jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Luke Power | Krishnendu Guha
Source: arXiv (Cornell University) (preprint, 2024-05-14)
Field: Materials Science — Materials Chemistry

Feature Importance and Explainability in Quantum Machine Learning Many Machine Learning (ML) models are referred to as black box models, providing no real insights into why a prediction is made. Feature importance and explainability are important for increasing transparency and trust in ML models, particularly in settings such as healthcare and finance. With quantum computing's unique capabilities, such as leveraging quantum mechanical phenomena like superposition, which can be combined with ML techniques to create the field of Quantum Machine Learning (QML), and such techniques may be applied to QML models. This article explores feature importance and explainability insights in QML compared to Classical ML models. Utilizing the widely recognized Iris dataset, classical ML algorithms such as SVM and Random Forests, are compared against hybrid quantum counterparts, implemented via IBM's Qiskit platform: the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC). This article aims to provide a comparison of the insights generated in ML by employing permutation and leave one out feature importance methods, alongside ALE (Accumulated Local Effects) and SHAP (SHapley Additive exPlanations) explainers. Feature (linguistics) ; Quantum ; Computer science ; Artificial intelligence ; Machine learning ; Pattern recognition (psychology) ; Physics ; Philosophy ; Quantum mechanics Machine Learning in Materials Science ; Neural Networks and Applications ; Explainable Artificial Intelligence (XAI)
Authors: David L. Tabb | Mohammed Hanzala Kaniyar | Omar G. Rosas Bringas | Heaji Shin | Luciano Di Stéfano | Martin S. Taylor | Shaoshuai Xie | Ömer H. Yilmaz | John LaCava
Source: Journal of Proteins and Proteomics (article, 2024-09-17)
Field: Chemistry — Spectroscopy

Interrogating data-independent acquisition LC–MS/MS for affinity proteomics The online version contains supplementary material available at 10.1007/s42485-024-00166-4. Workflow ; Proteome ; Proteomics ; Computer science ; Missing data ; Label-free quantification ; Software ; Quantitative proteomics ; Computational biology ; Chemistry ; Feature (linguistics) ; Data mining ; Pattern recognition (psychology) ; Bioinformatics ; Artificial intelligence ; Biology ; Machine learning ; Database ; Programming language ; Biochemistry Advanced Proteomics Techniques and Applications ; Biosensors and Analytical Detection ; Protein purification and stability
Authors: Laurine Lagache | Yanis Zirem | Émilie Le Rhun | Isabelle Fournier | Michel Salzet
Source: Molecular & Cellular Proteomics (article, 2024-12-05)
Field: Chemistry — Spectroscopy

