jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Elumalai Jayaprasath | Mohammed Salih | Martyn Fice | A. Brown | L. H. Li | Edmund H. Linfield | A. Valavanis | A.J. Seeds | Alexander Giles Davies | Joshua R. Freeman
Source: Communications Physics (article, 2026-02-04)
Field: Chemistry — Spectroscopy

Free-space optical communications at 4 Gbit/s data rate with a terahertz laser Terahertz-frequency (THz) carrier waves in free-space optical (FSO) communications offer the potential for > 1 Tbit/s data rates and stable latency. They offer wider bandwidths than available in the microwave region, together with reduced scattering and relaxed pointing requirements compared with visible and near-infrared regions. However, 1-10 THz FSO communications systems have thus far been limited to data rates several orders of magnitude lower than those of infrared systems. This work describes an experimental demonstration of multi-gigabit-per-second FSO communication using a THz quantum cascade laser (QCL), opening a new frontier for next-generation wireless communications. The FSO communication system consists of a 2.4 THz QCL source as the transmitter and a room-temperature Schottky barrier diode detector as the receiver. By directly modulating the terahertz QCL, we achieved non-return-to-zero on-off keying (NRZ-OOK) with a transmission rate of up to 4 Gbit/s. We evaluated the performance of the communication link by analyzing the bit error rate (BER) of the demodulated signal at the receiver while examining its relation to received optical power, QCL modulation power, and various bias points. Our work establishes the foundation for high-speed optical wireless communication based on terahertz QCL technology systems. Terahertz radiation ; Optical communication ; Optical wireless communications ; Transmission (telecommunications) ; Laser ; Bit error rate ; Communications system ; Detector ; Microwave ; Transmitter Spectroscopy and Laser Applications ; Optical Wireless Communication Technologies ; Semiconductor Lasers and Optical Devices
Authors: M. N. Moskovsky | M. V. Belyakov | I. Yu. Efrremenkov
Source: Grain Economy of Russia (article, 2026-01-18)
Field: Chemistry — Analytical Chemistry

Photoluminescent diagnostics of chickpeas High-quality seed material is a critical factor in the efficient production of grain and its products. Producing high-quality products requires more plant protein, a source of which is chickpeas. Quality control, which can be accomplished using optical methods, is of great importance when storing grain and seeds. The purpose of the current study was to validate the selection of informative spectral parameters to develop a photoluminescence diagnostic method for chickpeas. There were studied the optical spectral luminescence properties of middle-maturing chickpeas ‘Pamyat’ harvested in 2024, 2019, and 2017. Optical measurements were performed using a diffraction spectrum fluorimeter ‘CM2203’. There have been obtained excitation (absorption) and luminescence spectra. Chickpea excitation was in the range of 250–550 nm, with maxima at 362 and 424 nm for all samples studied. The greatest difference in the integral absorption parameter was in the excitation range of 370–500 nm. There were obtained integral parameters of the luminescence spectra at excitation wavelengths of 362 and 424 nm. Integral photoluminescence fluxes depended on storage time and percentage of protein and oil in seed. The error in determining the fluxes did not exceed 4.5 %. The most informative excitation wavelength was selected based on the condition of the maximum photo signal level, minimum error in determining the flux, and the greatest flux increase for different values of protein and oil percentage. The optimal excitation wavelength was 424 nm. The photoluminescence emission detection range for this excitation wavelength was 480–650 nm. The results obtained could form the basis to develop a photoluminescence method for monitoring chickpea parameters during long-term storage. Photoluminescence ; Fluorometer ; Photoluminescence excitation ; Excitation ; Luminescence ; Wavelength ; Quality (philosophy) ; Excitation wavelength Spectroscopy and Chemometric Analyses ; Proteins in Food Systems ; Genetic and Environmental Crop Studies
Authors: Quan Zhou | Shijian Zheng | Jing Zhang | Benyou Wang
Source: Agriculture (article, 2026-01-12)
Field: Chemistry — Analytical Chemistry

