jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Domingo Olivares-Postigo | Federico Gorrini | Valeria Bitonto | Johannes Ackermann | Rakshyakar Giri | Anke Krueger | Angelo Bifone
Source:  (preprint, 2021-10-06)
Field: Materials Science — Materials Chemistry

Divergent effects of laser irradiation on ensembles of nitrogen-vacancy centers in bulk and nano-diamonds: implications for biosensing Ensembles of negatively charged nitrogen vacancy centers (NV-) in diamond have been proposed for sensing of magnetic fields and paramagnetic agents, and as a source of spin-order for the hyperpolarization of nuclei in magnetic resonance applications. To this end, strongly fluorescent nanodiamonds represent promising materials, with large surface areas and dense ensembles of NV-. However, surface effects tend to favor the less useful neutral form, the NV0 centers. Here, we study the fluorescence properties and optically detected magnetic resonance (ODMR) of NV- centers as a function of laser power in strongly fluorescent bulk diamond and in nanodiamonds obtained by nanomilling the native material. In bulk diamond, we find that increasing laser power increases ODMR contrast, consistent with a power-dependent increase in spin-polarization. Surprisingly, in nanodiamonds we observe a non-monotonic behavior, with a decrease in ODMR contrast at higher laser power that can be ascribed to more efficient NV-→NV0 photoconversion in nanodiamonds compared to bulk diamond, resulting in depletion of the NV- pool. We also studied this phenomenon in cell cultures following internalization of NDs in macrophages. Our findings show that surface effects in nanodiamonds substantially affect the NV properties and provide indications for the adjustment of experimental parameters. Diamond ; Vacancy defect ; Fluorescence ; Materials science ; Laser ; Electron paramagnetic resonance ; Paramagnetism ; Chemical physics ; Nanotechnology ; Optoelectronics ; Condensed matter physics ; Chemistry ; Nuclear magnetic resonance ; Optics ; Physics Diamond and Carbon-based Materials Research ; Laser-induced spectroscopy and plasma ; Laser-Ablation Synthesis of Nanoparticles
Authors: Febryan Kusuma Wisnu | Sri Rahayoe | Rizza Wijaya | Mareli Telaumbanua | Agus Haryanto
Source: Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) (article, 2021-06-16)
Field: Chemistry — Inorganic Chemistry

MATHEMATICAL MODEL OF PHYSICAL PROPERTIES CHANGE OF COCONUT SAP IN THE VACUUM EVAPORATOR The potential of brown sugar as a substitute for granulated sugar is enormous considering the abundant coconut sap production. However, the quantity of brown sugar production through the traditional method is one of the main obstacles. This study used a vacuum evaporator that emphasizes the hygienic and effective mass production of brown sugar. For this reason, it is necessary to approach changes in the physical properties of sap juice during the cooking process. This knowledge is indispensable in the cooking process, which involves the proper evaporation and crystallization of brown sugar. This research is devoted to determining the viscosity, density, and dissolved solids expressed in Brix and proposes a mathematical model to predict the physical properties during the evaporation process of brown sugar as a function of the initial concentration the solution before proceeding to the crystallization process. Results confirm that the prediction model for Brix is Cθ=(Co–Ce)·exp(0.0067·t)+Ce, the model for viscosity µθ=µo·exp(0.011·t), and ρө=(0.44996·t)+ρ0 for the density prediction model. The resulted mathematical model can accurately predict the rate of change in coconut sap's physical properties, indicated by the high coefficient of determination (R2). Keywords : brix, brown sugar, density, vacuum evaporator, viscosity Sugar ; Brix ; Evaporation ; Viscosity ; Evaporator ; Crystallization ; Vacuum evaporation ; Sugar production ; Process (computing) ; Chemistry ; Thermodynamics ; Mathematics ; Pulp and paper industry ; Food science ; Materials science ; Physics ; Computer science ; Nanotechnology ; Engineering Coconut Research and Applications ; Chemical and Environmental Engineering Research ; Food and Agricultural Sciences
Authors: Yang Deng | Simiao Ren | Kebin Fan | Jordan M. Malof | Willie J. Padilla
Source: Figshare (article, 2021-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Supplementary document for Neural-adjoint method for the inverse design of all-dielectric metasurfaces - 5093654.pdf Supplemental Document Inverse ; Inverse problem ; Dielectric ; Artificial neural network ; Mathematics ; Computer science ; Mathematical analysis ; Artificial intelligence ; Physics ; Geometry ; Optoelectronics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Optimization
Authors: H Drayson
Source: PEARL (University of Plymouth) (article, 2021-04-01)
Field: Chemistry — Physical and Theoretical Chemistry

