jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yilin Zhao | Dongbo Zhao | Chunying Rong | Shubin Liu | Paul W. Ayers
Source: Preprints.org (preprint, 2025-05-23)
Field: Chemistry — Physical and Theoretical Chemistry

An Elementary Introduction to Classical and Quantum Information in Quantum Chemistry In this survey, we begin with a concise introduction to information theory within Shannon&amp;#039;s framework, focusing on the key concept of Shannon entropy and its related quantities: relative entropy, joint entropy, conditional entropy and mutual information. We then demonstrate how to apply these information-theoretic tools in quantum chemistry, adopting either classical or quantum formalisms based on the choice of information carrier involved. Quantum ; Quantum chemistry ; Theoretical physics ; Quantum mechanics ; Physics ; Engineering physics ; Molecule History and advancements in chemistry
Authors: B.C. do Amaral | Nicholas I. Brodie | Andrew R. M. Michael | D. Alex Crowder | Pauline Douglas | Morgan F. Khan | David C. Schriemer
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-10-16)
Field: Chemistry — Spectroscopy

Signal Attrition in Whole Cell Crosslinking Mass Spectrometry Abstract Crosslinking mass spectrometry (XL-MS) could replace traditional techniques for sampling the cellular interactome, such as affinity pulldown MS. It generates superior interaction data that can be used to better model cellular structure and function. However, the sampling depth of current XL-MS techniques is disappointing. Poor sampling is often blamed on a low-yielding crosslinking reaction, estimated to be ∼0.1% based on relative ion abundance in the mass spectrometer. Here, using a new two-step crosslinker installation process, we demonstrate that the yield of the chemical reaction is not the limiting factor in sampling the interactome. Low crosslink detection levels persist even when crosslink yields approach 30% of total peptide. We show that crosslinked peptides are not preferentially lost during sample workup; they enter the mass spectrometer at least as efficiently as linear peptides. Low detection rates arise mostly from severe signal splitting that reduces the S/N of crosslinked peptides, which is likely exacerbated by low-sensitivity database search tools and compounded by ion suppression. Mass spectrometry ; Sampling (signal processing) ; Yield (engineering) ; SIGNAL (programming language) ; Limiting ; Analytical Chemistry (journal) ; Ion current Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Cell Image Analysis Techniques
Authors: Ayu Muthia | Daimon Syukri | Mai Efdi | Adlis Santoni
Source: Tropical Journal of Natural Product Research (article, 2025-10-30)
Field: Chemistry — Analytical Chemistry

Rapid Spectroscopy-based Fingerprinting Combined with Data Fusion Chemometrics of Amaranthus tricolor L. for Growing Environment Discrimination Amaranthus tricolor L. is a nutrient-rich plant with significant health-promoting properties, making it a valuable candidate for functional foods and therapeutic applications. This study investigated the effect of the cultivation environment on the metabolite composition of A. tricolor L. by comparing soil- and hydroponically grown samples. Spectral analysis using ultraviolet-visible (UV-Vis) and Fourier transform infrared (FTIR) spectroscopy, combined with chemometric data fusion, was conducted to assess the metabolic profiles. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to evaluate the data, facilitating robust classification and accurate identification of the key metabolites. Volcano plot analysis indicated that the soil-grown plants accumulated higher levels of phenolics and flavonoids, whereas hydroponic cultivation favored the synthesis of photosynthetic pigments and membrane lipids. The PCA revealed distinct separation between the groups, with PC1 explaining 84.8% and 69.2% of the FTIR and UV-Vis variance, respectively. OPLS-DA models exhibited the highest classification accuracy (100%) with R²Y &gt; 0.99 and Q² &gt; 0.98. Notably, low-level data fusion further enhanced discrimination, increasing predictive variance to 76.0% and capturing subtle metabolic differences that single techniques cannot detect. These results suggested that soil cultivation promotes a defensive metabolic strategy that enhances the antioxidant capacity, whereas hydroponic systems support growth-oriented metabolism. The integrative chemometric and data fusion approach provided a comprehensive metabolomic fingerprint, offering valuable insights into the optimization of cultivation practices to enhance the nutritional and functional values of A. tricolor L. Principal component analysis ; Chemometrics ; Metabolomics ; Partial least squares regression ; Linear discriminant analysis ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Seed and Plant Biochemistry
Authors: Khushboo Kumari | Dharmendra Kumar | LP Singh
Source: International Journal of Pharmaceutical Research and Development (article, 2025-07-01)
Field: Chemistry — Organic Chemistry