Hyperspectral Wavelength Selection Based on Inter-Class Feature Differences for Maize Seed Age Discrimination Maize is a globally major crop; however, the prevalence of mixed-aged seeds in the market complicates consumer selection and impedes the healthy development of the maize industry. This study introduces a novel method for identifying maize seeds of different storage ages. Seeds were categorized into three age groups: new seeds, one-year stored, and two-year stored, with 300 seeds per group. Hyperspectral images of all 900 samples were acquired using a visible and near-infrared (Vis-NIR) hyperspectral imaging system. To achieve optimal results with minimal spectral data, a feature wavelength selection algorithm based on Inter-Class Feature Differences (IFD) was proposed. When only using the selected three key wavelengths, combined with the linear discriminant analysis (LDA) algorithm, the discrimination accuracy among three different age groups reached 85.67%, while the discrimination accuracy between new and aged seeds achieved 95.33%. Compared to two commonly used variable selection algorithms—Successive Projections Algorithm (SPA) and Random Frog (RF), the proposed IFD method demonstrated superior performance when only a limited number of key wavelengths were used for modeling. These results indicate that the proposed algorithm offers an effective and efficient solution for maize seed age discrimination, showing great potential for practical application. Hyperspectral imaging ; Feature selection ; Pattern recognition (psychology) ; Linear discriminant analysis ; Selection (genetic algorithm) ; Feature (linguistics) ; Variable (mathematics) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Source: International journal of intelligent engineering and systems (article, 2026-02-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modeling and Simulation of a 132/33 kV, 63 MVA Transformer Using the Jiles–Atherton Hysteresis Model for Inrush Current Analysis and Protection Enhancement Power transformers exhibit nonlinear magnetic behavior that significantly affects their transient response during energization, particularly through magnetizing inrush currents that may exceed 6-8 times the rated current.This study develops a detailed simulation model of a 132/33 kV, 63 MVA three-phase transformer using the Jiles-Atherton (JA) hysteresis model to accurately represent core saturation, residual flux, coercivity, and irreversible magnetization.The JA parameters were optimized by minimizing the error between simulated and factory test results.The final calibrated model achieved excellent agreement with manufacturer data, with a magnetizing current error of 0.54% (3.68A simulated vs. 3.70 A factory) and a core loss error of 0.27% (220.9 kW simulated vs. 221.5 kW factory).The model was applied to analyze inrush current behavior under various switching conditions.Without control, the peak inrush current reached values typical of 6-7 pu and exhibited strong asymmetry due to residual flux.To mitigate this, a Smart Reclosing Strategy (SRS) based on JA-derived residual flux prediction was introduced.Simulation results show that optimal reclosing at 45 reduces peak inrush magnitude by more than 50% compared with traditional 0 closing, while significantly improving waveform symmetry and damping characteristics.These results confirm that the combination of high-fidelity JA hysteresis modeling and an optimized reclosing strategy enhances transformer transient prediction accuracy, reduces inrush-related mechanical and electrical stress, and improves protection system selectivity. Inrush current ; Modeling and simulation ; Transformer ; Hysteresis ; Current (fluid) Magnetic Properties and Applications ; Power Systems Fault Detection ; Magnetic Field Sensors Techniques
Authors: Mingming Chen | Cai Ju | Hui Wang | Fang-Zhou Shu | Huanyang Chen | Qingdong Ou
Source: Frontiers of Physics (article, 2026-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Flexible terahertz metasurfaces with ultra-large incident angle tolerance and mechanical adaptability Metasurfaces operating under oblique incidence conditions have attracted considerable interest in modern photonic engineering, owing to their capability to enhance angular coverage for next-generation devices including wide-field detectors, multi-angle communication arrays, and advanced radar architectures. However, conventional metasurfaces frequently suffer from limitations in preserving functional stability at high incidence angles, where performance deterioration typically stems from reduced coupling efficiency and phase mismatch. This work proposes flexible terahertz metasurfaces with an ultra-large incident angle, addressing the limitations of conventional metasurfaces that suffer from severe performance degradation under high angles and lack mechanical adaptability. The proposed metasurfaces are designed through the synergistic integration of spoof localized surface plasmons (S-LSPs) and electromagnetically induced transparency (EIT). Experimental results demonstrate that the metasurfaces exhibit polarization-insensitive behavior while maintaining stable transmission spectra under oblique incidence up to 80°. Furthermore, bending tests confirm that the transmission spectrum of the metasurfaces remains stable even under significant mechanical deformation (with a maximum central angle of 111.7°). The proposed flexible metasurfaces provide a novel design paradigm for oblique-incident metasurfaces, holding great potential for emerging applications in conformal terahertz systems and adaptive wearable photonics. Terahertz radiation ; Transmission (telecommunications) ; Plasmon ; Photonics ; Bending ; Angle of incidence (optics) ; Metamaterial ; Adaptability ; Radar Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Advanced Antenna and Metasurface Technologies
Authors: M. K. Pawelkiewicz | Filippo Gatti | Didier Clouteau | Viatcheslav Kokoouline | Mehdi Adrien Ayouz
Source: Atoms (article, 2026-03-19)
Field: Materials Science — Materials Chemistry

