jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mario Ramos Maldonado | Thays Duarte Sepúlveda | Francisco Gatica Neira | Diego Venegas Vásconez
Source: Maderas Ciencia y tecnología (article, 2024-07-29)
Field: Materials Science — Polymers and Plastics

Machine learning para predecir la calidad del secado de chapas en la industria de tableros contrachapados de Pinus radiata El Aprendizaje automático o Machine learning es una herramienta que está siendo utilizada para optimizar procesos industriales de alta complejidad. En la industria de producción de paneles contrachapados, el secado de chapas es uno de los procesos más importantes ya que permite obtener productos con alta calidad. La naturaleza biológica y alta variabilidad estructural de la madera hace que su procesamiento industrial sea multivariado y difícil de controlar. La gran cantidad de variables presentes y la posibilidad cada vez más frecuente de medirlas en tiempo real están permitiendo la disponibilidad de una gran cantidad de datos. En la actualidad, el enfoque basado en datos y las técnicas de Inteligencia Artificial, específicamente Machine learning, pueden permitir enfoques robustos de predicción y de control. En la industria de procesos con altos niveles de automatización es posible viabilizar la toma de decisiones para predecir la calidad del producto, monitoreando las variables de control explicativas. El objetivo de este trabajo fue evaluar el comportamiento de tres algoritmos de Machine learning para predecir la calidad del proceso de secado de chapas a partir de un número considerable de variables de entrada capturadas de un proceso industrial real. Se utilizó la plataforma Weka y código Python. Se evaluaron los algoritmos: K-Nearest-Neighbor, eXtreme Gradient Boosting y Support Vector Machine. Se realizó reducción de variables y dimensionalidad de análisis de correlación y de componentes principales. Los resultados demostraron que eXtreme Gradient Boosting logró una precisión del 76 % en la predicción de resultados de calidad. Finalmente, se concluye que la metodología de ingeniería de datos y los algoritmos fueron eficientes para predecir los datos industriales. Humanities ; Pinus radiata ; Art ; Biology ; Botany Textile materials and evaluations ; Meat and Animal Product Quality
Authors: Devin M. Makey | Brandon T. Ruotolo
Source: Expert Review of Proteomics (review, 2024-06-02)
Field: Chemistry — Spectroscopy

Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis IM-MS has the potential to enhance the depth and efficiency of biotherapeutic characterization by providing additional insights into conformational changes, post-translational modifications, and impurity profiles. The rapid timescale of IM-MS positions it well to enhance the information content of existing assays through its facile integration with standard liquid-phase separation techniques that are commonly used for biopharmaceutical analysis. Mass spectrometry ; Ion-mobility spectrometry ; Biopharmaceutical ; Chromatography ; Chemistry ; Ion ; Analytical Chemistry (journal) Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Protein purification and stability
Authors: Raúl Losantos | Giacomo Prampolini | Antonio Monari
Source: Molecules (article, 2024-04-12)
Field: Materials Science — Materials Chemistry

A Portrait of the Chromophore as a Young System—Quantum-Derived Force Field Unraveling Solvent Reorganization upon Optical Excitation of Cyclocurcumin Derivatives The study of fast non-equilibrium solvent relaxation in organic chromophores is still challenging for molecular modeling and simulation approaches, and is often overlooked, even in the case of non-adiabatic dynamics simulations. Yet, especially in the case of photoswitches, the interaction with the environment can strongly modulate the photophysical outcomes. To unravel such a delicate interplay, in the present contribution we resorted to a mixed quantum-classical approach, based on quantum mechanically derived force fields. The main task is to rationalize the solvent reorganization pathways in chromophores derived from cyclocurcumin, which are suitable for light-activated chemotherapy to destabilize cellular lipid membranes. The accurate and reliable decryption delivered by the quantum-derived force fields points to important differences in the solvent's reorganization, in terms of both structure and time scale evolution. Chromophore ; Excitation ; Portrait ; Quantum ; Field (mathematics) ; Solvent ; Chemistry ; Photochemistry ; Physics ; Quantum mechanics ; Art history ; Art ; Organic chemistry ; Mathematics Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Photochemistry and Electron Transfer Studies
Authors: Hiroshi Shinotsuka | Kenji Nagata | Hideki Yoshikawa | Shuichi Ogawa | Akitaka Yoshigoe
Source: Applied Surface Science (article, 2024-12-03)
Field: Materials Science — Surfaces, Coatings and Films

