jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Philip Berg | Evan W. McConnell | Leslie M. Hicks | Sorina C. Popescu | George V. Popescu
Source: BMC Bioinformatics (article, 2019-03-01)
Field: Chemistry — Spectroscopy

Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics Identifying PTMs in large-scale datasets is a problem with distinct characteristics that require new methods for handling missing data imputation and differential proteome analysis. Linear models in combination with multiple-imputation could significantly outperform a t-test-based decision method. Missing data ; Imputation (statistics) ; Computer science ; Normalization (sociology) ; Proteome ; Proteomics ; Data mining ; Database normalization ; Artificial intelligence ; Bioinformatics ; Machine learning ; Pattern recognition (psychology) ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Oliver M. Crook | Lisa M. Breckels | Kathryn S. Lilley | Paul Kirk | Laurent Gatto
Source: F1000Research (preprint, 2019-04-11)
Field: Chemistry — Spectroscopy

A Bioconductor workflow for the Bayesian analysis of spatial proteomics Knowledge of the subcellular location of a protein gives valuable insight into its function. The field of spatial proteomics has become increasingly popular due to improved multiplexing capabilities in high-throughput mass spectrometry, which have made it possible to systematically localise thousands of proteins per experiment. In parallel with these experimental advances, improved methods for analysing spatial proteomics data have also been developed. In this workflow, we demonstrate using `pRoloc` for the Bayesian analysis of spatial proteomics data. We detail the software infrastructure and then provide step-by-step guidance of the analysis, including setting up a pipeline, assessing convergence, and interpreting downstream results. In several places we provide additional details on Bayesian analysis to provide users with a holistic view of Bayesian analysis for spatial proteomics data. Proteomics ; Workflow ; Computer science ; Bioconductor ; Bayesian probability ; Pipeline (software) ; Spatial analysis ; Software ; Data mining ; Data science ; Computational biology ; Artificial intelligence ; Biology ; Geography ; Database ; Remote sensing Advanced Proteomics Techniques and Applications ; Gene expression and cancer classification ; Data Management and Algorithms
Authors: Fikret Yıldız | Ahmet Turan Özdemir | Selman Uluışık
Source: Journal of Food Quality (article, 2019-07-08)
Field: Chemistry — Analytical Chemistry

Evaluation Performance of Ultrasonic Testing on Fruit Quality Determination There are several destructive and nondestructive methods for quality evaluation of agricultural products. Most of the employed traditional techniques are time-consuming and involve considerable degree of manual works. Destructive methods provide reasonable success rate of quality determination of fruits; however, they practically have many concerns about effectiveness, time, and cost. Therefore, developing portable, fast, and cost-effective techniques without harming fruits are desired for fruit quality evaluation. This work aims to develop a complete nondestructive quality evaluation system with (a) ultrasonic testing and (b) volume estimation by automatic machine vision techniques. The ultrasonic system consisted of a programmable bipolar remote pulser unit, a couple of piezoelectric probes for ultrasonic signal acquisitions as a transmitter and a receiver, an oscilloscope, and a computer. Visual appearance (size/volume) was determined using a machine vision system based on image processing techniques. Five different images of a fruit from different angles were captured by high-resolution digital cameras. Volume of the fruit was computed after horizontal and vertical distance of the fruit’s images captured. The calculated volume values by the computer vision system are validated with the theoretical values. Although nondestructive ultrasonic estimation and volume estimation by image processing methods are cheap, fast, and practical, the results obtained in our experiments concluded that these methods are not as reliable as claimed in the literature. Ultrasonic sensor ; Computer science ; Nondestructive testing ; Volume (thermodynamics) ; Computer vision ; Oscilloscope ; Transmitter ; Metering mode ; Image quality ; Quality (philosophy) ; Artificial intelligence ; Ultrasonic testing ; Image processing ; Acoustics ; Engineering ; Image (mathematics) ; Mechanical engineering ; Telecommunications Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Smart Agriculture and AI
Authors: Georgi J. Vadakkekara | Sabu Thomas | C. P. Reghunadhan Nair
Source: International Journal of Biological Macromolecules (article, 2019-02-09)
Field: Materials Science — Biomaterials

