jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ahrum Son | H. S. Kim | Jolene K. Diedrich | Casimir Bamberger | Daniel B. McClatchy | John R. Yates
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-05-30)
Field: Chemistry — Spectroscopy

<i>In vivo</i> Protein Footprinting Reveals the Dynamic Conformational Changes of Proteome of Multiple Tissues in Progressing Alzheimer’s Disease Abstract Numerous studies have investigated changes in protein expression at the system level using proteomic mass spectrometry, but only recently have studies explored the structure of proteins at the proteome level. We developed covalent protein painting (CPP), a protein footprinting method that quantitatively labels exposed lysine, and have now extended the method to whole intact animals to measure surface accessibility as a surrogate of in vivo protein conformations. We investigated how protein structure and protein expression change as Alzheimer’s disease (AD) progresses by conducting in vivo whole animal labeling of AD mice. This allowed us to analyze broadly protein accessibility in various organs over the course of AD. We observed that structural changes of proteins related to ‘energy generation,’ ‘carbon metabolism,’ and ‘metal ion homeostasis’ preceded expression changes in the brain. We found that proteins in certain pathways undergoing structural changes were significantly co-regulated in the brain, kidney, muscle, and spleen. Proteome ; Footprinting ; In vivo ; Proteomics ; Cell biology ; Chemistry ; Tau protein ; Biology ; Biochemistry ; Computational biology ; Alzheimer's disease ; Disease ; Gene ; Transcription factor ; Genetics ; Medicine ; Pathology Advanced Proteomics Techniques and Applications ; Biotin and Related Studies ; Alzheimer's disease research and treatments
Authors: Andy Lin | Brooke L. Deatherage Kaiser | Janine R. Hutchison | Jeffrey A. Bilmes | William Stafford Noble
Source: Bioinformatics (article, 2023-01-24)
Field: Chemistry — Spectroscopy

MS1Connect: a mass spectrometry run similarity measure Supplementary data are available at Bioinformatics online. Measure (data warehouse) ; Similarity measure ; Similarity (geometry) ; Mass spectrometry ; Computer science ; Data mining ; Chemistry ; Chromatography ; Artificial intelligence Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Yachong Yang | Arun Kumar Kuchibhotla | Eric Tchetgen Tchetgen
Source: arXiv (Cornell University) (preprint, 2023-07-31)
Field: Chemistry — Analytical Chemistry

Forster-Warmuth Counterfactual Regression: A Unified Learning Approach Series or orthogonal basis regression is one of the most popular non-parametric regression techniques in practice, obtained by regressing the response on features generated by evaluating the basis functions at observed covariate values. The most routinely used series estimator is based on ordinary least squares fitting, which is known to be minimax rate optimal in various settings, albeit under stringent restrictions on the basis functions and the distribution of covariates. In this work, inspired by the recently developed Forster-Warmuth (FW) learner, we propose an alternative series regression estimator that can attain the minimax estimation rate under strictly weaker conditions imposed on the basis functions and the joint law of covariates, than existing series estimators in the literature. Moreover, a key contribution of this work generalizes the FW-learner to a so-called counterfactual regression problem, in which the response variable of interest may not be directly observed (hence, the name ``counterfactual'') on all sampled units, and therefore needs to be inferred in order to identify and estimate the regression in view from the observed data. Although counterfactual regression is not entirely a new area of inquiry, we propose the first-ever systematic study of this challenging problem from a unified pseudo-outcome perspective. In fact, we provide what appears to be the first generic and constructive approach for generating the pseudo-outcome (to substitute for the unobserved response) which leads to the estimation of the counterfactual regression curve of interest with small bias, namely bias of second order. Several applications are used to illustrate the resulting FW-learner including many nonparametric regression problems in missing data and causal inference literature, for which we establish high-level conditions for minimax rate optimality of the proposed FW-learner. Estimator ; Counterfactual thinking ; Covariate ; Minimax ; Econometrics ; Regression ; Regression analysis ; Nonparametric regression ; Mathematics ; Statistics ; Mathematical optimization Spectroscopy and Chemometric Analyses ; Machine Learning and ELM ; Optimal Experimental Design Methods
Authors: Ricardo Espinosa
Source: Entropy (article, 2023-01-12)
Field: Chemistry — Analytical Chemistry