Advancements in the design and development of pyrazole derivatives as selective anti-inflammatory agents: Structural modifications, mechanisms, and therapeutic potential Pyrazole derivatives have gained significant attention in the field of medicinal chemistry due to their promising anti-inflammatory, analgesic, and antipyretic activities. The pyrazole scaffold offers substantial chemical versatility, allowing for the synthesis of a wide variety of compounds with selective activity against key inflammatory targets such as cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), and tumor necrosis factor-alpha (TNF-α). This review explores the recent advancements in the design and development of pyrazole-based anti-inflammatory agents, focusing on structural modifications that enhance their potency, selectivity, and pharmacokinetic properties. Additionally, we discuss the mechanisms by which these derivatives exert their anti-inflammatory effects, highlighting their therapeutic potential in treating chronic inflammatory diseases such as rheumatoid arthritis, osteoarthritis, and inflammatory bowel disease. The paper also covers the challenges faced in drug development and suggests future directions for improving the efficacy and safety of pyrazole-based anti-inflammatory drugs. Pyrazole ; Drug ; Drug development ; Anti-inflammatory ; Scaffold ; Drug discovery Synthesis and biological activity ; Inflammatory mediators and NSAID effects ; Rheumatoid Arthritis Research and Therapies
Authors: Péter Fejér | Adrienn Széles | Péter Ragán | Csaba Juhász | Éva Horváth | Tamás Rátonyi
Source: Precision Crop Production (article, 2025-07-22)
Field: Chemistry — Analytical Chemistry

Predicting maize yield with a multilayer perceptron (MLP) model using multivariate field data This study presents the findings of a multi-year maize field trial conducted on experimental plots between 2017 and 2019, focusing on the application of machine learning techniques to enhance yield prediction accuracy. A multilayer perceptron (MLP) neural network was employed to model the effects of agronomic treatments, environmental variation, and compositional traits. Six distinct modeling scenarios were developed to explore different combinations of input variables, with the grain yield of maize serving as the sole output parameter. These scenarios range from treatment-only models to those incorporating detailed quality and compositional data. The primary objective was to evaluate how well MLP models can capture the complex, nonlinear relationships influencing yield under varying conditions. The findings provide valuable insight into the role of machine learning in supporting decision-making for sustainable crop production, especially under diverse technological and environmental settings. The approach demonstrated here offers a foundation for more adaptable, data-driven strategies in agronomic optimization. Multilayer perceptron ; Artificial neural network ; Yield (engineering) ; Field (mathematics) ; Crop yield ; Range (aeronautics) ; Multivariate statistics Spectroscopy and Chemometric Analyses
Authors: Jian Zhang | Hao Jiang | Fan Yang | Feiliang Chen | Yang Liu | Yuqian Tang | Mo Li
Source: Research Square (preprint, 2025-05-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Breaking the bandwidth barrier:Graphene-driven programmable transmissive metasurfaces enableultra-wideband terahertz beam steering Terahertz radiation ; Beam steering ; Wideband ; Bandwidth (computing) ; Graphene ; Optoelectronics ; Optics ; Materials science ; Beam (structure) ; Physics ; Telecommunications ; Computer science ; Nanotechnology Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Ying Zhang | Jie Wang | Xiuhong Wu | Rui Chang | Hong Luo | Juan Yang | Quan Wu | Ze Xu | Yingfu Zhong
Source: Applied Sciences (article, 2025-01-09)
Field: Chemistry — Analytical Chemistry

