jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Eftychia G. Karageorgou | Natasa P. Kalogiouri | Victoria Samanidou
Source: Molecules (review, 2025-08-31)
Field: Chemistry — Spectroscopy

Green Approaches in High-Performance Liquid Chromatography for Sustainable Food Analysis: Advances, Challenges, and Regulatory Perspectives This review provides a comprehensive overview of the recent green innovations in high-performance liquid chromatography (HPLC) for sustainable food analysis. It outlines the principles of green analytical chemistry and examines advances such as eco-friendly solvent systems, miniaturized and energy-efficient instrumentation, and greener sample preparation techniques. Key applications include the analysis of bioactive compounds, detection of contaminants and residues, and support for clean-label and sustainability claims. Furthermore, the review discusses relevant regulatory and certification frameworks, including ISO 14001, ISO 22000, and global food safety initiatives aligned with environmental, social, and governance standards. Persistent challenges, such as cost, limitations in analytical performance, and limited instrument availability, are highlighted, along with the need for reliable metrics to assess the environmental impact and effectiveness of green analytical practices. The review concludes by emphasizing the need for interdisciplinary collaboration among scientists, industry stakeholders, and regulatory bodies to support the wider adoption of sustainable HPLC practices in food laboratories. Chemistry ; Biochemical engineering ; Business ; Environmental science ; Chromatography ; Computational biology ; Engineering ; Biology Analytical Chemistry and Chromatography ; Pesticide Residue Analysis and Safety ; Analytical chemistry methods development
Authors: Yujie Wei | Jinming Liu | Guiqing Xi | Yuhao Lu
Source: Foods (article, 2025-11-17)
Field: Chemistry — Analytical Chemistry

Quantitative Detection of Key Parameters and Authenticity Verification for Beer Using Near-Infrared Spectroscopy Alcohol content and original wort concentration are key indicators of beer quality. The detection of these metrics and the authentication of beer authenticity are crucial for protecting consumer rights. To this end, this study investigates quantitative detection methods for beer alcohol content and original wort concentration based on near-infrared spectroscopy (NIRS), as well as authenticity verification methods for craft, industrial, and non-fermented beers. Convolutional neural networks combined with a long short-term memory networks (CNN-LSTM) feature extraction method was proposed for establishing multiple regression models and partial least squares discriminant analysis (PLS-DA) model. The results indicate that the CNN-LSTM combined with the support vector machine regression demonstrates optimal performance, with coefficients of determination exceeding 0.99 for the alcohol content calibration, validation, and independent test sets, and all relative root mean square errors below 2.67%. For original wort concentration, the coefficients of determination exceeded 0.97 across the calibration, validation, and independent test sets, with relative root mean square errors below 4.05%. The CNN-LSTM combined with the PLS-DA approach exhibited the lowest variable dimension while achieving 100% classification accuracy. This method offers rapid, non-destructive, and efficient advantages, making it suitable for beer quality control and market regulation. Partial least squares regression ; Pattern recognition (psychology) ; Linear discriminant analysis ; Support vector machine ; Artificial neural network ; Feature (linguistics) ; Key (lock) ; Dimension (graph theory) Spectroscopy and Chemometric Analyses ; Fermentation and Sensory Analysis ; Advanced Chemical Sensor Technologies
Authors: Kusumiyati Kusumiyati | Ine Elisa Putri | Yuda Hadiwijaya | Ary Giri Dwi Kartika | Yusuf Eka Maulana | Wawan Sutari