Predicting Protein Pathways Associated to Tumor Heterogeneity by Correlating Spatial Lipidomics and Proteomics: The Dry Proteomic Concept Prediction of proteins and associated biological pathways from lipid analyses via matrix-assisted laser desorption/ionization (MALDI) MSI is a pressing challenge. We introduced "dry proteomics," using MALDI MSI to validate spatial localization of identified optimal clusters in lipid imaging. Consistent cluster appearance across omics images suggests association with specific lipid and protein in distinct biological pathways, forming the basis of dry proteomics. The methodology was refined using rat brain tissue as a model, then applied to human glioblastoma, a highly heterogeneous cancer. Sequential tissue sections underwent omics MALDI MSI and unsupervised clustering. Spatial omics analysis facilitated lipid and protein characterization, leading to a predictive model identifying clusters in any tissue based on unique lipid signatures and predicting associated protein pathways. Application to rat brain slices revealed diverse tissue subpopulations, including successfully predicted cerebellum areas. Similarly, the methodology was applied to a dataset from a cohort of 50 glioblastoma patients, reused from a previous study. However, among the 50 patients, only 13 lipid signatures from MALDI MSI data were available, allowing for the identification of lipid-protein associations that correlated with patient prognosis. For cases lacking lipid imaging data, a classification model based on protein data was developed from dry proteomic results to effectively categorize the remaining cohort. Proteomics ; Glioblastoma ; Computational biology ; Quantitative proteomics ; Bioinformatics ; Chemistry ; Biology ; Cancer research ; Biochemistry Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Metabolomics and Mass Spectrometry Studies
Authors: Huan Chen | Zixin Wang | Xin Chen | Junli Wang
Source: Sensors (article, 2024-12-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tunable Beam Steering Metasurface Based on a PMN-PT Crystal with a High Electro-Optic Coefficient Existing tunable optical metasurfaces based on the electro-optic effect are either complex in structure or have a limited phase modulation range. In this paper, a simple rectangular metasurface structure based on a Pb(Mg<sub>1/3</sub>Nb<sub>2/3</sub>)O<sub>3</sub>-PbTiO<sub>3</sub> (PMN-PT) crystal with high electro-optic coefficient of 120 pm/V was designed to demonstrate its electrically tunable performance in the optical communication band through simulations. By optimizing the structure parameters, a tunable metasurface was generated that can induce a complete 2π phase shift for beam deflection while maintaining relatively uniform transmittance. Simulations further demonstrated the electrical tunability of the beam deflection direction and operating wavelength of the metasurface. This tunable optical metasurface, with its simple and easily fabricated structure, can promote the development and application of multifunctional and controllable metasurfaces. Its adjustable beam deflection direction and operating wavelength may find applications in fields such as optical communication systems and imaging. Beam steering ; Materials science ; Optics ; Deflection (physics) ; Transmittance ; Optoelectronics ; Wavelength ; Optical switch ; Beam (structure) ; Optical communication ; Phase modulation ; Physics ; Phase noise Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Bin Li | Yang Jinli | Sun Zhao‐xiang | Yang Shi‐min | Aiguo Ouyang | Yande Liu
Source: Journal of Chemometrics (article, 2024-05-28)
Field: Chemistry — Analytical Chemistry

Detection the internal quality of watermelon seeds based on terahertz imaging technology combined with image smoothing and enhancement algorithm Abstract The cultivation processes of watermelon seed are often affected by issues such as empty shells and defects, resulting in significant losses. To obtain high‐quality seeds, the terahertz imaging technology combined with image smoothing and enhancement algorithm was proposed to reduce the noise and non‐obvious features caused by the influence in the imaging process and realize the non‐destructive, efficient, and accurate detection of the internal quality of watermelon seeds. Initially, a terahertz imaging system with a spatial resolution of 0.4 mm was used to acquire images of watermelon seeds with varying levels of fullness. Subsequently, denoising techniques, including Gaussian filtering, median filtering, bilateral filtering, discrete wavelet transformation denoising, wavelet denoising, and principal component analysis denoising, were used to handle the terahertz spectral images of watermelon seeds in the frequency range of 1–1.5 THz, respectively. Image enhancement operations, involving segmented linear gray‐level transformation and fractional‐order differentiation, were performed on the terahertz images of watermelon seeds after denoising. The optimal image processing approach was determined based on defect assessment through threshold segmentation. Finally, the validation was conducted at a spatial resolution of 0.2 mm. The images at a spatial resolution of 0.4 mm were subjected to wavelet denoising and window slicing in segmented linear gray‐level transformation (WS‐SLT) enhancement; the results exhibited the following improvements in defect accuracy compared with untreated THz images. A 7.74% increase in accuracy was observed for empty seeds, along with a 6.29% increase in the defect ratio for defective seeds 1. The defect ratio for intact seeds was 0, and there was no significant difference in defect ratio accuracy for defective seeds 2. At a spatial resolution of 0.2 mm, the average defect ratio error of THz imaging handled by wavelet denoising and WS‐SLT was approximately 5.04%. In conclusion, the terahertz imaging technology coupled with wavelet denoising and WS‐SLT methods can be used to enhance the accuracy of internal defect detection in watermelon seeds, and it provides a technical foundation and reference for assessing watermelon seed fullness. Noise reduction ; Smoothing ; Artificial intelligence ; Wavelet ; Terahertz radiation ; Bilateral filter ; Image resolution ; Mathematics ; Pattern recognition (psychology) ; Image quality ; Non-local means ; Wavelet transform ; Computer vision ; Computer science ; Pixel ; Materials science ; Image (mathematics) ; Image denoising ; Optoelectronics Spectroscopy and Chemometric Analyses ; Terahertz technology and applications ; Powdery Mildew Fungal Diseases
Authors: Robert Zimmerleiter | Wolfgang Greibl | Gerold Meininger | Kristina Duswald | Günther Hannesschläger | Paul Gattinger | Matthias Rohm | Christian Fuczik | Robert E. Holzer | Markus Brandstetter
Source: Sensors (article, 2024-05-17)
Field: Chemistry — Analytical Chemistry