Bayesian estimation analysis of X-ray photoelectron spectra: Application to Si 2p spectrum analysis of oxidized silicon surfaces Silicon ; Spectral line ; X-ray photoelectron spectroscopy ; Materials science ; Spectrum (functional analysis) ; Analytical Chemistry (journal) ; Computational physics ; Chemistry ; Physics ; Optoelectronics ; Nuclear magnetic resonance ; Environmental chemistry Electron and X-Ray Spectroscopy Techniques ; Advancements in Photolithography Techniques ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Ching‐Han Chang | Pawel L. Urban
Source: ACS Omega (article, 2024-10-11)
Field: Chemistry — Spectroscopy

Does the Formation of a Taylor Cone in a Pulsating Electrospray Directly Impact Mass Spectrometry Signals? Electrospray ionization (ESI) remains the dominant technique in mass spectrometry (MS)-based analyses. Here, we investigated the relationship between a crucial aspect of ESI, the formation of the Taylor cone, and the MS ion current by utilizing a triple quadrupole (QqQ) mass spectrometer coupled with a streaming high-speed camera and a 3-ring electrode system. In one test, ion current over a 30-s plume gate (a ring electrode) opening was compared with the Taylor cone occurrence analyzed offline, with Spearman's correlation coefficients consistently near 0 despite parameter variations. In another test, real-time detection of Taylor cones was synchronized with QqQ-MS, selectively opening (de-energizing) the plume gate based on the Taylor cone status. This approach enabled matching the ion current with the Taylor cone occurrence. There was no apparent difference between the MS signals recorded in the presence and absence of a Taylor cone. Additionally, a Faraday plate was employed as a detector in offline experiments, revealing agreement between the frequency of liquid meniscus (Taylor cone) oscillation (∼1.92 kHz)-measured by high-speed imaging-and the frequency of spray current (∼1.93 kHz). We suggest that the lack of positive correlations in the MS experiments is due to intrinsic ion carryover during transit from the ion source to the detector and due to the insufficient data acquisition rate of the mass spectrometer, which erases short-term fluctuations of ion current. Electrospray mass spectrometry ; Electrospray ; Mass spectrometry ; Chemistry ; Cone (formal languages) ; Chromatography ; Computer science ; Algorithm Mass Spectrometry Techniques and Applications ; Electrohydrodynamics and Fluid Dynamics ; Analytical Chemistry and Chromatography
Authors: Nicholas B. Hamilton | Steve Arns | Mee Shelley | Irene Bechis | John C. Shelley
Source: ChemRxiv (preprint, 2024-03-25)
Field: Chemistry — Organic Chemistry

Calculating Apparent pKa Values of Ionizable Lipids in Lipid Nanoparticle Creating new ionizable lipids for use in lipid nanoparticles (LNPs) is an active field of research. One of the critical properties for selecting suitable ionizable lipids is the apparent pKa value of the lipid as formulated in an LNP. We have developed a structure-based, computational methodology for the prediction of the apparent pKa value of ionizable lipids within LNPs. This methodology has been validated for the three most successful ionizable lipids to date which are present in the mRNA LNP COVID-19 vaccines COMIRNATY® (Pfizer/BioNTech) and Spikevax® (Moderna), and the siRNA LNP therapeutic Onpattro® (Alnylam). The calculation was also applied to Lipid A, a variant of the ionizable lipid used in COMIRNATY®. We believe that this new technology permits systematic computational prescreening of ionizable lipids to select the most promising candidates for synthesis and experimental testing, accelerating the formulation improvement process and reducing costs. Chemistry ; Nanoparticle ; Biophysics ; Nanotechnology ; Materials science ; Biology Free Radicals and Antioxidants ; Process Optimization and Integration ; Computational Drug Discovery Methods
Authors: Ilmārs Apeināns | Marks Sondors | Lienīte Litavniece | Sergejs Kodors | Imants Zarembo | D. Feldmane
Source: Environment Technology Resources Proceedings of the International Scientific and Practical Conference (article, 2024-06-22)
Field: Chemistry — Analytical Chemistry