A Rapid and Nondestructive Quality Detection Approach for Yongchuan Xiuya Tea Based on NIRS and siPLS-ANN Method The efficient and non-destructive evaluation of Yongchuan Xiuya tea quality represents a key advancement in the tea industry. Near-infrared spectroscopy (NIRS), a non-invasive analytical technology, allows for the acquisition of spectral data while preserving sample integrity. Through preprocessing the spectral data and employing the synergy interval partial least squares (siPLS) method to identify characteristic spectral regions, principal component analysis (PCA) is applied, followed by the development of a Jordan–Elman artificial neural network prediction model (ANN) for tea quality assessment. The optimal spectral preprocessing approach identified in this study is a combination of multiplicative scatter correction and second derivative processing. Key spectral intervals include 4377.6 cm−1–4751.7 cm−1, 4755.6 cm−1–5129.7 cm−1, 6262.7 cm−1–6633.9 cm−1, and 7386 cm−1–7756.3 cm−1, with the first three principal components achieving a cumulative contribution rate of 99.05%. Utilizing a tanh activation function, the model exhibited strong predictive performance: an Rp2 of 0.980 and RMSEP of 0.341 for prediction set samples, and an Rp2 of 0.978 with RMSEP of 0.373 for unknown samples. These findings demonstrate the potential of integrating NIRS with Jordan–Elman neural networks for rapid and accurate Yongchuan Xiuya tea quality evaluation, establishing a solid technological foundation for the application of NIRS in tea quality assessment. Principal component analysis ; Mathematics ; Preprocessor ; Artificial neural network ; Multiplicative function ; Near-infrared spectroscopy ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Biological system ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Phytochemicals and Antioxidant Activities
Authors: Xinyang Mu | Yuzhen Lu
Source: Research Square (preprint, 2025-02-20)
Field: Chemistry — Analytical Chemistry

Non-destructive Detection of Spotted Wing Drosophila Infestation in Blueberries Using Hyperspectral Imaging Hyperspectral imaging ; Wing ; Drosophila (subgenus) ; Infestation ; Biology ; Computer vision ; Artificial intelligence ; Computer science ; Engineering ; Horticulture ; Aerospace engineering ; Genetics Spectroscopy and Chemometric Analyses ; Insect Pest Control Strategies ; Insect and Pesticide Research
Authors: Bagus Wahyu Setyawan | Yuvita Lira Vesti Arista | Arfiati Ulfa Utami
Source: Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) (article, 2025-01-24)
Field: Chemistry — Analytical Chemistry

Chemical Content Evaluation of Peaberry Robusta Green Bean Using FT NIRS Method Mount Ijen is a prominent region for peaberry Robusta coffee beans, which has entered international markets. Accurate real-time estimation of its chemical components is crucial for export activities. This study evaluated moisture content, lipid, and caffeine in Robusta peaberry coffee beans from Ijen using FT-NIRS (Fourier Transform – Near Infrared Spectroscopy). A total of 50 samples were scanned in triplicate, generating 150 spectral data points. The data were optimized for wavelength selection and pre-treated using Standard Normal Variate Transformation (SNV), Second Derivative (dg2), Multiplicative Scatter Correction (MSC), and normalization. Results showed that FT-NIRS proved effective for rapid and accurate estimation of these components. The best calibration model used Kubelka-Munk transformation with dg2 pre-treatment in the 1000-2500 nm wavelength range. Optimal Partial Least Squares (PLS) factors were PLS 4 for lipid content (R2 = 0.98, SEP = 0.013%, SEC = 0.012%, CV = 0.81, RPD = 2.03, consistency = 95.21%), PLS 5 for moisture content (R2 = 0.94, SEP = 0.014%, SEC = 0.014%, CV = 0.80, RPD = 4.88, consistency = 101.02%), and PLS 5 for caffeine content (R2 = 0.94, SEP = 0.014%, SEC = 0.014%, CV = 0.80, RPD = 4.88, consistency = 101.02%). Keywords: Absorbance, Caffeine, Lipid, Moisture Content, Pre-Treatment. Content (measure theory) ; Chemistry ; Mathematics ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Food composition and properties
Authors: Chukwuebuka Egbuna | Kingsley C. Patrick-Iwuanyanwu | Eugene N. Oyeike | Colin B. Lukong | Cecilia Chika Unegbu | Chukwuemeke D. Edward | Chukwudi Jude Chikwendu | C. C. Ilechukwu | Michael Chinedu Olisah | Anthony O. Ekesiobi | Jonathan C. Ifemeje | I. H. Iheukwumere
Source:  (article, 2025-06-03)
Field: Chemistry — Organic Chemistry