EspEn Graph for the Spatial Analysis of Entropy in Images The quantification of entropy in images is a topic of interest that has had different applications in the field of agronomy, product generation and medicine. Some algorithms have been proposed for the quantification of the irregularity present in an image; however, the challenges to overcome in the computational cost involved in large images and the reliable measurements in small images are still topics of discussion. In this research we propose an algorithm, EspEn Graph, which allows the quantification and graphic representation of the irregularity present in an image, revealing the location of the places where there are more or less irregular textures in the image. EspEn is used to calculate entropy because it presents reliable and stable measurements for small size images. This allows an image to be subdivided into small sections to calculate the entropy in each section and subsequently perform the conversion of values to graphically show the regularity present in an image. In conclusion, the EspEn Graph returns information on the spatial regularity that an image with different textures has and the average of these entropy values allows a reliable measure of the general entropy of the image. Entropy (arrow of time) ; Computer science ; Artificial intelligence ; Graph ; Mathematics ; Pattern recognition (psychology) ; Image processing ; Image (mathematics) ; Theoretical computer science Spectroscopy and Chemometric Analyses ; Cell Image Analysis Techniques ; Smart Agriculture and AI
Authors: Brahim Mohammedi | Hocine Benkharfia | Brahim Beladel | N. Mellel | K. Bessine | N.E. Moulai
Source: Atom Indonesia (article, 2023-11-23)
Field: Materials Science — Materials Chemistry

Neural Network Predictions of Atomic Form Factors and Incoherent Scattering Functions In order to predict atomic form factors and incoherent scattering functions which are used to calculate the coherent and incoherent total scattering cross sections, a technique based on artificial neural networks of the multilayer type was implemented. In this context, two neural models have been developed and compared with those in the literature. This study revealed both the accuracy of the results obtained and the effectiveness of the designed model. The mean relative error for the least estimated property does not exceed 16.5 %. The software realized in this way give a prediction of the above parameters for the input variables Z: Atomic number, x: sin(ϑ/2)/λ and E: Photon energy, and it provides users with flexibility for prediction. The advantages of this technique lie in its very fast handling, due to its ease of use, and in the two integrated networks, which it guarantees for a variety of input parameters such as atomic number, photon energy, and momentum transfer variable. Artificial neural network ; Context (archaeology) ; Scattering ; Flexibility (engineering) ; Computer science ; Photon ; Incoherent scatter ; Property (philosophy) ; Energy (signal processing) ; Momentum transfer ; Computational physics ; Physics ; Algorithm ; Artificial intelligence ; Optics ; Mathematics ; Quantum mechanics ; Statistics Radiation Shielding Materials Analysis ; Electron and X-Ray Spectroscopy Techniques
Authors: Alexander Schröder | Leon van Velzen | Maurits Kelder | Sascha Schäfer
Source: arXiv (Cornell University) (preprint, 2023-07-31)
Field: Materials Science — Surfaces, Coatings and Films

Improving the temporal resolution of event-based electron detectors using neural network cluster analysis Novel event-based electron detector platforms provide an avenue to extend the temporal resolution of electron microscopy into the ultrafast domain. Here, we characterize the timing accuracy of a detector based on a TimePix3 architecture using femtosecond electron pulse trains as a reference. With a large dataset of event clusters triggered by individual incident electrons, a neural network is trained to predict the electron arrival time. Corrected timings of event clusters show a temporal resolution of 2 ns, a 1.6-fold improvement over cluster-averaged timings. This method is applicable to other fast electron detectors down to sub-nanosecond temporal resolutions, offering a promising solution to enhance the precision of electron timing for various electron microscopy applications. Detector ; Temporal resolution ; Electron ; Resolution (logic) ; Cluster (spacecraft) ; Ultrashort pulse ; Femtosecond ; Physics ; Nanosecond ; Event (particle physics) ; Computer science ; Optics ; Artificial intelligence ; Laser ; Nuclear physics Electron and X-Ray Spectroscopy Techniques ; Semiconductor materials and devices ; Advanced Electron Microscopy Techniques and Applications
Authors: Lamisa Hoque | Md. Suruz Mian | Kunio Okimura | Toshihiro Nakanishi
Source: e-Journal of Surface Science and Nanotechnology (article, 2023-05-12)
Field: Materials Science — Polymers and Plastics