To the Bitter End: Affect, Experience and Chemical Ecology This article explores taste in its chemical, gustemological and affective senses, asking what\nwe speak of when we talk about “bitter experience.” Drawing lines of connection between\nhuman affect and chemical ecology, it suggests a way of thinking about taste as a chemical\nentanglement of affective qualities and ecological relations. Two observations underpin the\nargument. First, the ambiguous resonance of bitter-tasting compounds in human culture is\ngrounded in their ambiguous medical meaning, the same drug may serve as poison or cure.\nSecond, plants interact with many other life-forms by producing chemical compounds, many\nof which are bitter tasting, that have effects on the metabolisms of the organisms around\nthem. These secondary metabolites have become entangled in human physiology and culture.\nThe use of bitter-tasting plants in food and medicine requires specialised technical knowledge\nfor identification, processing and dosing, a necessity that expresses itself in various yet\ncomparable cultural responses to bitterness. A number of cultural traditions hold strong\nassociations between embitterment, wisdom, healing, and remembrance. In these similar\nresponses to bitterness, the article suggests that there is an ecological and affective resonance\nthat might be located in the idea of bitter experience. Affect (linguistics) ; Ecology ; Chemical ecology ; Psychology ; Geography ; Biology ; Communication History and advancements in chemistry ; Geographies of human-animal interactions
Authors: Megan Yu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-06-25)
Field: Chemistry — Physical and Theoretical Chemistry

Elucidating the genome of <i>Emydura subglobosa</i> through manual annotation and computational biology tools Abstract Rapid advancements in automated genomic technologies have uncovered many unique findings about the turtle genome and its associated features including olfactory gene expansions and duplications of toll-like receptors. However, automated technologies often result in a high frequency of errors through the process of assembly and annotation and highlight the need for manual annotation. In this study, we have manually annotated four genes of the red-bellied short-neck turtle ( Emydura subglobosa ), an understudied outgroup of turtles representing a diverse lineage. We improved upon initial ab initio gene predictions through homology-based evidence and generated refined consensus models. Through functional, localization, and structural analyses of the predicted proteins, we have discovered conserved genes encoding proteins that play a role in C21-steroid hormone biosynthetic processes, Vitamin A uptake, collagen/elastin integrity, tumor suppression, and fatty acid catabolism. Overall, these findings further our knowledge about the genetic features underlying turtle physiology, morphology, and longevity, which could have important implications for the treatment of human diseases and evolutionary studies. Biology ; Computational biology ; Genome ; Gene ; Annotation ; Gene Annotation ; Turtle (robot) ; Comparative genomics ; Evolutionary biology ; Genomics ; Homology (biology) ; Genome project ; Genetics thermodynamics and calorimetric analyses ; Heat shock proteins research ; Coagulation, Bradykinin, Polyphosphates, and Angioedema
Authors: Lawrence Chai | Ping Zhu | Jin Chai | Changxu Pang | Babak Andi | Seán McSweeney | John Shanklin | Qun Liu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-09-11)
Field: Materials Science — Materials Chemistry

