZnO),i.e.,conventional particles with zinc-and oxygen-terminated polar surfaces as the dominating planes,and nanorods with mixed-terminated nonpolar *** and theoretical results indicate that both the rate of reaction and the degradation pathway depend on the adsorption configuration of diuron onto the *** molecules adsorb in different alignments on the two surfaces,contributing to the formation of different degradation *** the aliphatic and aromatic sides of diuron adsorb on the polar surfaces simultaneously,leading to an attack by hydroxyl radicals from both *** the other hand,on the mixed-terminated surface,only the aliphatic part adsorbs and is *** exposed surface is therefore the key factor controlling the degradation *** diuron degradation on ZnO,a catalyst confined tomixed-terminated surfaces,i.e.,ZnO nanorods,is more desirable,as it avoids the formation of intermediates with potent phytotoxicity and cytogenotoxicity.

关键词： Diuron Photocatalysis Adsorption Degradation pathway Mechanism Toxicity

Transferable Learning of Reaction Pathways from Geometric Priors

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arXiv 2025年

作者： Nam, Juno Steiner, Miguel Misterka, Max Yang, Soojung Singhal, Avni Gómez-Bombarelli, Rafael Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Energy Storage Research Alliance Argonne National Laboratory 9700 South Cass Avenue LemontIL60439 United States Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States Computational and Systems Biology Program Massachusetts Institute of Technology CambridgeMA02139 United States

Identifying minimum-energy paths (MEPs) is crucial for understanding chemical reaction mechanisms but remains computationally demanding. We introduce MEPIN, a scalable machine-learning method for efficiently predicting MEPs from reactant and product configurations, without relying on transition-state geometries or pre-optimized reaction paths during training. The task is defined as predicting deviations from geometric interpolations along reaction coordinates. We address this task with a continuous reaction path model based on a symmetry-broken equivariant neural network that generates a flexible number of intermediate structures. The model is trained using an energy-based objective, with efficiency enhanced by incorporating geometric priors from geodesic interpolation as initial interpolations or pre-training objectives. Our approach generalizes across diverse chemical reactions and achieves accurate alignment with reference intrinsic reaction coordinates, as demonstrated on various small molecule reactions and [3+2] cycloadditions. Our method enables the exploration of large chemical reaction spaces with efficient, data-driven predictions of reaction pathways. Copyright © 2025, The Authors. All rights reserved.

关键词： Reaction intermediates

Nuclear Neural Networks: Emulating Late Burning Stages in Core Collapse Supernova Progenitors

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arXiv 2025年

作者： Grichener, Aldana Renzo, Mathieu Kerzendorf, Wolfgang E. Farmer, Rob de Mink, Selma E. Bellinger, Earl Patrick Chan, Chi-Kwan Chen, Nutan Farag, Ebraheem Justham, Stephen Steward Steward Observatory Department of Astronomy University of Arizona 933 North Cherry Avenue TucsonAZ85721 United States Max Planck Institute for Astrophysics Karl-Schwarzschild-Str. 1 Garching85748 Germany Department of Physics Technion Haifa3200003 Israel Department of Computational Mathematics Science and Engineering Michigan State University East LansingMI48824 United States Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Ludwig-Maximilians-Universitat Munchen Geschwister-Scholl-Platz 1 Munchen80539 Germany Department of Astronomy Yale University New HavenCT06511 United States Steward Observatory Department of Astronomy University of Arizona 933 North Cherry Avenue TucsonAZ85721 United States Data Science Institute University of Arizona 1230 N. Cherry Avenue TucsonAZ85721 United States Program in Applied Mathematics University of Arizona 617 North Santa Rita TucsonAZ85721 United States Machine Learning Research Lab Volkswagen AG Munich38440 Germany

One of the main challenges in modeling massive stars to the onset of core collapse is the computational bottleneck of nucleosynthesis during advanced burning stages. The number of isotopes formed requires solving a large set of fully-coupled stiff ordinary differential equations (ODEs), making the simulations computationally intensive and prone to numerical instability. To overcome this barrier, we design a nuclear neural network (NNN) framework with multiple hidden layers to emulate nucleosynthesis calculations and conduct a proof-of-concept to evaluate its performance. The NNN takes the temperature, density and composition of a burning region as input and predicts the resulting isotopic abundances along with the energy generation and loss rates. We generate training sets for initial conditions corresponding to oxygen core depletion and beyond using large nuclear reaction networks, and compare the predictions of the NNNs to results from a commonly used small net. We find that the NNNs improve the accuracy of the electron fraction by 280 − 660 % and the nuclear energy generation by 250 − 750 %, consistently outperforming the small network across all timesteps. They also achieve significantly better predictions of neutrino losses on relatively short timescales, with improvements ranging from 100 − 106 %. While further work is needed to enhance their accuracy and applicability to different stellar conditions, integrating NNN trained models into stellar evolution codes is promising for facilitating large-scale generation of core-collapse supernova (CCSN) progenitors with higher physical fidelity. © 2025, CC BY.

关键词： Nucleosynthesis