CHERRY FRUITLET DETECTION USING YOLOV5 OR YOLOV8? Agriculture 5.0 incorporates autonomous decision-making systems in order to make agriculture more productive. Our study is related to the development of the autonomous orchard monitoring system using unnamed aerial vehicles for automatic fruiting assessment and yield forecasting. Respectively, artificial intelligence must be developed to count fruits in an orchard. The modern solutions are mainly data-based. Therefore, we collected and annotated cherry dataset with natural images (CherryBBCH81) for neural network training. The goal of the experiment was to select the optimal “You Look Only Once” (YOLO) model for the rapid development of fruit detection. Our experiment showed that YOLOv5m provided better results for CherryBBCH81 – mean average precision (mAP) at 0.5 0.886 in comparison with YOLOv8m mAP@0.5 0.870. However, additional tests with dataset Pear640 showed that YOLOv8m can outperform YOLOv5m: 0.951 vs 0.943 (mAP@0.5). Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Identification and Quantification in Food
Authors: Jiongzhi Zheng | Zheng Chang | Changpeng Lin | Chongjia Lin | Yanguang Zhou | Baoling Huang | Ruiqiang Guo | Geoffroy Hautier
Source: arXiv (Cornell University) (preprint, 2024-06-03)
Field: Materials Science — Materials Chemistry

Ineffectiveness of Formamidine in Suppressing Ultralow Thermal Conductivity in Cubic Hybrid Perovskite FAPbI3 Fundamentally understanding the lattice dynamics and microscopic mechanisms of thermal transport in cubic hybrid organic-inorganic perovskites remains elusive, primarily due to their strong anharmonicity and frequent phase transitions. In this work, we comprehensively investigate the thermal transport behavior in cubic hybrid perovskite FAPbI3, integrating first principles-based anharmonic lattice dynamics with a linearized Wigner transport formula. The Temperature Dependent Effective Potential (TDEP) technique allows us to stabilize the negative soft modes, primarily dominated by organic cations, at finite temperatures in cubic FAPbI3. We then predict an ultra-low thermal conductivity of ~0.63 Wm^(-1) K^(-1) in cubic FAPbI3 at 300 K, with a temperature dependence of T^(-0.740), suggesting a good crystalline nature of phonon transport. Notably, the ultra-low thermal conductivity in cubic FAPbI3 is primarily attributed to the [PbI3]1- units, challenging the conventional focus on organic FA+ cations. This shift in focus is due to the presence of Pb(s)-I(p) anti-bonding sates within the [PbI3]1- units. Furthermore, thermal transport in cubic FAPbI3 is predominantly governed by the particle-like phonon propagation channel across the entire temperature range of 300-500 K, a result of diminished suppression of low-frequency phonons by FA+ cations and large inter-branch spacings. Finally, our findings underscore that the anharmonic force constants are highly temperature-sensitive, leading to underestimations of thermal conductivity when relying on 0-K anharmonic force constants. Our study not only elucidates the microscopic mechanisms of thermal transport in cubic FAPbI3 but also provides a crucial framework for the discovery, design, and understanding of hybrid organic-inorganic compounds with ultra-low thermal conductivity. Perovskite (structure) ; Cubic crystal system ; Thermal conductivity ; Materials science ; Conductivity ; Thermal ; Chemical engineering ; Chemistry ; Composite material ; Thermodynamics ; Physics ; Crystallography ; Physical chemistry ; Engineering Thermal Expansion and Ionic Conductivity ; Advanced Thermoelectric Materials and Devices ; Optical properties and cooling technologies in crystalline materials
Authors: Zhichao Qiu | Gangao Li | Zongbao Huang | Xiuhan He | Zilin Zhang | Zhiwei Li | Huiling Du
Source: Frontiers in Plant Science (article, 2024-05-30)
Field: Chemistry — Analytical Chemistry