Source: International Journal of Food Science (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Quality Assurance of Total Carotenoids and Quercetin in Marigold Flowers ( <i>Tagetes erecta</i> L.) as Edible Flowers Marigold flowers, which are also known as <i>Tagetes erecta</i> L., are widely recognized for their bright colors and health benefits. Therefore, the purpose of this research was to investigate the quality of total carotenoid content (TCC) and quercetin in marigold flowers, specifically the edible ones, using visible near-infrared spectroscopy (Vis-NIRS) technology. Both bioactive compounds in these flowers were assessed using Vis-NIRS. The technology is considered to be a rapid and non-destructive method for evaluating the quality of agricultural products. To ensure accuracy in the evaluation, Vis-NIRS was validated against conventional methods such as spectrophotometry and chromatography. The results showed that the use of Vis-NIRS helped to accurately determine the levels of TCC and quercetin in marigold flowers. Based on the analysis results, the best accuracy values for TCC were as follows: the correlation coefficient of the calibration set (<i>R</i> <sub>cal</sub>) was 0.94, the root mean square error of the calibration set (RMSEC) was 125.57, the correlation coefficient of the prediction set (<i>R</i> <sub>pred</sub>) was 0.87, the root mean square error of the prediction set (RMSEP) was 129.35, and the ratio of prediction to deviation (RPD) was 2.77. For quercetin, the best accuracy values were: <i>R</i> <sub>cal</sub> was 0.96, RMSEC was 1.63, <i>R</i> <sub>pred</sub> was 0.88, RMSEP was 2.37, and RPD was 2.09. These results demonstrate that the method provides a reliable alternative to destructive method. The research showed that Vis-NIRS served as a reliable quality assurance tool for assessing bioactive compounds in marigold flowers. Tagetes ; Quercetin ; Correlation coefficient ; Mathematics ; Carotenoid ; Mean squared error ; Coefficient of determination ; Chemistry ; Horticulture ; Food science ; Statistics ; Biology ; Biochemistry Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Leaf Properties and Growth Measurement
Authors: Peter O’Reilly | Genevieve Loiselle | Ryan Darragh | Carmine J. Slipski | Denice C. Bay
Source: npj Antimicrobials and Resistance (review, 2025-05-13)
Field: Chemistry — Organic Chemistry

Reviewing the complexities of bacterial biocide susceptibility and in vitro biocide adaptation methodologies Decreased bacterial susceptibility to biocides raises concerns due to their influences on antibiotic resistance. The lack of standardized breakpoints, established methods, and consistent terminology complicates this research. This review summarizes techniques for studying biocide resistance mechanisms, susceptibility testing, and in-vitro adaptation methods, highlighting their benefits and limitations. Here, the challenges in studying biocide susceptibility and the need for standardized approaches in biocide research are emphasized for commonly studied biocide classes. Biocide ; Microbiology ; Adaptation (eye) ; Biology ; Chemistry Antimicrobial agents and applications ; Bacterial biofilms and quorum sensing ; Bacillus and Francisella bacterial research
Authors: Shenlong Zha | Hang Chen | Chen Liu | Yuxiang Guo | Hongliang Ma | Qilei Zhang | Lingli Li | Shengbao Zhan | Gang Cheng | Yanan Cao | Pan Pan
Source: Photoacoustics (article, 2025-02-01)
Field: Chemistry — Spectroscopy

Multivariate-coupled-enhanced photoacoustic spectroscopy with Chebyshev rational fractional-order filtering algorithm for trace CH4 detection An innovative and miniature photoacoustic spectroscopy (PAS) gas sensor based on a multivariate-coupled amplification photoacoustic cell (MVCA-PAC) with a total length of 100 mm was developed to achieve ultra-sensitive trace CH<sub>4</sub> detection. Acoustic pressure distribution simulations reveal that at the first-order resonance frequency, the MVCA-PAC achieves a maximum acoustic pressure approximately 3.9 times higher than that of a conventional photoacoustic cell. The absorption optical path of the MVCA-PAC reached 2068 mm through 22 reflections, resulting in a 2-fold increase in the amplitude of photoacoustic signals compared to the traditional photoacoustic cell with an equivalent absorption optical path. Furthermore, compared to a single-pass photoacoustic cell, the <i>2-f</i> signal intensity of the MVCA-PAC increased by a factor of 4.5. Allan variance analysis indicated a detection limit of 0.572 ppm for CH<sub>4</sub> detection with an averaging time of approximately 300 s. To further improve the measurement precision of the designed sensor, the Chebyshev rational fractional-order filtering (CRFOF) algorithm was introduced for PAS signal processing for the first time. Post-processing results demonstrated a 15.4-fold improvement in measurement precision, achieving a precision of 0.578 ppm. Finally, continuous monitoring of atmospheric CH<sub>4</sub> over a 48-hour period validated the reliability and feasibility of the sensor. Chebyshev filter ; TRACE (psycholinguistics) ; Multivariate statistics ; Order (exchange) ; Photoacoustic spectroscopy ; Materials science ; Photoacoustic imaging in biomedicine ; Spectroscopy ; Multivariate analysis ; Algorithm ; Analytical Chemistry (journal) ; Computer science ; Optics ; Mathematics ; Physics ; Chemistry ; Statistics ; Mathematical analysis ; Quantum mechanics ; Chromatography ; Business Spectroscopy and Laser Applications ; Advanced Chemical Sensor Technologies ; Atmospheric and Environmental Gas Dynamics