Sensor for Rapid In-Field Classification of Cannabis Samples Based on Near-Infrared Spectroscopy A rugged handheld sensor for rapid in-field classification of cannabis samples based on their THC content using ultra-compact near-infrared spectrometer technology is presented. The device is designed for use by the Austrian authorities to discriminate between legal and illegal cannabis samples directly at the place of intervention. Hence, the sensor allows direct measurement through commonly encountered transparent plastic packaging made from polypropylene or polyethylene without any sample preparation. The measurement time is below 20 s. Measured spectral data are evaluated using partial least squares discriminant analysis directly on the device's hardware, eliminating the need for internet connectivity for cloud computing. The classification result is visually indicated directly on the sensor via a colored LED. Validation of the sensor is performed on an independent data set acquired by non-expert users after a short introduction. Despite the challenging setting, the achieved classification accuracy is higher than 80%. Therefore, the handheld sensor has the potential to reduce the number of unnecessarily confiscated legal cannabis samples, which would lead to significant monetary savings for the authorities. Mobile device ; Cannabis ; Linear discriminant analysis ; Computer science ; Sample (material) ; Field (mathematics) ; Artificial intelligence ; Remote sensing ; Mathematics ; Medicine ; Chemistry ; Psychiatry ; Chromatography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Johanna Tüshaus | Stephan Eckert | Marius Fraefel | Yuxiang Zhou | Pauline Pfeiffer | Christiane Halves | Federico Fusco | Johannes Weigl | Lisa Hönikl | V.M. Butenschön | Rumyana Todorova | Hilka Rauert‐Wunderlich | Matthew The | Andreas Rosenwald | Volker Heinemann | Julian Walter Holch | Bernhard Meyer | Wilko Weichert | Carolin Mogler | Peer‐Hendrik Kuhn | Bernhard Küster
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-06-27)
Field: Chemistry — Spectroscopy

Towards routine proteome profiling of FFPE tissue: Insights from a 1,200 case pan-cancer study Abstract Proteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performance of experimental workflows. Here, we did so by analyzing 1,220 tumors from six cancer entities processed over the course of three years. Key findings include the need for a new normalization method ensuring equal and reproducible sample loading for LC-MS/MS analysis across cohorts, showing that tumors can, on average, be profiled to a depth of &gt;4,000 proteins and discovering that current software fails to process such large data sets. We report the first comprehensive pan-cancer proteome expression resource for FFPE material comprising 11,000 proteins which is of immediate utility to the scientific community by way of a web resource. It enables a range of analysis including quantitative comparisons of proteins between patients or cohorts or the discovery of protein fingerprints representing the tissue of origin, or proteins enriched in certain cancer entities. Profiling (computer programming) ; Computational biology ; Proteome ; Biology ; Bioinformatics ; Computer science Advanced Proteomics Techniques and Applications ; Protease and Inhibitor Mechanisms ; Advanced Biosensing Techniques and Applications
Authors: А. В. Блинов | Zafar Rekhman | Alexey Golik | A. A. Gvozdenko | Andrey Nagdalian | Максим Ребезов
Source: Agrarian science (article, 2024-04-25)
Field: Chemistry — Analytical Chemistry