Study on Relation Between Voltage-induced Switching Behavior and Self-sustained Electrical Oscillations in Vanadium Dioxide Thin Films A VO2 film with a thickness of 400 nm was deposited on indium-tin-oxide/glass substrate by the inductively coupled plasma-assisted radio frequency magnetron sputtering method. A temperature-dependent Raman spectrum exhibits mixed VO2 M2 and triclinic (T) phases at room temperature. A resistance change of more than one order of magnitude is achieved in out-of-plane direction in the prepared sample. The current-voltage (I-V) characteristics of the prepared sample are investigated by varying the contact probe force on the VO2 side from 1 to 30 gf. At low probe forces, a multi-step like I-V characteristic is obtained. On the other hand, when the probe force is increased, the I-V characteristic similar to the usually reported I-V in VO2 is obtained. Moreover, it was found that the hysteresis width of the I-V characteristics became larger with increasing the probe force. In oscillation measurements, the self-sustained electrical oscillation was obtained until 20 gf. At 20 gf, the oscillation region became smaller than 1 and 5 gf. However, the oscillation was not found at 30 gf. This is responsible for the large hysteresis width in the I-V characteristics. The results suggested that there is a strong correlation between the hysteresis behavior of the I-V characteristics and the oscillation characteristics. We believe that the findings of the present study will contribute to the further acceleration of the application of the VO2 films in various fields. Oscillation (cell signaling) ; Hysteresis ; Materials science ; Thin film ; Indium tin oxide ; Substrate (aquarium) ; Analytical Chemistry (journal) ; Raman spectroscopy ; Sputter deposition ; Condensed matter physics ; Nuclear magnetic resonance ; Sputtering ; Chemistry ; Nanotechnology ; Optics ; Physics Transition Metal Oxide Nanomaterials ; Advanced Memory and Neural Computing ; Magneto-Optical Properties and Applications
Authors: Sung-Wook Kim | KIICE
Source: Journal of information and communication convergence engineering (article, 2023-09-27)
Field: Materials Science — Materials Chemistry

Identification of Partial Discharge Defects based on Back-Propagation Algorithm in Eco-friendly Insulation Gas This study presents a method for identifying partial discharge defects in an eco-friendly gas insulated system using a backpropagation algorithm.Four partial discharge (PD) electrode systems, namely, a free-moving particle, protrusion on the conductor, protrusion on the enclosure, and voids, were designed to simulate PD defects that can occur during the operation of eco-friendly gas-insulated switchgear.The PD signals were measured using an ultrahigh-frequency sensor as a nonconventional method based on IEC 62478.To identify the types of PD defects, the PD parameters of single PD pulses in the time and frequency domains and the phase-resolved partial discharge patterns were extracted, and a back-propagation algorithm in the artificial neural network was designed using a virtual instrument based on LabVIEW.The backpropagation algorithm proposed in this paper has an accuracy rate of over 90% for identifying the types of PD defects, and the result is expected to be used as a reference database for asset management and maintenance work for eco-friendly gas-insulated power equipment. Partial discharge ; Identification (biology) ; Computer science ; Algorithm ; Electric discharge in gases ; Electrical engineering ; Materials science ; Engineering ; Voltage High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Aerosol Filtration and Electrostatic Precipitation
Authors: Xingfa Gao | Chunying Chen | Yuliang Zhao
Source: Chinese Science Bulletin (Chinese Version) (article, 2023-10-17)
Field: Chemistry — Electrochemistry