Maleic acid modified cellulose for scavenging lead from water Chemisorption ; Chemistry ; Cellulose ; Maleic acid ; Inorganic chemistry ; Freundlich equation ; Sodium ; Organic chemistry ; Aqueous solution ; Adsorption ; Polymer Advanced Cellulose Research Studies ; Adsorption and biosorption for pollutant removal
Authors: Ludovic Escoubas | Miriam Carlberg | Judikaël Le Rouzo | Florent Pourcin | Jörg Ackermann | Olivier Margeat | Clément Reynaud | David Duché | Jean‐Jacques Simon | Rose-Marie Sauvage | Gérard Berginc
Source: Progress in Quantum Electronics (article, 2019-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Design and realization of light absorbers using plasmonic nanoparticles Nanoparticle ; Materials science ; Absorptance ; Plasmon ; Plasmonic nanoparticles ; Photodetector ; Nanotechnology ; Optoelectronics ; Thin film ; Nanophotonics ; Ray ; Layer (electronics) ; Optics ; Reflectivity ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Plasmonic and Surface Plasmon Research ; Quantum Dots Synthesis And Properties
Authors: Constantin Ahlmann-Eltze | Simon Anders
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-06-06)
Field: Chemistry — Spectroscopy

proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry Abstract Protein mass spectrometry with label-free quantification (LFQ) is widely used for quantitative proteomics studies. Nevertheless, well-principled statistical inference procedures are still lacking, and most practitioners adopt methods from transcriptomics. These, however, cannot properly treat the principal complication of label-free proteomics, namely many non-randomly missing values. We present proDA , a method to perform statistical tests for differential abundance of proteins. It models missing values in an intensity-dependent probabilistic manner. proDA is based on linear models and thus suitable for complex experimental designs, and boosts statistical power for small sample sizes by using variance moderation. We show that the currently widely used methods based on ad hoc imputation schemes can report excessive false positives, and that proDA not only overcomes this serious issue but also offers high sensitivity. Thus, proDA fills a crucial gap in the toolbox of quantitative proteomics. Quantitative proteomics ; Missing data ; Computer science ; Probabilistic logic ; Imputation (statistics) ; Proteomics ; Label-free quantification ; Statistical power ; Inference ; Statistical model ; Leverage (statistics) ; Data mining ; Computational biology ; Statistics ; Artificial intelligence ; Machine learning ; Chemistry ; Mathematics ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Jing Yan | Louka van Stuijvenberg | Saskia M. van Ruth
Source: European Journal of Lipid Science and Technology (article, 2019-09-03)
Field: Chemistry — Analytical Chemistry

Handheld Near‐Infrared Spectroscopy for Distinction of Extra Virgin Olive Oil from Other Olive Oil Grades Substantiated by Compositional Data Abstract Miniaturization of analytical technology has paved the way for in‐situ screening of foods. In the current study, the spectral features of olive oils are examined by handheld near‐infrared spectroscopy to explore the technology's capabilities to distinguish extra virgin olive oil (EVOO) from lower grade oils. Eighty EVOO, forty refined olive oil (ROO), and ten pomace olive oil (POO) samples are analysed for their spectral and compositional features. The latter included analysis of the fatty acids (FAs), the chlorophylls and carotenoids, chromatic coordinates and moisture contents. The 1350–1570 nm wavelength range appeared most suitable for distinction of the oils. One‐class classification models with three different classifiers are subsequently estimated using this range, and their quantitative performance is assessed from probabilistic data. Soft independent modeling of class analogies models appears to predict the identity of the oils with a high success rate. Compared to the other oils, POO comprises a significantly higher and lower proportion of polyunsaturated and monounsaturated FAs, respectively. Higher contents of chlorophylls, carotenoids, and moisture are noted for EVOO. The relevant spectral information for distinction of the oils correlates strongly with the degree of unsaturation of the oils as well as their levels of chlorophylls, carotenoids, and moisture. Practical Applications : The findings of this study demonstrate that the handheld NIRS technique is promising for future rapid screening of olive oil grades. The statistical methods used and the robust validation procedure will help potential users to select the optimal strategy for multivariate data analysis. In addition, the exploration of correlations with compositional characteristics provides insight into the handheld NIRS working mechanism in regard to EVOO authentication. Olive oil ; Food science ; Moisture ; Degree of unsaturation ; Vegetable oil ; Carotenoid ; Chemistry ; Chemometrics ; Environmental science ; Mathematics ; Chromatography Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies
Authors: Xiaolong Li | Changjun Xie | Shuhai Quan | Ying Shi | Zebo Tang
Source: IEEE Access (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Optimization of Thermoelectric Modules’ Number and Distribution Pattern in an Automotive Exhaust Thermoelectric Generator Thermoelectric generators are efficient devices to recover energy from the automotive exhaust gas. In this paper, conversion efficiency of automotive thermoelectric generator (ATEG) and the maximum electrical power generated by the ATEG, defining as the power output of the ATEG excluding the energy loss caused to the engine improved by optimizing the number of thermoelectric modules (TEMs) and its distribution pattern in an ATEG. An advanced numerical model of ATEG considering the effect of the heat transfer among the adjacent TEMs' rows is developed with Simulation-X software. In order to acquire the ATEG's optimal electrical performance, a 3-step optimization is applied. First, 17 independent factors (the number of TEMs in each row from 1 to 18) are assessed and the significant parameters are screened using Plackett-Burman design. Second, an experiment designed with a central composite design is performed to analyze the sensitivity of six selected factors and a surrogate model is built through response surface method. Then, conflicts in two objectives are settled with a multi-objective genetic algorithm. According to the optimization results of a given ATEG, the maximum electrical power generated by the ATEG is 139.47 W and the conversion efficiency is 2.51% under steady engine condition. Finally, the performances of the optimized design under different engine conditions are discussed. The results show that the maximum power generated by the ATEG and efficiency respectively increase by 49.8% and 106.5% after optimization when the exhaust inlet temperature is 805 K and the mass flow rate is 0.5 kg/s. Thermoelectric generator ; Automotive engineering ; Thermoelectric effect ; Sensitivity (control systems) ; Exhaust gas ; Power (physics) ; Materials science ; Computer science ; Maximum power principle ; Environmental science ; Mechanical engineering ; Nuclear engineering ; Electronic engineering ; Engineering ; Physics ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Environmental Education and Sustainability ; Thermal Radiation and Cooling Technologies
Authors: Kailei Lu | Yingxin Yi | Li Xu | Xianhao Sun | Lu Liu | Hanyang Li
Source: Nanomaterials (article, 2019-12-20)
Field: Materials Science — Materials Chemistry