Authors: Zaqlul Iqbal | Nils Kristian Afseth | Annelies Postelmans | Jens Petter Wold | Petter Vejle Andersen | Joni Kusnadi | Wouter Saeys
Source: Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (article, 2025-03-22)
Field: Chemistry — Analytical Chemistry

Detection and quantification of pork adulteration in beef meatballs with Raman spectroscopy and near infrared spectroscopy Chemistry ; Raman spectroscopy ; Spectroscopy ; Near-infrared spectroscopy ; Infrared spectroscopy ; Analytical Chemistry (journal) ; Infrared ; Chromatography ; Organic chemistry ; Optics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Go Soma | Kento Komatsu | Yoshiaki Nakano | Takuo Tanemura
Source: Nature Communications (article, 2025-08-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Complete vectorial optical mode converter using multi-layer metasurface Vectorial optical mode converters that can transform orthogonal sets of multiple input vector beams into other orthogonal sets are attractive for various applications in optics and photonics. While multi-plane light conversion (MPLC) and metasurface technologies have been explored to individually address multiple spatial mode conversion and polarization mode manipulation, there has been no universal methodology to simultaneously convert a set of multiple vectorial modes with spatially non-uniform wavefronts and polarizations. Here, we present a general device framework to achieve complete vectorial mode conversion based on the MPLC concept incorporating multi-layer metasurfaces. The effectiveness of our method is confirmed experimentally by demonstrating 6-mode (3 spatial modes × 2 polarization modes) multiplexer fabricated on a compact chip. Additionally, we apply it to design devices with more advanced functionalities: a mode-division-multiplexed dual-polarization coherent receiver and spatial-mode-multiplexed vectorial holography. The versatility of our protocol makes it a powerful tool for realizing universal optical mode converters. Mode (computer interface) ; Layer (electronics) ; Computer science ; Optoelectronics ; Physics ; Optics ; Materials science ; Nanotechnology Metamaterials and Metasurfaces Applications ; Optical Wireless Communication Technologies ; Photonic and Optical Devices
Authors: Zhenwei Liang | Xiuquan Xu | Deyong Yang | Yanbin Liu
Source: Agriculture (article, 2025-04-14)
Field: Chemistry — Analytical Chemistry

The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains A rice impurity detection algorithm model, DE-YOLO, based on YOLOX-s improvement is proposed to address the issues of small crop target recognition and the similarity of impurities in rice impurity detection. This model achieves correct recognition, classification, and detection of rice target crops with similar colors in complex environments. Firstly, changing the CBS module to the DBS module in the entire network model and replacing the standard convolution with Depthwise Separable Convolution (DSConv) can effectively reduce the number of parameters and the computational complexity, making the model lightweight. The ECANet module is introduced into the backbone feature extraction network, utilizing the weighted selection feature to cluster the network in the region of interest, enhancing attention to rice impurities and broken grains, and compensating for the reduced accuracy caused by model light weighting. The loss problem of class imbalance is optimized using the Focal Loss function. The experimental results demonstrate that the DE-YOLO model has an average accuracy (mAP) of 97.55% for detecting rice impurity crushing targets, which is 2.9% higher than the average accuracy of the original YOLOX algorithm. The recall rate (R) is 94.46%, the F1 value is 0.96, the parameter count is reduced by 48.89%, and the GFLOPS is reduced by 46.33%. This lightweight model can effectively detect rice impurity/broken targets and provide technical support for monitoring the rice impurity/ broken rate. Impurity ; Environmental science ; Materials science ; Physics Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Smart Agriculture and AI