An innovative form of the essential trace element copper for fortification of dairy products Microelementosis is a disease associated with a deficiency of certain vital microelements. Today, there are ways to combat the lack of essential micronutrients. In this article, the mechanochemical synthesis of a triple copper-containing complex with ascorbic acid and L-isoleucine, an essential amino acid, was carried out. Examination of the sample by X-ray diffractometry showed that the sample has a trigonal crystal structure with space group P31c. As a result of computer quantum chemical modeling, the values of the difference in total energy, chemical hardness, energy of the highest occupied molecular orbital and the lowest unoccupied molecular orbital were determined. We determined the optimal option for the interaction of copper with vitamin C and L- isoleucine, where the binding occurs through hydroxyl groups attached to the C 2 and C 3 atoms of ascorbic acid, and through the carboxyl group and α-amino group of isoleucine. The sample was examined by IR spectroscopy and confirmed by computer modeling data. The stability of the resulting complex was studied depending on the technological parameters — pH, temperature and exposure time. Using the Greco-Latin square method, a matrix for planning a multifactorial experiment was compiled. An analysis of the dependence of the change in optical density (∆ D) on pH, temperature and exposure time showed that the pH of the medium and the temperature of the solution have a significant effect on ∆ D: an increase in the pH of the medium and the temperature of the solution leads to an increase in ∆ D. Exposure time does not have a significant effect to change the optical density value (∆ D). The parameters at which sample stability is observed correspond to the lowest values of ∆ D: pH = 3–8, t = 25–70, τ = 5–15. The effect of the concentration of a copper-containing complex on the physicochemical parameters of milk was studied. It has been established that the optimal concentration of copper ascorbate isoleucinate for fortifying dairy products is 0.005 mol/l or less. Next, an organoleptic assessment of the indicators of milk enriched with copper ascorbate isoleucinate was carried out. The analysis of the results showed that the organoleptic parameters (smell and taste) of milk enriched with ascorbate-isoleucinate of copper are 0.1 points higher than those of milk enriched with the inorganic form of the essential trace element copper and 0.3 points lower than that of the control milk sample. Fortification ; TRACE (psycholinguistics) ; Trace element ; Copper ; Chemistry ; Food science ; Business ; Organic chemistry ; Philosophy Heavy Metals in Plants ; Animal Diversity and Health Studies ; Phytochemical and Pharmacological Studies
Authors: Lei Zhu | Xusheng Li | Liang Dong | Wenjing Xie | Guanyu Shang | Shah Nawaz Burokur | Xumin Ding
Source: Chinese Optics Letters (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Bi-layered coded metasurface for multi-functional hologram with broadband transmission and efficient reflection A multi-functional full-space metasurface based on frequency and polarization multiplexing is proposed.The metasurface unit consists of metallic patterns printed on the two faces of a single-layered dielectric substrate.The unit cell can control electromagnetic wavefronts to achieve a broadband transmission with amplitudes greater than 0.4 from 4.4 to 10.4 GHz.Meanwhile, at 11.7 GHz and 15.4 GHz, four high-efficiency reflection channels with a reflection amplitude greater than 0.8 are also realized.When illuminated by linearly polarized waves, five different functions can be realized at five different frequencies, which are demonstrated by theoretical calculations, full-wave simulations, and experimental measurements. Optics ; Broadband ; Reflection (computer programming) ; Wavefront ; Polarization (electrochemistry) ; Reflection coefficient ; Holography ; Amplitude ; Transmission (telecommunications) ; Materials science ; Optoelectronics ; Physics ; Computer science ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Sofia Goia | Gareth Cooper | D Norman | Charlotte Primeau | Michael Hall | Julian Hawley | Mark A. Williams
Source: Forensic Science International (article, 2024-07-27)
Field: Materials Science — Materials Chemistry

