jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xue Cai | Weigang Ge | Xiao Yi | Rui Sun | Jiang Zhu | Cong Lu | Ping Sun | Tiansheng Zhu | Guan Ruan | Chunhui Yuan | Shuang Liang | Mengge Lyv | Shiang Huang | Yi Zhu | Tiannan Guo
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-09-30)
Field: Chemistry — Spectroscopy

PulseDIA: in-depth data independent acquisition mass spectrometry using enhanced gas phase fractionation ABSTRACT An inherent bottleneck of data independent acquisition (DIA) analysis by Orbitrap-based mass spectrometers is the relatively large window width due to the relatively slow scanning rate compared to TOF. Here we present a novel gas phase separation and MS acquisition method called PulseDIA-MS, which improves the specificity and sensitivity of Orbitrap-based DIA analysis. This is achieved by dividing the ordinary DIA-MS analysis covering the entire mass range into multiple injections for DIA-MS analyses with complementary windows. Using standard HeLa digests, the PulseDIA method identified 69,530 peptide precursors from 9,337 protein groups with ten MS injections of 30 min LC gradient. The PulseDIA scheme containing two complementary windows led to the highest gain of peptide and protein identifications per time unit compared to the conventional 30 min DIA method. We further applied the method to profile the proteome of 18 cholangiocarcinoma (CCA) tissue samples (benign and malignant) from nine patients. PulseDIA identified 7,796 protein groups in these CCA samples, with 14% increase of protein identifications, compared to the conventional DIA method. The missing value for protein matrix dropped by 7% with PulseDIA acquisition. 681 proteins were significantly dysregulated in tumorous CCA samples. Together, we presented and benchmarked an alternative DIA method with higher sensitivity and lower missing rate. Orbitrap ; Mass spectrometry ; Chromatography ; Proteome ; Chemistry ; Peptide ; Analytical Chemistry (journal) ; Fractionation ; Biochemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; RNA and protein synthesis mechanisms
Authors: Wenbin Ye | Guoli Ji | Leiming Yuan | Limin Li | Xiaojing Chen | Fatemeh Karimidehcheshmeh | Xi Chen | Guangzao Huang
Source: Applied Sciences (article, 2019-05-18)
Field: Chemistry — Analytical Chemistry

A Sparse Classification Based on a Linear Regression Method for Spectral Recognition This study introduces a spectral-recognition method based on sparse representation. The proposed method, the linear regression sparse classification (LRSC) algorithm, uses different classes of training samples to linearly represent the prediction samples and to further classify them according to residuals in a linear regression model. Two kinds of spectral data with completely different physical properties were used in this study. These included infrared spectral data and laser-induced breakdown spectral (LIBS) data for Tegillarca granosa samples polluted by heavy metals. LRSC algorithm was employed to recognize the two classes of data, and the results were compared with common spectral-recognition algorithms, such as partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), artificial neural network (ANN), random forest (RF), and support vector machine (SVM), in terms of recognition rate and parameter stability. The results show that LRSC algorithm is not only simple and convenient, but it also has a high recognition rate. Pattern recognition (psychology) ; Linear discriminant analysis ; Artificial intelligence ; Support vector machine ; Sparse approximation ; Mathematics ; Computer science Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Mineral Processing and Grinding
Authors: CF So
Source: Biomedical Journal of Scientific & Technical Research (article, 2019-09-17)
Field: Chemistry — Analytical Chemistry

Deep Learning Analysis for Blood Glucose Monitoring Using Near Infrared Spectroscopy Diabetes Mellitus (DM) is an intractable condition in which blood glucose levels cannot be regulated normally by the body alone [1] it has many complications, including heart disease and stroke, kidney failure, blindness or vision problems, diabetic neuropathy and diabetic foot. Treatment methods include dietary regulation to control blood glucose levels, oral medication, and insulin injection, and all of these treatments should rely on blood glucose measurement. Diabetic patients are encouraged to check their blood glucose levels several times per day Currently, the most common means of checking is by using a self-monitoring blood glucose meter In this way, diabetic patients can obtain a clear picture of their blood glucose levels for therapy optimization and for insulin dosage adjustment for those who need daily China ; Medical education ; Psychology ; Medicine ; Gerontology ; Sociology ; Family medicine ; Political science Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Metabolomics and Mass Spectrometry Studies
Authors: Simon Goisser | Julius Krause | Michael Fernandes | Heike Mempel
Source: Repository KITopen (Karlsruhe Institute of Technology) (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Determination of tomato quality attributes using portable NIR-sensors As part of a research project a multidisciplinary approach of different research institutes is followed to investigate the possibility of using a commercially available miniaturized NIR-sensor for the determination of tomato fruit quality parameters in postharvest. Correlation of spectra and tomato reference values of firmness, dry matter and total soluble solids showed good prediction accuracy. Additionally the decline of firmness over storage time with respect to storage temperature of tomatoes could be modelled. Therefore, the decline of firmness as an indicator for shelf-life can be predicted using this portable NIR-Sensor. Postharvest ; Shelf life ; Environmental science ; Food science ; Mathematics ; Chemistry ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Müge Dursun | Yavuz Şenol | BULGUN ENDER YAZGAN | Taner Akkan
Source: Industria Textila (article, 2019-03-01)
Field: Materials Science — Polymers and Plastics