Correction: Pawelkiewicz et al. Introducing Machine Learning in Teaching Quantum Mechanics. Atoms 2025, 13, 66 Missing Supplementary Materials [...] Quantum ; Algebra over a field ; Quantum computer Machine Learning in Materials Science ; Computational Physics and Python Applications ; Science Education and Pedagogy
Authors: Shuli Niu | Qinyu Zheng | Song Wang | Jinsong Wang | Jiayu Xia | Weinan Chen | Q. Q. Zhang | Jingrun Xu | Jiaqiang Liao
Source: Research Square (preprint, 2026-02-03)
Field: Chemistry — Physical and Theoretical Chemistry

Divergent thermal acclimation of plant and microbial respiration Acclimatization ; Respiration ; Respiration rate ; Air temperature ; Environmental factor ; Cellular respiration thermodynamics and calorimetric analyses ; Microbial Community Ecology and Physiology ; Plant Water Relations and Carbon Dynamics
Authors: Khalid Akkour | Mohamed. M. R. Rafiullah | Afshan Masood | Ibrahim O. Alanazi | Assim A. Alfadda | Salini Scaria Joy | Ali Bassi | H Alhalal | Eman Alshehri | Maria Arafah | Shahid Nawaz | Hicham Benabdelkamel
Source: Frontiers in Medicine (article, 2026-04-09)
Field: Chemistry — Spectroscopy

Label–free quantitative urinary proteomics for non-invasive biomarker discovery in endometrial cancer Background Endometrial cancer (EC) is a growing global healthcare concern. The diagnosis of EC involves invasive techniques. There is a pressing need for reliable, non-invasive screening methods utilizing biomarkers that diagnose these patients. Methods We conducted a case–control study consists of 40 women including 20 EC (cancer group) and 20 controls (control group) recruited from King Khalid University Hospital, King Saud University. All participants include both cancer and control groups underwent histopathological examination for confirmation. Cancer group had a confirmed diagnosis of EC and control group confirmed benign tissue, verified by histopathological examination. Midstream urine samples were collected under standardized fasting conditions, and proteins extracted using methanol–chloroform precipitation. An untargeted label-free LC-MS/MS mass spectrometric approach combined with bioinformatics was used to determine changes in the proteomic profiles. Multivariate statistical analysis (PCA, OPLS-DA) using MetaboAnalyst v6.0. functional annotation and pathway enrichment were carried out using Ingenuity Pathway Analysis (IPA) and PANTHER classification to identify key biological processes and canonical pathways associated with EC. Results The participants in this cohort were matched for age, with a mean of 59.50 ± 7.13 years in the EC group, and 54.15 ± 10.45 years, in the controls. The study found EC patients had significant differences in 193 proteins (117 upregulated and 76 downregulated) when compared to the controls. There was a clear separation seen between the EC and control groups in multivariate analyses using the PCA, PLS-DA, and OPLS-DA. Glutamate dehydrogenase 1 (GLUD1) and Iduronate 2-sulfatase, both of which were found to be downregulated, and histidine-rich glycoprotein, which was upregulated in EC patients with AUCs of 0.945, 0.965, and 0.875 in the receiver operating curve analysis. Pathway enrichment analysis and network analysis provided molecular insights into the activation of Fc gamma receptor-dependent phagocytosis, complement activation, TRIM21 signaling, and amino acid metabolism. Conclusion The study identified three key biomarkers, GLUD1, Iduronate 2-sulfatase, and histidine-rich glycoprotein, that were significantly dysregulated in patients with EC. The findings highlight that there are systemic immune engagement and tumor-driven metabolic shifts in EC. Biomarker discovery ; Biomarker ; Endometrial cancer ; Cancer ; Bladder cancer ; Proteomics ; Cohort ; Urine Advanced Proteomics Techniques and Applications ; Endometrial and Cervical Cancer Treatments ; Molecular Biology Techniques and Applications
Authors: Kaelyn Dunnell | Adria Lleal | E.A. Hodille | Jonathan Dufour | Rémi Delaporte-Mathurin | Tom Wauters
Source: arXiv (Cornell University) (article, 2026-04-06)
Field: Materials Science — Materials Chemistry