Temperature-Independent Lifetime and Thermometer Operated in a Biological Window of Upconverting NaErF4 Nanocrystals Lifetime of lanthanide luminescence basically decreases with increasing the ambient temperature. In this work, we developed NaErF4 core–shell nanocrystals with compensation of the lifetime variation with temperature. Upconversion lifetime of various emissions remains substantially unchanged as increasing the ambient temperature, upon 980/1530 nm excitation. The concentrated dopants, leading to extremely strong interactions between them, are responsible for the unique temperature-independent lifetime. Besides, upconversion mechanisms of NaErF4 core-only and core–shell nanocrystals under 980 and 1530 nm excitations were comparatively investigated. On the basis of luminescent ratiometric method, we demonstrated the optical thermometry using non-thermally coupled 4F9/2 and 4I9/2 emissions upon 1530 nm excitation, favoring the temperature monitoring in vivo due to both excitation and emissions fall in the biological window. The formed NaErF4 core–shell nanocrystals with ultra-small particle size, highly efficient upconversion luminescence, unique temperature-independent lifetimes, and thermometry operated in a biological window, are versatile in applications such as anti-counterfeiting, time-domain manipulation, and biological thermal probes. Photon upconversion ; Materials science ; Luminescence ; Nanocrystal ; Thermometer ; Excitation ; Dopant ; Optoelectronics ; Core (optical fiber) ; Nanotechnology ; Doping ; Composite material Luminescence Properties of Advanced Materials ; Perovskite Materials and Applications ; Luminescence and Fluorescent Materials
Authors: Hongjun Jin | Hongpeng Li | Zhiyang Zhu | Jianbin Huang | Yunlong Xiao | Yun Yan
Source: Angewandte Chemie International Edition (article, 2019-10-21)
Field: Materials Science — Materials Chemistry