Research on non-destructive and rapid detection technology of foxtail millet moisture content based on capacitance method and Logistic-SSA-ELM modelling Moisture content testing of agricultural products is critical for quality control, processing efficiency and storage management. Testing foxtail millet moisture content ensures stable foxtail millet quality and helps farmers determine the best time to harvest. A differential capacitance moisture content detection device was designed based on STM32 and PCAP01 capacitance digital converter chip. The capacitance method combined with the back-propagation(BP) algorithm and the extreme learning machine(ELM) algorithm was chosen to construct an analytical model for foxtail millet moisture content, temperature, and volume duty cycle. This work performs capacitance measurements on foxtail millet with different moisture contents, temperatures, and proportions of the measured substance occupying the detection area (that is, the volumetric duty cycle). On this foundation, the sparrow search algorithm (SSA) is used to optimize the BP and ELM models. However, SSA may encounter problems such as falling into local optimization solutions due to the reduction of population diversity in the late iterations. As a consequence, Logistic algorithm is introduced to optimize SSA, making it more appropriate for solving specific problems. Upon comparative analysis, the model predicted using the Logistic-SSA-ELM algorithm was more accurate. The results indicate that the predicted values of prediction set coefficient of determination (RP), prediction set root mean square error (RMSEP) and prediction set ratio performance deviation (RPDP) were 0.7016, 3.7150 and 1.4035, respectively. This algorithm has excellent prediction performance and can be used as a model for detection of foxtail millet moisture content. In view of the important role of foxtail millet moisture content detection in acquisition and storage, it is particularly important to study a nondestructive and fast online real-time detection method. The designed capacitive sensor with differential structure has well stabilization and high accuracy, which can be further studied in depth and gradually move towards the general trend of agricultural development of smart agriculture and precision agriculture. Foxtail ; Water content ; Capacitance ; Moisture ; Algorithm ; Mathematics ; Computer science ; Environmental science ; Statistics ; Agronomy ; Engineering ; Meteorology ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Li‐Lin Du | Zhengwei Huang | Chun Li | Ling Jiang
Source: RSC Advances (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Quantitative analysis of the illegal addition of Atenolol in Panax notoginseng based on NIR–MIR spectral data fusion and calibration transfer To address the issue of the common illegal addition of Atenolol in Panax notoginseng, we propose an approach that realizes multivariate calibration transfer between different particle sizes based on near-infrared (NIR) and mid-infrared (MIR) spectral data fusion. To achieve high prediction accuracy, we construct three data fusion schemes (full-spectrum fusion, feature-level fusion, and decision-level fusion) that combine NIR and MIR spectral data. Among three data fusion schemes, the feature-level fusion based on the UVE-SPA-PLS model for 120-mesh spectral data achieves optimal prediction accuracy. Here, a Piecewise Direct Standardization (PDS) algorithm has been applied to calibration transfer from 100-mesh and 80-mesh to 120-mesh to reduce the influence of particle size and improve the robustness of the model. The correlation coefficient (<i>R</i><sup>2</sup>) of 100-mesh, and 80-mesh prediction sets can reach 0.9861 and 0.9823, respectively. The corresponding root mean square error (RMSE) are 0.1545 and 0.2045, respectively. This research provides a method for illegal additions in precious herbs and reduces the effect of particle size on spectral modeling, enabling high-precision quantitative detection. In addition, it has important application prospects in reducing experimental losses of precious medicinal materials and ensuring the safe use of Chinese and Western medicines, which provides an alternative method for non-destructive testing. Panax notoginseng ; Calibration ; Atenolol ; Chemistry ; Fusion ; Computer science ; Chromatography ; Medicine ; Mathematics ; Statistics ; Internal medicine Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Food Quality and Safety Studies
Authors: Ane Håkansson
Source: Nuclear Engineering and Design (article, 2024-01-05)
Field: Materials Science — Materials Chemistry

ANItA – A new Swedish national competence centre in new nuclear power technology In 2021, a proposal was submitted to the Swedish Energy Agency, which meant that the three leading Swedish universities: Uppsala University, KTH and Chalmers as well as the Swedish and Finnish nuclear power industry would together form a national competence centre for research and development work regarding the introduction of small modular reactors in Sweden. The proposal, called, ANItA (Academic-industrial Nuclear technology Initiative to Achieve a sustainable energy future) entailed a commitment for ten years and was granted funds for the first five years with an option for continued funding for the following five years. The initial research portfolio includes fourteen projects spanning a wide range of technical and non-technical aspects of small modular reactor (SMR) technology. During the last few months, the projects have been staffed with both national and international doctoral students and postdocs and thus constitute a contribution to securing the important supply of expertise in the nuclear field in Sweden. ANItA has attracted great interest from the surrounding society, which includes both politics and mass media and discussions are being held with potential new industrial partners. The renewed interest in new nuclear power in Sweden has further strengthened ANItA's role and the development is moving in a direction that enables to fulfil the basic idea behind ANItA, namely that through research and development work produce knowledge-based decision support for politicians and policymakers in the introduction of new nuclear power technology in Sweden. Nuclear power ; Competence (human resources) ; Political science ; Portfolio ; Work (physics) ; Politics ; Engineering ; Agency (philosophy) ; Public relations ; Management ; Business ; Sociology ; Social science ; Economics ; Finance ; Mechanical engineering Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies ; Nuclear reactor physics and engineering
Authors: Sibashish Chakraborty | Rishabh Vij | Richa Goel | Bhanu Pratap Singh | Kunaal Dhingra | Venu Gopal Achanta | Satish Kumar Dubey
Source: Scientific Reports (article, 2024-11-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