Authors: Jennifer M.S. Koh | Erin K. Sykes | Jyoti Rukhaya | Asim Anees | Qing Zhong | Christopher C. Jackson | Benedict Panizza | Roger R. Reddel | Rosemary L. Balleine | Peter G. Hains | Phillip J. Robinson
Source: Clinical Proteomics (article, 2025-02-05)
Field: Chemistry — Spectroscopy

The effect of storage time and temperature on the proteomic analysis of FFPE tissue sections Formalin-fixed paraffin-embedded (FFPE) tissues present an important resource for cancer proteomics. They are more readily available than fresh frozen (FF) tissues and can be stored at ambient temperature for decades. FFPE blocks are largely stable for long-term preservation of tumour histology, but the antigenicity of some proteins in FFPE sections degrades over time resulting in deteriorating performance of immunohistochemistry (IHC). It is not known whether FFPE sections that have previously been cut from blocks and used for liquid chromatography-mass spectrometry (LC-MS) analysis at a later time are affected by storage time or temperature. We determined the stability of FFPE sections stored at room temperature (RT) versus - 80 °C over 48 weeks. The stored sections were processed at different timepoints (n = 11) and compared to sections that were freshly cut from FFPE blocks at each timepoint (controls). A total of 297 sections (rat brain, kidney and liver stored at RT, - 80 °C or freshly cut) were tryptically digested and analysed on TripleTOF 6600 mass spectrometers in data-dependent acquisition (DDA) mode. Kidney and liver digests were also analysed in data-independent acquisition (DIA) mode. The number of proteins and peptides identified by DDA with ProteinPilot and some common post-translational modifications (PTMs) were unaffected by the storage time or temperature. Nine of the most common FFPE-associated modifications were quantified using DIA data and all were unaffected by storage time or temperature. Therefore, FFPE tissue sections are suitable for proteomic studies for at least 48 weeks from the time of sectioning. Proteomics ; Mass spectrometry ; Antigenicity ; Chemistry ; Kidney ; Immunohistochemistry ; Molecular biology ; Pathology ; Chromatography ; Biology ; Biochemistry ; Medicine ; Immunology ; Antibody ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Molecular Biology Techniques and Applications
Authors: Ruifeng Wang | Jieying Zang | Hao Zhong | Yunsen Zhang | Defang Ouyang
Source: npj Drug Discovery. (article, 2025-06-04)
Field: Materials Science — Biomaterials

Understanding the molecular insights of marketed liposomal drugs using molecular dynamics simulations of reduced scale coarse-grained models The complexity of the internal structure of liposome remains insufficiently understood, posing challenges to the rational design and development of liposomal formulations. In this study, we employed coarse-grained molecular dynamics simulation to investigate the structural details of the commercially available nine liposomal formulations, with five passive loading systems (Arikayce Kit®, Visudyne®, Ambisome®, Mepact®, and Exparel®) and four active loading systems (Doxil®, Myocet®, Onivyde®, and Vyxeos®). In five passive loading liposome systems, protonation of drug molecules significantly reduces their binding to phospholipid membranes and even drastically alters the morphology and vesicle size in multivesicular liposomes. However, the orientation of drug molecules in lipid membranes is independent of protonation, with hydrophobic part inward and hydrophilic part outward. In four active loading systems, the presence of ions within the liposome cavity promotes the self-aggregation of drugs, thereby enhancing drug retention and release profiles. This study provided valuable molecular insights for marketed liposomes formulation. Molecular dynamics ; Scale (ratio) ; Computer science ; Computational biology ; Chemistry ; Computational chemistry ; Physics ; Biology Nanoparticle-Based Drug Delivery ; Lipid Membrane Structure and Behavior ; Surfactants and Colloidal Systems
Authors: Nanxuan Wu | Chao Qian | Zhedong Wang | Xiaoyue Zhu | Xiaogan Cheng | Er-Ping Li | Hongsheng Chen