Non-radical surface chemistry mechanism of nanotoxicology Mechanism (biology) ; Chemistry ; Nanotoxicology ; Nanotechnology ; Materials science ; Epistemology ; Organic chemistry ; Philosophy Electrochemical Analysis and Applications ; Advanced Nanomaterials in Catalysis ; Nanoparticles: synthesis and applications
Authors: Bin Zhu | Hongrong Liu
Source: Preprints.org (preprint, 2023-06-14)
Field: Materials Science — Surfaces, Coatings and Films

A Method to Fast Ab Initio Cryo-Electron Microscopy Initial Volume Reconstruction Single particle analysis with cryogenic electron microscopy (cryo-EM) can determine high resolution structures of macromolecular assemblies. To reconstruct final three-dimension(3D) density map, a reliable initial model is essential and ab-initio reconstruction usually can avoid model bias. The grand challenge for ab-initio reconstruction is to alignment two-dimension(2D) low signal-to-noise ratio(SNR) of particle images with random and unknown parameters. Here we formulate a fast ab initio reconstruction method(named AlignFM) based on Fourier Mellin transform and particle-swarm intelligence optimization(PSO) algorithm. It enables simultaneous 2D alignment and 3D refinement, which can fast generate a reliable 3D map. After experiments on several real datasets. AlignFM shows high performance on fast ab initio reconstruction with a small amount of data. Ab initio ; Dimension (graph theory) ; Particle swarm optimization ; Algorithm ; Computer science ; Physics ; Artificial intelligence ; Mathematics ; Quantum mechanics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Chunyan Ma | Jiyong Shi | Xiang Wu | Mingqiang Guo | Cunjun Li
Source: Applied Ecology and Environmental Research (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

HYPERSPECTRAL ESTIMATION OF WHEAT CHLOROPHYLL CONTENT BASED ON PRINCIPAL COMPONENT ANALYSIS Chlorophyll content is an important index to measure the nutritional status of wheat. Rapid and accurate estimation of chlorophyll content is crucial to monitor the photosynthetic capacity and growth status of wheat and optimize its quality. To solve the problem of low precision in the hyperspectral estimation of crop chlorophyll content, this paper selects vegetation indices, spectral characteristic parameters, fractional differential spectrum, and wavelet energy coefficient as index parameters. Meanwhile, principal component analysis (PCA) is exploited to reduce and fuse these index parameters to eliminate the multicollinearity among the index parameters. Then, based on multiple linear regression and support vector machine algorithms, the estimation model of wheat chlorophyll content in different growth stages is constructed. The results show that the PCA reduces the dimension of hyperspectral data while retaining the original information, which improves the operation efficiency of the model, and ensures the effect of chlorophyll content estimation. The experimental results indicate that the multiple linear regression method achieves a better estimation effect of chlorophyll content at the booting stage, and the R 2 , RMSE, and nRMSE of the estimation model are 0.79, 2.21, and 5.50% respectively. This study provides a new technical method for estimating crop chlorophyll content using hyperspectral remote sensing data and comprehensive index parameters. Hyperspectral imaging ; Principal component analysis ; Estimation ; Content (measure theory) ; Component (thermodynamics) ; Environmental science ; Mathematics ; Remote sensing ; Computer science ; Artificial intelligence ; Statistics ; Geology ; Engineering Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Water Quality Monitoring and Analysis
Authors: Albena Ivanova-Vasileva | Zlatin Zlatev | Tsvetelina Georgieva | Plamen Daskalov
Source: MATEC Web of Conferences (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Determination of the parameter color of fresh engine oils by color indices and predictive models Color prediction tools for motor oils, which can be used to assess their quality are presented in the paper. Three measuring devices working on optical principle for color prediction was used and compared. Color models and color index are defined by RGB, Lab and LCh color components. It was found that the combined use of seven color indices leads to an increase in accuracy for predicting the value characteristics of motor oils.. The obtained results demonstrate that the algorithm used for the analysis of color characteristics of motor lubricating oils allowed the creation of adequate regression models. The proposed research tools can be used in practice, which enables a quick assessment of the quality of motor oils based on the parameter color. RGB color model ; Color index ; Color model ; Computer science ; Artificial intelligence ; Color space ; Color analysis ; Color measurement ; Computer vision ; Mathematics ; Pattern recognition (psychology) ; Physics ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Advanced Measurement and Detection Methods ; Water Quality Monitoring and Analysis
Authors: György Marosi | Katalin Bocz
Source: eXPRESS Polymer Letters (article, 2023-12-06)
Field: Materials Science — Polymers and Plastics