The use of micro-CT in the investigation of a case involving 3D printed firearms This paper highlights how micro-CT was used to assist in the investigation of hybrid firearms constructed using a mixture of plastic and metal components, as a complementary technique to the physical examination performed by firearms experts. In recent years, there has been an increase in the complexity and sophistication of 3D printed and hybrid firearm designs. This was also the case in the investigation presented herein, with the firearms seized demonstrating a step change in the threat level they pose through their complexity. Thus, we describe how data produced from micro-CT scans was used to help firearms experts study the viability and mechanics of two hybrid weapons prior to dismantling and test-firing. This process aided experts in determining whether components were 3D printed or manufactured through other means, whilst ensuring that a digital record (digital twin) was retained in case evidence was damaged during testing. Finally, we show how the data was presented visually through animations and as evidence in court. This proved to be imperative when communicating to the judge, jury, and wider investigating teams, the complex multiple components and mechanisms within the firearms. Sophistication ; 3d printed ; Jury ; Computer science ; Process (computing) ; Crime scene ; Poison control ; Forensic engineering ; Computer security ; Engineering ; Psychology ; Law ; Medicine ; Medical emergency ; Biomedical engineering High-Velocity Impact and Material Behavior ; Advanced X-ray and CT Imaging ; Conservation Techniques and Studies
Authors: Jian Feng | Yangyang Liu | Peiwei Liu | Yun Yang | Anzhen Xie | Jianhe Wei
Source: PLoS ONE (article, 2024-12-02)
Field: Chemistry — Organic Chemistry

Resinous included phloem as a key indicator of authentic or fake agarwood Agarwood, the resinous wood of the genus Aquilaria Lam. and Gyrinops Gaertn. of the family Thymelaeaceae, is a very valuable traditional medicinal material and spice. Due to the high economic value of agarwood, unscrupulous merchants have led to the prevalence of fake agarwood in the trade market in pursuit of high profits. Therefore, it is crucial to explore the characteristics of agarwood and establish a simple and rapid method to identify authenticity. This study compared the authenticity of the microstructure of agarwood from different producing areas with that of artificially simulated fake agarwood. The included phloem of authentic agarwood contains brown to brownish resin. And these resins were naturally and stably distributed. The fake agarwood is divided into two categories: one itself is non-agarwood wood (without included phloem), and the other is artificially counterfeiting. However, the filling of resin in the included phloem of agarwood did not occur after artificially simulated counterfeiting treatments. Of the 18 commercially available samples, 10 had the same microstructure as agarwood, but six of them were not completely filled with resin in the included phloem. Therefore, the resinous included phloem is a key characteristic structure of agarwood. It can be used as a basis for authenticity identification of agarwood. This will provide a convenient and rapid method for promoting and popularizing agarwood authentication in trade, customs enforcement, CITES management, and other fields. Agarwood ; Phloem ; Botany ; Biology ; Medicine ; Pathology Wood and Agarwood Research ; Cultural Heritage Materials Analysis ; Identification and Quantification in Food
Authors: Thang V. Pham | Alex A. Henneman | Nam X Truong | Connie R. Jiménez
Source: Bioinformatics (article, 2024-06-29)
Field: Chemistry — Spectroscopy

msproteomics sitereport: reporting DIA-MS phosphoproteomics experiments at site level with ease sitereport is available as a command line tool in the Python package msproteomics, released under the Apache License 2.0 and available from the Python Package Index (PyPI) at https://pypi.org/project/msproteomics and GitHub at https://github.com/tvpham/msproteomics. Phosphoproteomics ; Python (programming language) ; Computer science ; Software ; MIT License ; Software engineering ; Operating system ; Phosphorylation ; Chemistry ; Protein phosphorylation ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Jiancheng Li | Yi Xiong | Shichao Feng | Chongle Pan | Xuan Guo
Source: Bioinformatics Advances (article, 2024-01-01)
Field: Chemistry — Spectroscopy

CloudProteoAnalyzer: scalable processing of big data from proteomics using cloud computing This application is available online at https://sipros.oscer.ou.edu/ or https://sipros.unt.edu for free use. The source code is available at https://github.com/Biocomputing-Research-Group/CloudProteoAnalyzer under the GPL version 3.0 license. Cloud computing ; Computer science ; Proteomics ; Scalability ; Upload ; Big data ; Software ; Source code ; Process (computing) ; Data science ; Database ; World Wide Web ; Data mining ; Operating system ; Biology Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Bioinformatics and Genomic Networks