Hydrogen Inventory Simulations for PFCs (HISP) Hydrogen Inventory Simulations for Plasma facing components (HISP) is an open-source simulation tool to model the evolution of hydrogen (H) isotopes inventory in plasma-facing-components (PFCs) of magnetic confinement fusion devices. The objective was to produce a demonstrative study describing the efficiency of tritium (T) removal strategies in ITER. HISP transforms plasma code outputs to spatial-averaged inputs along ITER's first wall (FW) and divertor for 1D H transport models using FESTIM. Exposure conditions were tested in three scenarios that included DT operation and varied T removal methods. Generally, DT operation resulted in $\approx$ \SI{35}{g} of T in FW and divertor components after 10 days of DT pulses. Almost \SI{80}{\%} of the total T inventory resided in co-deposited boron layers in the divertor. Baking proved to be the most effective T removal method in the divertor, decreasing T inventory by almost \SI{88}{\%} for tungsten and almost \SI{30}{\%} for boron. T removal was also evaluated from Glow Discharge Conditioning (GDC) - with a peak efficiency of \SI{23}{\%} in the tungsten FW - and low power deuterium (DD) pulses - with a peak efficiency of \SI{13}{\%} in the entire divertor. Due to the high removal efficiency of baking, inclusion of GDC and DD pulses in the tested scenarios did not meaningfully change final T inventory values, which varied by less than \SI{2}{\%} in the FW and \SI{10}{\%} in the divertor between scenarios. Divertor ; Tungsten ; Fusion power ; Hydrogen ; Deuterium ; Plasma ; Boron Fusion materials and technologies ; Magnetic confinement fusion research ; Superconducting Materials and Applications
Authors: Malik Almunif | Faris Alsolamy | Anthony Grbic
Source:  (article, 2026-02-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Synthesis of Arbitrary Radiation Patterns Using Non-local Reactive Metasurfaces This paper introduces a microwave network-based technique for the design of non-local beamforming metasurface antennas. The metasurface is modeled as a multiport admittance matrix. Beamforming is achieved by tailoring the passive and lossless self-admittances and nearest-neighbor coupling admittances between unit cells. This eliminates the need for numerical optimization or adding surface-waves to enforce passivity. In this technique, target far-field patterns are projected onto the unit cells to determine the required voltage distribution, and Tikhonov regularization is employed to ensure smooth voltages. These voltages are then mapped to a coupling network that is composed of only self-admittances and nearest-neighbor coupling admittances using a systematic synthesis procedure. Practical realization of these admittance matrices is demonstrated using a π-equivalent circuit representation. Several design examples, including Dolph-Chebyshev and multi-beam antennas, are presented to validate the proposed method and demonstrate its capability to generate arbitrary radiation patterns. Admittance ; Coupling (piping) ; Admittance parameters ; Microwave ; Lossless compression ; Voltage ; Beamforming ; Miniaturization ; Realization (probability) Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Y. Sungtaek Ju
Source: arXiv (Cornell University) (article, 2026-03-20)
Field: Materials Science — Materials Chemistry

SymCircuit: Bayesian Structure Inference for Tractable Probabilistic Circuits via Entropy-Regularized Reinforcement Learning Probabilistic circuit (PC) structure learning is hampered by greedy algorithms that make irreversible, locally optimal decisions. We propose SymCircuit, which replaces greedy search with a learned generative policy trained via entropy-regularized reinforcement learning. Instantiating the RL-as-inference framework in the PC domain, we show the optimal policy is a tempered Bayesian posterior, recovering the exact posterior when the regularization temperature is set inversely proportional to the dataset size. The policy is implemented as SymFormer, a grammar-constrained autoregressive Transformer with tree-relative self-attention that guarantees valid circuits at every generation step. We introduce option-level REINFORCE, restricting gradient updates to structural decisions rather than all tokens, yielding an SNR (signal to noise ratio) improvement and >10 times sample efficiency gain on the NLTCS dataset. A three-layer uncertainty decomposition (structural via model averaging, parametric via the delta method, leaf via conjugate Dirichlet-Categorical propagation) is grounded in the multilinear polynomial structure of PC outputs. On NLTCS, SymCircuit closes 93% of the gap to LearnSPN; preliminary results on Plants (69 variables) suggest scalability. Reinforcement learning ; Probabilistic logic ; Greedy algorithm ; Parametric statistics ; Bayesian probability ; Multilinear map ; Generative model ; Frequentist inference ; Inference Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; Evolutionary Algorithms and Applications
Authors: Andrea Argentini | Esperanza Fernández | Jarne Pauwels | Kris Gevaert
Source: bioRxiv (Cold Spring Harbor Laboratory) (article, 2026-03-12)
Field: Chemistry — Spectroscopy