Neural network based thermal protective performance predictionof three-layered fabrics for firefighter clothing The firefighter protective clothing is comprised of three main layers; an outer shell, a moisture barrier and a thermal liner. This three-layered fabric structure provides protection against the fire and extremely hot environments. Various parameters such as fabric construction, weight, warp/weft count, warp/weft density, thickness, water vapour resistance of the fabric layers have effect on the protective performance as heat transfer through the firefighter clothing. In this study, it is aimed to examine the predictability of the heat transfer index of three-layered fabrics, as function of the fabric parameters using artificial neural networks. Therefore, 64 different three layered-fabric assembly combinations of the firefighter clothing were obtained and the convective heat transfer (HTI) and radiant heat transfer (RHTI) through the fabric combinations were measured in a laboratory. Six multilayer perceptron neural networks (MLPNN) each with a single hidden layer and the same 12 input data were constructed to predict the convective heat transfer performance and the radiant heat transfer performance of three-layered fabrics separately. The networks 1 to 4 were trained to predict HTI12, HTI24, RHTI12, and RHTI24, respectively, while networks 5 and 6 had two outputs, HTI12 and HTI24, and RHTI12 and RHTI24, respectively. Each system indicates a good correlation between the predicted values and the experimental values. The results demonstrate that the proposed MLPNNs are able to predict the convective heat transfer and the radiant heat transfer effectively. However, the neural network with two outputs has slightly better prediction performance Heat transfer ; Artificial neural network ; Convective heat transfer ; Materials science ; Convection ; Thermal ; Meteorology ; Computer science ; Artificial intelligence ; Mechanics Textile materials and evaluations ; Thermoregulation and physiological responses ; Heat Transfer Mechanisms
Authors: Fatma Göktepe | Gülçin CANİPEK | M. İ. Soysal
Source: TEKSTİL VE KONFEKSİYON (article, 2019-03-07)
Field: Materials Science — Polymers and Plastics

THE COMPARISON OF PHYSICAL CHARACTERISTICS OF ANATOLIAN NATIVE GOAT DOWN FIBERS WITH CASHMERE Very fine and soft down-hair fibers of native goats can have a potential as a valuable raw-material source for high quality products. Therefore, down-hair fibers were collected from native goats raised in different regions of Turkey, then their physical properties were analyzed and results were compared with cashmere fibers. Along with mean fiber diameter and its variation, single fiber length and its variation, which are the most important parameters regarding spinnability of a textile fiber, this work reports for the first time fiber scale characteristics of Anatolian native goat down-hair fibers. In this respect, scale pattern, mean scale frequency, cuticle scale height, curvature, crimp frequency were analyzed as well as fiber tenacity and breaking elongation properties. The economical potential of these down-hair fibers in Turkey were also investigated. The results show that these native goat down-hair fibers, that have been wasted mostly, have very similar properties to cashmere fibers with adequate properties for spinnability, hence they have potential for high-quality textile products as a substitute for cashmere fiber. Crimp ; Fiber ; Breaking strength ; Materials science ; Tenacity (mineralogy) ; Composite material ; Cuticle (hair) ; Elongation ; Textile ; Ultimate tensile strength ; Anatomy ; Biology Textile materials and evaluations ; Mechanical Engineering and Vibrations Research ; Mechanical Behavior of Composites
Authors: Chun Liu | Changming Zhao | Haiyang Zhang | Zilong Zhang | Shuyuan Gao | Yunshi Wang
Source: IEEE photonics journal (article, 2019-08-01)
Field: Materials Science — Surfaces, Coatings and Films

Analysis of Mini-Camera's Cat-Eye Retro-Reflection for Characterization of Diffraction Rings and Arrayed Spots Mini-cameras are one of several emerging types of cat-eye devices using small lenses with insufficient retro-reflection for traditional detection systems to identify. Based on a structural analysis of these devices, this paper provides an accurate theoretical description of the received beam profile. The simulated and experimental results have good similarity in terms of profile shapes and trends with different incident angles and defocus distances. An analysis of the detection conditions and the reflection image features described in this article can thus be applied to hidden camera detection. Mini-cameras can be detected according to these features of the received beam profiles. Reflection (computer programming) ; Optics ; Computer science ; Computer vision ; Artificial intelligence ; Diffraction ; Beam (structure) ; Characterization (materials science) ; Similarity (geometry) ; Physics ; Image (mathematics) Optical Coatings and Gratings ; Ocular Surface and Contact Lens ; Photonic Crystals and Applications
Authors: Vasile Plămădeală
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2019-03-15)
Field: Materials Science — Materials Chemistry