Hydration‐Facilitated Fine‐Tuning of the AIE Amphiphile Color and Application as Erasable Materials with Hot/Cold Dual Writing Modes Hydration water greatly impacts the color of inorganic crystals, but it is still unknown whether hydration water can be utilized to systematically manipulate the emission color of organic luminescent groups. Now, metal ions with different hydration ability allow fine-tuning the emission color of a fluorescent group displaying aggregation induced emission (AIE). Because the hydration water can be removed easily by gentle heating or mechanical grinding and re-gained by solvent fuming, rewritable materials can be fabricated both in the hot-writing and cold-writing modes. This hydration-facilitated strategy will open up a new vista in fine-tuning the emission color of AIE molecules based on one synthesis and in the design of smart luminescent devices. Materials science ; Luminescence ; Fluorescence ; Aggregation-induced emission ; Amphiphile ; Molecule ; Nanotechnology ; Optoelectronics ; Photochemistry ; Chemical engineering ; Optics ; Chemistry ; Copolymer ; Composite material ; Organic chemistry ; Polymer Luminescence and Fluorescent Materials ; Supramolecular Chemistry and Complexes ; Molecular Sensors and Ion Detection
Authors: Jinxing Chen | Ji Feng | Fan Yang | Rashed Aleisa | Qiao Zhang | Yadong Yin
Source: Angewandte Chemie (article, 2019-05-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Space‐Confined Seeded Growth of Cu Nanorods with Strong Surface Plasmon Resonance for Photothermal Actuation Abstract Herein, we show that copper nanostructures, if made anisotropic, can exhibit strong surface plasmon resonance comparable to that of gold and silver counterparts in the near‐infrared spectrum. Further, we demonstrate that a robust confined seeded growth strategy allows the production of high‐quality samples with excellent control over their size, morphology, and plasmon resonance frequency. As an example, copper nanorods (CuNRs) are successfully grown in a limited space of preformed rod‐shaped polymer nanocapsules, thereby avoiding the complex nucleation kinetics involved in the conventional synthesis. The method is unique in that it enables the flexible control and fine‐tuning of the aspect ratio and the plasmonic resonance. We also show the high efficiency and stability of the as‐synthesized CuNRs in photothermal conversion and demonstrate their incorporation into nanocomposite polymer films that can be used as active components for constructing light‐responsive actuators and microrobots. Nanorod ; Surface plasmon resonance ; Materials science ; Photothermal therapy ; Plasmon ; Nanotechnology ; Nucleation ; Polymer ; Nanostructure ; Copper ; Photothermal effect ; Surface plasmon ; Resonance (particle physics) ; Nanoparticle ; Nanocomposite ; Optoelectronics ; Chemistry ; Composite material Gold and Silver Nanoparticles Synthesis and Applications ; Solar-Powered Water Purification Methods ; Nanomaterials and Printing Technologies
Authors: Anju Toor | Joe Forth | Simone Bochner de Araujo | Maria Consiglia Merola | Yufeng Jiang | Xubo Liu | Yu Chai | Honghao Hou | Paul D. Ashby | Gerald G. Fuller | Thomas P. Russell
Source: Langmuir (article, 2019-09-19)
Field: Materials Science — Materials Chemistry

Mechanical Properties of Solidifying Assemblies of Nanoparticle Surfactants at the Oil–Water Interface The effect of polymer surfactant structure and concentration on the self-assembly, mechanical properties, and solidification of nanoparticle surfactants (NPSs) at the oil-water interface was studied. The surface tension of the oil-water interface was found to depend strongly on the choice of the polymer surfactant used to assemble the NPSs, with polymer surfactants bearing multiple polar groups being the most effective at reducing interfacial tension and driving the NPS assembly. By contrast, only small variations in the shear modulus of the system were observed, suggesting that it is determined largely by particle density. In the presence of polymer surfactants bearing multiple functional groups, NPS assemblies on pendant drop surfaces were observed to spontaneously solidify above a critical polymer surfactant concentration. Interfacial solidification accelerated rapidly as polymer surfactant concentration was increased. On long timescales after solidification, pendant drop interfaces were observed to spontaneously wrinkle at sufficiently low surface tensions (approximately 5 mN m<sup>-1</sup>). Interfacial shear rheology of the NPS assemblies was elastic-dominated, with the shear modulus ranging from 0.1 to 1 N m<sup>-1</sup>, comparable to values obtained for nanoparticle monolayers elsewhere. Our work paves the way for the development of designer, multicomponent oil-water interfaces with well-defined mechanical, structural, and functional properties. Nanoparticle ; Chemical engineering ; Materials science ; Chemistry ; Nanotechnology ; Engineering Pickering emulsions and particle stabilization ; Surfactants and Colloidal Systems ; Liquid Crystal Research Advancements
Authors: Barbara Farkaš | Umberto Terranova | Nora H. de Leeuw
Source: Physical Chemistry Chemical Physics (article, 2019-12-12)
Field: Materials Science — Materials Chemistry