Source: Advanced Functional Materials (article, 2025-04-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Accelerating Cross‐Scenario Metasurface Adaptability with Plug‐and‐Play Kernel Abstract The adaptivity of metasurfaces depicts an important behavior of dynamically adjusting their internal properties to adapt to changing environments and cater to various demands. In spite of the proliferation of intelligence‐driven metasurfaces, they still lack the analogical reasoning to execute cross‐scenario tasks due to the random and unpredictable scattering events. Here, a compatible plug‐and‐play scheme is proposed to assist metasurfaces adapt from one to another environment. Unlike conventional step‐by‐step training, such a scheme enables the rapid establishment of reliable neural networks with physical interpretability by integrating past experience into a package kernel. Taking the invisibility cloak as a demonstration, a fully intelligent system is set up, and carried out a three‐stage adaptability validation: point‐to‐point, path‐to‐path, and scene‐to‐scene, suggesting a substantial speed improvement compared with direct learning. Furthermore, by capitalizing on the resonant metasurfaces, the plug‐and‐play kernel is successfully extended to broadband performance with a relative bandwidth of 50%. work provides a powerful and easy‐to‐access recipe for advancing metasurfaces in new and even unknown environments and fosters the shining and bloom of intelligent adaptive meta‐devices. Adaptability ; Materials science ; Kernel (algebra) ; Spark plug ; Plug and play ; Nanotechnology ; Systems engineering ; Mechanical engineering ; Computer science ; Engineering ; Biology ; Ecology ; Operating system Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Fei Zhang | Hanlin Bao | Mingbo Pu | Yinghui Guo | Tongtong Kang | Xiong Li | Qiong He | Mingfeng Xu | Xiaoliang Ma | Xiangang Luo
Source: Light Science & Applications (article, 2025-05-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dispersion-engineered spin photonics based on folded-path metasurfaces Spin photonics revolutionizes photonic technology by enabling precise manipulation of photon spin states, with spin-decoupled metasurfaces emerging as pivotal in complex optical field manipulation. Here, we propose a folded-path metasurface concept that enables independent dispersion and phase control of two opposite spin states, effectively overcoming the limitations of spin photonics in achieving broadband decoupling and higher integration levels. This advanced dispersion engineering is achieved by modifying the equivalent length of a folded path, generated by a virtual reflective surface, in contrast to previous methods that depended on effective refractive index control by altering structural geometries. Our approach unlocks previously unattainable capabilities, such as achieving achromatic focusing and achromatic spin Hall effect using the rotational degree of freedom, and generating spatiotemporal vector optical fields with only a single metasurface. This advancement substantially broadens the potential of metasurface-based spin photonics, extending its applications from the spatial domain to the spatiotemporal domain. Photonics ; Dispersion (optics) ; Nanophotonics ; Optics ; Materials science ; Optoelectronics ; Physics Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Orbital Angular Momentum in Optics
Authors: Minghao Ning | Haozong Zhong | Zhen Gu | Lingen Zhang | Ning Qu | Jun Ding | Tao Li | Lin Li
Source: Nanophotonics (article, 2025-02-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Enhanced optical encryption via polarization‐dependent multi‐channel metasurfaces Optical encryption offers a powerful platform for secure information transfer, combining low power consumption, high-speed transmission, and intuitive visualization. Metasurfaces, with their unprecedented ability to manipulate light across multiple degrees of freedom within quasi-two-dimensional nanostructures, are emerging as promising devices for advanced encryption. However, encryption capacity remains constrained by limited information channels. Here, we present a visual secret sharing (VSS) scheme utilizing metasurfaces with multiple polarization-dependent channels and minimized crosstalk. Using a global optimization strategy for nanostructure geometries across the entire metasurface, we successfully realize eight independent polarization channels with negligible crosstalk. By encoding both the key and information into these channels with a modified VSS scheme, we demonstrate the complete recovery of seven plaintexts. This strategy supports scalable, high-capacity encryption, and can incorporate additional optical degrees of freedom, offering advanced solutions for advanced secure communication, information storage, and anti-counterfeiting. Encryption ; Computer science ; Scalability ; Polarization (electrochemistry) ; Electronic engineering ; Materials science ; Computer network ; Engineering ; Chemistry Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Chaos-based Image/Signal Encryption