MODERN ROAD SAFETY ELEMENTS OF THE PIETONS More than 270000 pedestrians die annually on roads across the world, accounting for about 22% of the total number of people killed in road accidents. In addition, millions of pedestrians are traumatized, some of them become disabled for life. The pedestrian is the most vulnerable road traffic victim. Compared to drivers, they are not physically protected, and road accidents with their involvement often become a tragedy – usually the pedestrian gets serious injuries, including incompatible with life. The article contains a brief description of the pedestrian-driver relationship, the statistics of road accidents with the involvement of pedestrians in the Republic of Moldova, the modern practices and technologies applied in some countries regarding the efficient organization of the pedestrian safety. Transport engineering ; Pedestrian ; Computer science ; Geography ; Engineering Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Aerospace, Electronics, Mathematical Modeling
Authors: Dorte B. Bekker‐Jensen | Oliver M. Bernhardt | Alexander Hogrebe | Ana Martínez‐Val | Lynn Verbeke | Tejas Gandhi | Christian D. Kelstrup | Lukas Reiter | Jesper V. Olsen
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-06-03)
Field: Chemistry — Spectroscopy

Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition (DIA) without the need for spectral libraries ABSTRACT Quantitative phosphoproteomics has in recent years revolutionized understanding of cell signaling, but it remains a challenge to scale the technology for high-throughput analyses. Here we present a rapid and reproducible phosphoproteomics approach to systematically analyze hundreds of samples by fast liquid chromatography tandem mass spectrometry using data independent acquisition (DIA). To overcome the inherent issue of positional phosphopeptide isomers in DIA-based phosphoproteomics, we developed and employed an accurate site localization scoring algorithm, which is incorporated into the Spectronaut software tool. Using a library of synthetic phosphopeptides spiked-in to a yeast phosphoproteome in different ratios we show that it is on par with the top site localization score for data-dependent acquisition (DDA) based phosphoproteomics. Single-shot DIA-based phosphoproteomics achieved an order of magnitude broader dynamic range, higher reproducibility of identification and improved sensitivity and accuracy of quantification compared to state-of-the-art DDA-based phosphoproteomics. Importantly, direct DIA without the need of spectral libraries performed almost on par with analyses using specific project-specific libraries. Moreover, we implemented and benchmarked an algorithm for globally determining phosphorylation site stoichiometry in DIA. Finally, we demonstrate the scalability of the DIA approach by systematically analyzing the effects of thirty different kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that a large proportion of EGF-dependent phospho-regulation is mediated by a specific set of protein kinases. Phosphoproteomics ; Computer science ; Computational biology ; Scalability ; Bioinformatics ; Phosphorylation ; Chemistry ; Biology ; Protein phosphorylation ; Protein kinase A ; Biochemistry ; Database Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Victoria Lafuente | Luis Javier Herrera | Jesús Val Falcón | Razvan Ghinea | A.I. Negueruela
Source: Spanish Journal of Agricultural Research (article, 2019-12-18)
Field: Chemistry — Analytical Chemistry

Determination of soluble solids content in Prunus avium by Vis/NIR equipment using linear and non-linear regression methods Aim of study: Developing models to determine soluble solids content (SSC) in cherry trees by means of Vis/NIR spectroscopy.Area of study: The Spanish Autonomous Community of Aragón (Spain).Material and methods: Vis/NIR spectroscopy was applied to Prunus avium fruit ‘Chelan’ (n=360) to predict total SSC using a range 400-2420 nm. Linear (PLS) and nonlinear (LSSVM) regression methods were applied to establish prediction models.Main results: The two regression methods applied obtained similar results (Rcv2=0.97 and Rcv2=0.98 respectively). The range 700-1060 nm attained better results to predict SSC in different seasons. Forty variables selected according to the variable selection method achieved Rcv2 value, 0.97 similar than full range.Research highlights: The development of this methodology is of great interest to the fruit sector in the area, facilitating the harvest for future seasons. Further work is needed on the development of the NIRS methodology and on new calibration equations for other varieties of cherry and other species. Prunus ; Linear regression ; Calibration ; Mathematics ; Bayesian multivariate linear regression ; Linear model ; Regression analysis ; Range (aeronautics) ; Statistics ; Chemometrics ; Regression ; Horticulture ; Chemistry ; Biology ; Chromatography ; Materials science Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Pesticide Residue Analysis and Safety
Authors: H.E. Weekes | David Dye | John E. Proctor | D. F. Smith | Cristina L. Simionescu | Timothy J. Prior | M.R. Wenman
Source: Journal of Nuclear Materials (article, 2019-07-11)
Field: Materials Science — Materials Chemistry