Binding modes of carboxylic acids on cobalt nanoparticles Owing to their high saturation magnetisation, cobalt nanoparticles hold significant potential for the hyperthermia treatment of tumours. Covalent binding of carboxylic acids to the nanoparticles can induce biocompatibility, whilst also preventing the formation of surface oxides which reduce the magnetic properties of cobalt. Understanding the origin of the acid-metal interaction is key, yet probably the most experimentally challenging step, for the rational design of such entities. In this density functional theory study, we use static calculations to establish that a 57-atom Co cluster is the smallest model able to reproduce the adsorption behaviour of carboxylic acids, and ab initio metadynamics to obtain the structure and the free energy landscape for its interaction with valeric acid. Our simulations show that a bridging bidentate binding mode has a stronger affinity compared to monodentate binding, with energetically high transition barriers between the two. A chelate interaction mode of two carboxyl oxygen atoms can be formed as an intermediate. These results clarify the organic-inorganic interactions in the cobalt-acid system, providing a basis for the rational design of biocompatible metallic nanoparticles. Cobalt ; Nanoparticle ; Chemistry ; Density functional theory ; Denticity ; Binding energy ; Rational design ; Transition metal ; Covalent bond ; Metal ; Metadynamics ; Computational chemistry ; Carboxylic acid ; Combinatorial chemistry ; Nanotechnology ; Chemical physics ; Materials science ; Inorganic chemistry ; Organic chemistry ; Molecular dynamics ; Catalysis Nanocluster Synthesis and Applications ; Machine Learning in Materials Science ; Magnetism in coordination complexes
Authors: Boyu Zhang | Mingming Zhao | Yanfei Qi | Rui Tian | Boye B. Carter | Hangjin Zou | Chuhan Zhang | Chunyan Wang
Source: Scientific Reports (article, 2019-10-16)
Field: Materials Science — Materials Chemistry

The Intrinsic Enzyme Activities of the Classic Polyoxometalates Abstract The mimicking enzyme activities of eighteen classic POMs with different structures, Keggin (H 3 PW 12 O 40 , H 4 SiW 12 O 40 , H 4 GeW 12 O 40 , K 4 GeW 12 O 40 , H 3 PMo 12 O 40 , H 4 SiMo 12 O 40 and Eu 3 PMo 12 O 40 ), Wells-Dawson (H 6 P 2 Mo 18 O 62 , α-(NH 4 ) 6 P 2 W 18 O 62 and α-K 6 P 2 W 18 O 62 ·14H 2 O), lacunary-Keggin (Na 8 H[α-PW 9 O 34 ], Na 10 [α-SiW 9 O 34 ], Na 10 [α-GeW 9 O 34 ] and K 8 [γ-SiW 10 O 36 ]), the transition-metal substituted-type (α-1,2,3-K 6 H[SiW 9 V 3 O 34 ] and H 5 PMo 10 V 2 O 40 ), sandwich-type (K 10 P 2 W 18 Fe 4 (H 2 O) 2 O 68 ) and an isopolyoxotungstate (Na 10 H 2 W 12 O 42 ) were screened and compared. The mechanisms and reaction conditions of POMs with mimicking enzyme-like activities were also analyzed. The results shown that the structures, the hybrid atoms, the coordination atoms, the substituted metal atoms, pH and substrate are the effect factors for the enzyme mimic activities of POM. Among the eighteen POMs, H 3 PW 12 O 40 , H 4 SiW 12 O 40 , H 4 GeW 12 O 40 , α-(NH 4 ) 6 P 2 W 18 O 62 , α-K 6 P 2 W 18 O 62 ·14H 2 O, Na 8 H[α-PW 9 O 34 ], Na 10 [α-SiW 9 O 34 ], Na 10 [α-GeW 9 O 34 ], K 8 [γ-SiW 10 O 36 ], K 10 P 2 W 18 Fe 4 (H 2 O) 2 O 68 and Na 10 H 2 W 12 O 42 had the peroxidase activities. Eu 3 PMo 12 O 40 , H 3 PMo 12 O 40 , H 4 SiMo 12 O 40 , α-1,2,3-K 6 H [SiW 9 V 3 O 34 ], H 6 P 2 Mo 18 O 62 and H 5 PMo 10 V 2 O 40 showed the oxidase-like activities. K 4 GeW 12 O 40 did not show the peroxidase and oxidase activities. The Na 8 H[α-PW 9 O 34 ], Na 10 [α-SiW 9 O 34 ] and Na 10 [α-GeW 9 O 34 ] showed intrinsic enzyme activities at alkaline conditions, which were different from other type of POMs. The sandwich-type K 10 P 2 W 18 Fe 4 (H 2 O) 2 O 68 displayed the strongest peroxidase activity, which is similar to natural horseradish peroxidase. Metal ; Enzyme ; Chemistry ; Substrate (aquarium) ; Polyoxometalate ; Lacunary function ; Crystallography ; Stereochemistry ; Catalysis ; Biochemistry ; Organic chemistry ; Biology Polyoxometalates: Synthesis and Applications ; Advanced Nanomaterials in Catalysis ; Metal-Organic Frameworks: Synthesis and Applications