Fibers and safety in fire retarded polymer systems: Are we just at the beginning of the road? editorial Materials science ; Polymer ; Polymer science ; Fire safety ; Forensic engineering ; Composite material ; Business ; Engineering ; Risk analysis (engineering) Flame retardant materials and properties ; Fire dynamics and safety research ; Engineering and Material Science Research
Authors: Lance W.Q. Xu | Sina Jazani | Zeliha Kilic | Steve Pressé
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-09-06)
Field: Chemistry — Organic Chemistry

Single-Molecule Reaction-Diffusion We propose to capture reaction-diffusion on a molecule-by-molecule basis from the fastest acquirable timescale, namely individual photon arrivals. We illustrate our method on intrinsically disordered human proteins, the linker histone H1.0 as well as its chaperone prothymosin <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mstyle><mml:mi>α</mml:mi></mml:mstyle> </mml:math> , as these diffuse through an illuminated confocal spot and interact forming larger ternary complexes on millisecond timescales. Most importantly, single-molecule reaction-diffusion, smRD, reveals single molecule properties without trapping or otherwise confining molecules to surfaces. We achieve smRD within a Bayesian paradigm and term our method Bayes-smRD. Bayes-smRD is further free of the average, bulk, results inherent to the analysis of long photon arrival traces by fluorescence correlation spectroscopy. In learning from thousands of photon arrivals continuous spatial positions and discrete conformational and photophysical state changes, Bayes-smRD estimates kinetic parameters on a molecule-by-molecule basis with two to three orders of magnitude less data than tools such as fluorescence correlation spectroscopy thereby also dramatically reducing sample photodamage. Diffusion ; Molecule ; Chemistry ; Physics ; Organic chemistry ; Thermodynamics Click Chemistry and Applications ; Monoclonal and Polyclonal Antibodies Research ; Biotin and Related Studies
Authors: Alessandro Puleio | Luca Martellucci | Riccardo Rossi | Novella Rutigliano | Ivan Wyss | P. Gaudio
Source: Journal of Instrumentation (article, 2023-05-01)
Field: Chemistry — Analytical Chemistry

An alternative SNR-based weighted-LSM algorithm to classify and measure the concentration of Biological Agents from Laser-Induced Fluorescence Abstract Optical spectroscopic techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), have already been used to study and detect Biological Agents (BAs). Unfortunately, BAs usually share similar-shaped emitted spectra and low-signal intensities, making their detection and classification difficult to assess. Least-Square Minimisation (LSM) based algorithms are usually deployed to measure the concentration of agents from spectra. Recently, it has been shown how the use of ad hoc weights can help in improving the performance of the concentration evaluation. More specifically, it has been observed that the “weight matrix” should be modelled as a function of the boundary conditions of the problem. This work proposes a new weight matrix that is based on the Signal-to-Noise Ratio (SNR) of the measurements. The idea is based on the fact that more noisy data are less reliable and therefore weight should be lowered. The paper, after a brief introduction and review of the LSM applied to spectra, will show the new methodology. A systematic analysis of the new algorithm is done and the comparison with the other LSM algorithms is presented. The results clearly show that there is a range of parameters for which the new algorithm performs better. Measure (data warehouse) ; Computer science ; Algorithm ; Laser ; Matrix (chemical analysis) ; Range (aeronautics) ; SIGNAL (programming language) ; Biological system ; Materials science ; Physics ; Optics ; Data mining Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Statistical Process Monitoring