Computational Screening of High-Affinity Natural Product-Derived Inhibitors Targeting NF-κB Protein: A Molecular Docking Approach toward Anti-Inflammatory and Anticancer Therapeutics Nuclear factor kappa B (NF-κB) is a pivotal transcription factor involved in inflammation, immune responses, and cancer progression. In the quest for safer and more effective therapeutic agents, this study employed molecular docking to screen 313 bioactive phytochemicals against NF-κB, aiming to identify potential natural inhibitors. Ligands were curated from literature and public databases and prepared using ChemDraw, VConf, and Open Babel, while the NF-κB protein (PDB ID: 1SVC) was retrieved from the RCSB Protein Data Bank and refined using BIOVIA Discovery Studio. Binding site prediction was achieved via PrankWeb and literature data. Docking was conducted with PyRx 0.8 using AutoDock Vina, and binding interactions were analyzed in Discovery Studio. Results revealed that hypericin and withanolide exhibited the strongest binding affinities (-8.4 kcal/mol), surpassing standard NF-κB inhibitors such as olmesartan (-6.3 kcal/mol) and disulfiram (-3.5 kcal/mol). Other top-performing compounds included diosmin (-8.3 kcal/mol), tomatidine, tubeimoside-I, and solanine (all -8.0 kcal/mol), each interacting with key NF-κB residues through hydrogen bonding and hydrophobic interactions. These phytochemicals, available from diverse medicinal plants, showed superior binding profiles, highlighting their therapeutic potential. Overall, the study underscores the promise of natural compounds in modulating NF-κB activity and supports their further investigation through molecular dynamics simulations and experimental validation. These findings provide a foundation for the development of phytochemical-based NF-κB inhibitors with potential applications in inflammation and cancer therapy. Docking (animal) ; Natural product ; Computational biology ; Chemistry ; Anti-inflammatory ; Pharmacology ; Biochemistry ; Biology ; Medicine Synthesis and biological activity ; Cytokine Signaling Pathways and Interactions ; Pharmacological Effects of Natural Compounds
Authors: Thomas Kempe | S. M. Ali Tabei | Mohammad Rashid Ansari
Source: Research Square (preprint, 2025-09-04)
Field: Chemistry — Spectroscopy

Intermediate State Formation of Topologically Associated Chromatin Domains using Quantum Annealing Chromatin ; Quantum annealing ; Quantum ; Annealing (glass) ; Physics ; Computational biology ; Evolutionary biology ; Biology ; Genetics ; Quantum mechanics ; Quantum computer ; DNA ; Thermodynamics Molecular spectroscopy and chirality
Authors: Devon Kohler | Eralp Doğu | M. Bhattacharya | Ozge Karayel | Masaka Magana | Aoli Wu | Veronica G. Anania | Olga Vitek
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-09-16)
Field: Chemistry — Spectroscopy

Accounting for longitudinal peak quality metrics with MSstats+ enhances differential analysis in proteomic experiments with data-independent acquisition Abstract Mass spectrometry-based proteomics with data-independent acquisition benefits from advanced instrumentation and computational analysis. Despite continued improvements, the quality of quantification may be poor for some measurements. As the scale of proteomic experiments increases, these poor-quality measurements are challenging to characterize by hand, yet they undermine the detection of differentially abundant proteins and the downstream biological conclusions. We introduce MSstats+ , a computational workflow that takes as input not only peak intensities reported by tools such as Spectronaut, but also quality metrics such as peak shape and retention time, and longitudinal run order profiles of these metrics. MSstats+ translates these metrics into a single measure of quality, and downweights poor quality measurements when detecting differentially abundant proteins. The method offers a natural treatment of missing values, weighting the imputed values according to the quality metrics in the run. We demonstrate the accuracy of the resulting differential analysis in four experiments: two custom benchmarking studies with intentionally induced anomalies, a controlled mixture of proteomes, and a large-scale clinical investigation. MSstats+ is implemented in the family of open-source R/Bioconductor packages MSstats . Weighting ; Benchmarking ; Workflow ; Quality (philosophy) ; Measure (data warehouse) ; Instrumentation (computer programming) ; Scale (ratio) ; Differential (mechanical device) Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Gene expression and cancer classification
Authors: Suyeon Seo | Ju-Hee Lee | Minchae Kang | Eunsol Park | M. HAN
Source: Biomimetics (article, 2025-12-31)
Field: Materials Science — Polymers and Plastics