DiaReport: Reproducible Workflow for Differential Expression Analysis and Interactive Reporting in DIA-based Proteomics Abstract Summary Data-independent acquisition (DIA) has become the preferred data acquisition method for mass spectrometry-based proteomics, yet, reproducible workflows for differential expression (DE) analysis and reporting results remain limited. We present DiaReport, an R package that performs precursor- and protein-level DE analysis from DIA-NN output using MSqRob and QFeatures, while generating high-quality, interactive HTML reports through Quarto. DiaReport integrates precursor data, filtering of missing values, normalization, protein summarization and statistical modeling within a single function, supporting both simple pairwise as well as complex experimental designs. The package provides structured outputs and configuration files to ensure computational reproducibility across different studies. To accommodate diverse research needs, DiaReport includes multiple reporting templates tailored to different proteomic applications. Applying DiaReport to an extracellular vesicle (EV) proteomics dataset demonstrates its ability to efficiently analyze DIA data and provide rapid insights into sample quality and protein level differences. Availability and Implementation DiaReport is an open-source R package available at https://github.com/Gevaert-Lab/diareport . The package is platform-independent and distributed under the MIT license. Reports are generated using Quarto and require only standard R dependencies. Detailed documentation, installation guides and usage vignettes are provided within the repository. The interactive HTML reports discussed in this study, including the UPS2 benchmark and EV case study, are archived on Zenodo ( https://doi.org/10.5281/zenodo.18632744 and https://doi.org/10.5281/zenodo.18632731 ). Contact Corresponding author: Kris Gevaert; kris.gevaert@vib-ugent.be . Workflow ; Automatic summarization ; Benchmark (surveying) ; Pairwise comparison ; Proteomics ; R package ; Pipeline (software) ; Data acquisition ; Sample (material) ; Bioconductor Advanced Proteomics Techniques and Applications ; Biotin and Related Studies ; Mass Spectrometry Techniques and Applications
Authors: Shao Nan Chen | Zhan Ye Chen | Si ran Wang | Bi Rui | Jin Kang | Zheng Xing Wang | Zhen Jie Qi | Lijie Wu | Hui Dong Li | Jun Yan Dai | Qiang Cheng | Tie Jun Cui
Source: ArXiv.org (article, 2026-01-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Programmable radio-frequency calculations in electromagnetic-wave domain Information metasurfaces have emerged as pivotal components in next-generation electronic systems, with significant progress in their applications to communication, radar, and sensing. However, the current researches are mainly focused on their physical structures and system functions, while radio-frequency (RF) signal processing and calculation remain constrained to digital-domain operations. This reliance on digital conversion inherently increases hardware complexity and power consumption. To address this challenge, we propose a programmable RF calculation system based on a space-time-coding metasurface (STCM), which can control the wave-matter interactions through space-time-coding (STC) strategies and achieve direct RF calculations in the electromagnetic (EM) space in a reprogrammable way. Particularly, the fundamental signal operations - Fourier transform and convolution - are implemented in the EM-wave domain successfully. We validate the RF calculation capabilities in radar scenarios, facilitating the accurate detection of target velocity and range. Theoretical analysis, numerical simulations, and experimental results collectively demonstrate that the STCM-based RF calculation system exhibits superior precision, enhanced operational efficiency, and notable cost-effectiveness, highlighting its significant potentials for the next-generation electronic system deployments. Convolution (computer science) ; Digital signal processing ; Signal processing ; Radar ; SIGNAL (programming language) ; Frequency domain ; Radio frequency ; Power (physics) ; Domain (mathematical analysis) Metamaterials and Metasurfaces Applications ; Advanced Wireless Communication Technologies ; Advanced Antenna and Metasurface Technologies