PlQC based highly sensitive and reproducible novel SERS active substrate for biomolecule detection with high specificity Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for biomolecule sensing. When combined with a broadband plasmonic structure, label-free, highly sensitive detection of specific molecules is possible. It is non-invasive, sensitive, fast, and can be used for in-situ analysis, unlike enzyme-linked immunosorbent assay, fluorescence immunoassay, and radioimmunoassay. However, one of the challenges is to have an active SERS substrate that is uniform, sensitive, and specific to molecules of interest. In this work, we report plasmonic quasicrystal (PlQC) as a highly sensitive (enhancement factor ≈ 10<sup>14</sup>), uniform, reproducible, and stable (concerning time and ambient conditions) SERS active substrate. Herein, we present the label-free sensing of standard cotinine (up to 1 ng/mL), the ideal biomarker for nicotine exposure due to its long lifetime compared to nicotine. In addition, up to 1 nanogram level of cotinine has also been detected in synthetic urine and saliva employing PlQC as a SERS-active substrate. Our results on the principal component analysis of Rhodamine 6G and Cotinine demonstrate that broadband, dispersionless PlQC is suitable for label-free detection of single biomolecules. Biomolecule ; Substrate (aquarium) ; Substrate specificity ; Nanotechnology ; Computer science ; Computational biology ; Chemistry ; Materials science ; Biology ; Biochemistry ; Enzyme Gold and Silver Nanoparticles Synthesis and Applications ; Advanced biosensing and bioanalysis techniques ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Geoffroy Gaschignard | Maxime Millet | Apolline Bruley | Karim Benzerara | Manuela Dezi | Fériel Skouri‐Panet | Élodie Duprat | Isabelle Callebaut
Source: Proteins Structure Function and Bioinformatics (article, 2024-01-22)
Field: Materials Science — Materials Chemistry

<scp>AlphaFold2</scp>‐guided description of<scp>CoBaHMA</scp>, a novel family of bacterial domains within the heavy‐metal‐associated superfamily Three-dimensional (3D) structure information, now available at the proteome scale, may facilitate the detection of remote evolutionary relationships in protein superfamilies. Here, we illustrate this with the identification of a novel family of protein domains related to the ferredoxin-like superfold, by combining (i) transitive sequence similarity searches, (ii) clustering approaches, and (iii) the use of AlphaFold2 3D structure models. Domains of this family were initially identified in relation with the intracellular biomineralization of calcium carbonates by Cyanobacteria. They are part of the large heavy-metal-associated (HMA) superfamily, departing from the latter by specific sequence and structural features. In particular, most of them share conserved basic amino acids (hence their name CoBaHMA for Conserved Basic residues HMA), forming a positively charged surface, which is likely to interact with anionic partners. CoBaHMA domains are found in diverse modular organizations in bacteria, existing in the form of monodomain proteins or as part of larger proteins, some of which are membrane proteins involved in transport or lipid metabolism. This suggests that the CoBaHMA domains may exert a regulatory function, involving interactions with anionic lipids. This hypothesis might have a particular resonance in the context of the compartmentalization observed for cyanobacterial intracellular calcium carbonates. Context (archaeology) ; Protein family ; Proteome ; Biology ; Computational biology ; Biochemistry ; Function (biology) ; SUPERFAMILY ; Compartmentalization (fire protection) ; Protein structure ; Chemistry ; Evolutionary biology ; Gene Enzyme Structure and Function ; Genomics and Phylogenetic Studies ; Protein Structure and Dynamics