Compressive Strength Optimization of 3D-Printed Voronoi Trabecular Bone Using the Taguchi Method The surge in demand for patient-specific orthopedic implants necessitates the precise optimization of design and processing parameters for artificial trabecular bone. This research utilizes Voronoi-based porous structures to replicate the irregular geometry characteristic of natural trabecular bone. All specimens were fabricated through fused deposition modeling (FDM) with polylactic acid (PLA). The study systematically investigated the influence of four primary parameters, namely build orientation, extruder temperature, layer height, and pore count, on compressive strength. To ensure experimental efficiency, the research implemented a Taguchi L20 orthogonal array. Subsequent signal-to-noise (S/N) ratio analysis identified the optimal parameter set as a y-90° build orientation, an extruder temperature of 200 °C, a layer height of 0.2 mm, and a count of 150 pores. These findings underscore the necessity of integrated geometric and process parameter optimization to advance additive manufacturing for orthopedic applications. Taguchi methods ; Compressive strength ; Extrusion ; Porosity ; Plastics extrusion ; Process (computing) ; Design of experiments ; Layer (electronics) ; Deposition (geology) Polymer Foaming and Composites ; Bone Tissue Engineering Materials ; Additive Manufacturing and 3D Printing Technologies
Authors: 腾 张
Source: Modeling and Simulation (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Geometric Phase-Based Metasurfaces for Focusing and Vortex Longitudinal Polarization Evolution 超构表面在纵向方向上的调控为控制偏振状态引入了新的维度，为了实现偏振态随传播方向的演化，文章提出了一种基于几何相位调制的超构表面，可以同步实现纵向聚焦、涡旋及偏振态的演化。该设计基于复振幅的叠加方法来构建结构，并通过时域有限差分方法(FDTD)进行了数值仿真验证。仿真的结果表明，所设计的超构表面在纵向上从焦点演化到涡旋的过程中，可以同时实现正交线偏振态的演化；进一步设计了双涡旋的纵向偏振演化，同时也实现了涡旋拓扑荷的演化。这种沿传播方向动态调控偏振态的方法，为开发光控可切换器件及推动光–物质相互作用的研究开辟了新的应用前景。Metasurfaces with longitudinal modulation capabilities introduce a new dimension for polarization state control. To achieve polarization evolution along the propagation direction, this article proposes a geometric-phase-modulated metasurface that simultaneously enables longitudinal focusing, vortex generation, and polarization evolution. The design employs a complex-amplitude superposition method for structural configuration, validated through finite-difference time-domain (FDTD) numerical simulations. Results demonstrate that the metasurface facilitates orthogonal linear polarization evolution during the longitudinal transition from focused spots to vortex beams. Furthermore, we implement dual-vortex configurations exhibiting longitudinal polarization evolution while enabling dynamic modulation of vortex topological charges. This approach to dynamically manipulate polarization states along the propagation axis opens new prospects for developing optically controlled switchable devices and advancing light-matter interactions. Vortex ; Polarization (electrochemistry) ; Geometric phase ; Optics ; Physics ; Phase (matter) ; Mechanics ; Condensed matter physics Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Orbital Angular Momentum in Optics
Authors: Enes Eken | İsmail Bayraklı
Source: Konya Journal of Engineering Sciences (article, 2025-12-01)
Field: Chemistry — Spectroscopy

EXTRACTING A MUCH WIDER ABSORPTION SPECTRAL RANGE FROM A NARROWER RANGE USING TRANSFORMER MODEL Obtaining a wide absorption spectral range rapidly at high resolution plays a crucial role in scientific research and practical applications. The main motivation of this work is to investigate the rapid acquisition of a very wide spectral range at high resolution by using a much narrower absorption spectral range. To accomplish this, we proposed a novel transformer-based approach that produces a wider absorption spectral range (100 cm−1 ) with high resolution in milliseconds from a narrow absorption spectral range (2 cm−1 ). A distributed feedback quantum cascade laser (DFB QCL) together with a multi-pass cell was used to obtain the absorption lines. To evaluate the performance of the sensor, N2O was selected as the target molecule. Spectral resolution ; Absorption (acoustics) ; Range (aeronautics) ; Resolution (logic) ; Absorption spectroscopy ; Cascade ; Laser Spectroscopy and Laser Applications ; Semiconductor Lasers and Optical Devices ; Advanced Fiber Laser Technologies