The effect of pressure on hydrogen solubility in Zircaloy-4 Hydrogen ; Diamond anvil cell ; Solubility ; Hydride ; Dissolution ; Thermodynamics ; Chemistry ; Zirconium alloy ; Materials science ; Analytical Chemistry (journal) ; Crystallography ; Metallurgy ; High pressure ; Physical chemistry ; Zirconium ; Organic chemistry Nuclear Materials and Properties ; High-pressure geophysics and materials ; Fusion materials and technologies
Authors: Eneh I.I. | Onugwu E.O. | Eneh P.C. | Patrick Uche Okafor
Source: INTERNATIONAL JOURNAL OF RESEARCH IN ENGINEERING & SCIENCE (article, 2019-01-01)
Field: Materials Science — Polymers and Plastics

IMPROVING THE CONTROL OF PRETERM INFANT MASS SKIN TEMPERATURE USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM This paper presents a system for controlling an infant skin temperature using ArtificialNeuro-Fuzzy Inference System (ANFIS). Mathematical and Simulink models of the infant and the incubator system were developed. The ANFIS model integrates both the Fuzzy Logic Control (FLC) rules and the Artificial Neural Network (ANN) to produce optimum control for the variation of the skin temperature of the preterm infant inside the incubator. Simulation was carried out using the ANFIS model, open loop incubator and FLC in two instances. A0.9kg and 2.5kg infant masses and postnatal ages of 5 days were used in the first and second instances. Result showedthat in the first instance, the ANFIS model made a 2.2% and 0.82% improvement over the open loop incubator and the FLC respectively. While a 6.5% and 2.3% improvementwere also made by the ANFIS model over the open loop incubator and the FLC in the second instance. Adaptive neuro fuzzy inference system ; Inference system ; Neuro-fuzzy ; Inference ; Fuzzy inference ; Computer science ; Fuzzy control system ; Artificial intelligence ; Fuzzy logic Textile materials and evaluations ; Engineering and Agricultural Innovations
Authors: David Shteynberg | Eric W. Deutsch | David Campbell | Michael R. Hoopmann | Ulrike Kusebauch | Dave Lee | Luis Mendoza | Mukul K. Midha | Zhi Sun | Anthony D. Whetton | Robert L. Moritz
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-06-22)
Field: Chemistry — Spectroscopy

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms and demonstrate its performance on ground-truth synthetic peptide reference datasets, one previously published small dataset, one new larger dataset, and also on a previously published phospho-enriched dataset where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210. Pipeline (software) ; Computer science ; Ground truth ; Proteome ; Sequence (biology) ; False discovery rate ; Sequence database ; Database search engine ; Proteomics ; Mass spectrometry ; Data mining ; False positive paradox ; Computational biology ; Algorithm ; Bioinformatics ; Chemistry ; Artificial intelligence ; Search engine ; Biology ; Information retrieval ; Biochemistry ; Chromatography Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Daiki Fuwa | Takuya Sakuragi | Mai MIZUBAYASHI | Masayuki Kobayashi | Tetsuya Katsumi
Source: MATERIALS TRANSACTIONS (article, 2019-04-04)
Field: Materials Science — Materials Chemistry

Prediction of Laminations in Zinc Alloy Die-Casting by Gas-Liquid Two-Phase Flow Simulation In the manufacturing process of zinc alloy die-casting, laminations are a serious problem because they cause blister defects and the deposition of zinc on the mold surface. Thus, it is very important to analytically predict the risk of lamination formation before determining the mold design. In this study, we proposed a criterion for predicting the locations of laminations. The criterion value is estimated from the result of a molten metal flow simulation and can indirectly predict the locations of laminations. As the analytic method in the mold-filling simulation, we adopted a gas-liquid two-phase flow model with a finite element method, and the Cahn-Hilliard equation was adopted to determine the interface between the gas and the liquid. We predicted the locations of laminations for two different types of gating system using the mold-filling simulation. The validity of the proposed criterion for laminations was confirmed by comparison of the results of the simulation and the observation of laminations after practical die-casting. Lamination ; Mold ; Materials science ; Die casting ; Casting ; Die (integrated circuit) ; Alloy ; Flow (mathematics) ; Liquid metal ; Melt flow index ; Zinc ; Finite element method ; Metallurgy ; Mechanics ; Composite material ; Structural engineering ; Engineering ; Layer (electronics) ; Physics Solidification and crystal growth phenomena ; Metallurgical Processes and Thermodynamics ; Aluminum Alloy Microstructure Properties