AlphaFold Protein Structure Database for Sequence-Independent Molecular Replacement Abstract Crystallographic phasing recovers the phase information that is lost during a diffraction experiment. Molecular replacement is a dominant phasing method for the crystal structures in the protein data bank. In one form it uses a protein sequence to search a structure database for finding suitable templates for phasing. However, such sequence information is not always available such as when proteins are crystallized with unknown binding partner proteins or when the crystal is that of a contaminant. The recent development of AlphaFold has resulted in the availability of predicted protein structures for all proteins from twenty species. In this work, we tested whether AlphaFold-predicted E. coli protein structures were accurate enough for sequence-independent phasing of diffraction data from two crystallization contaminants for which we had not identified the protein. Using each of more than 4000 predicted structures as a search model, robust molecular replacement solutions were obtained which allowed the identification and structure determination of both structures, YncE and YadF. Our results advocate a general utility of AlphaFold-predicted structure database with respect to crystallographic phasing. Phaser ; Molecular replacement ; Protein Data Bank ; Sequence (biology) ; Protein crystallization ; Protein structure ; Crystal structure ; Crystallography ; Protein structure database ; X-ray crystallography ; Database ; Diffraction ; Computational biology ; Crystallization ; Chemistry ; Computer science ; Biology ; Sequence database ; Physics ; Biochemistry ; Gene ; Optics Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Karin Schork | Michael Turewicz | Julian Uszkoreit | Jörg Rahnenführer | Martin Eisenacher
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-07-29)
Field: Chemistry — Spectroscopy

Characterization of peptide-protein relationships in protein ambiguity groups via bipartite graphs Abstract In bottom-up proteomics, proteins are enzymatically digested into peptides before measurement with mass spectrometry. The relationship between proteins and their corresponding peptides can be represented by bipartite graphs. We conduct a comprehensive analysis of bipartite graphs using quantified peptides from measured data sets as well as theoretical peptides from an in silico digestion of the corresponding complete taxonomic protein sequence databases. The aim of this study is to characterize and structure the different types of graphs that occur and to compare them between data sets. We observed a large influence of the accepted minimum peptide length during in silico digestion. When changing from theoretical peptides to measured ones, the graph structures are subject to two opposite effects. On the one hand, the graphs based on measured peptides are on average smaller and less complex compared to graphs using theoretical peptides. On the other hand, the proportion of protein nodes without unique peptides, which are a complicated case for protein inference and quantification, is considerably larger for measured data. Additionally, the proportion of graphs containing at least one protein node without unique peptides rises when going from database to quantitative level. The fraction of shared peptides and proteins without unique peptides as well as the complexity and size of the graphs highly depends on the data set and organism. Large differences between the structures of bipartite peptide-protein graphs have been observed between database and quantitative level as well as between analyzed species. In the analyzed measured data sets, the proportion of protein nodes without unique peptides ranged from 6.4% to 55.0%. This highlights the need for novel methods that can quantify proteins without unique peptides. The knowledge about the structure of the bipartite peptide-protein graphs gained in this study will be useful for the development of such algorithms. Bipartite graph ; In silico ; Peptide ; Combinatorics ; Computer science ; Graph ; Computational biology ; Mathematics ; Biology ; Genetics ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Priyanka Kothoke | Anupama Deshpande | Yogesh Chaudhari
Source:  (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Partial Discharge Type Detection utilizing Statistical Techniques (n-q) and Random Forest Method Partial Discharge (PD) designs are critical instrument for the findings of high voltage (HV) protection frameworks. Human specialists can find conceivable protection absconds in different portrayals of the PD information. One of the most broadly utilized portrayals is Phase-Resove,d PD (PRPD) design Partial discharge ; Random forest ; Voltage ; Statistical analysis ; Computer science ; High voltage ; Phase (matter) ; Electronic engineering ; Artificial intelligence ; Statistics ; Mathematics ; Electrical engineering ; Engineering ; Physics High voltage insulation and dielectric phenomena ; Electrostatic Discharge in Electronics ; Power Transformer Diagnostics and Insulation
Authors: Huoming Zhang | Dalila Bensaddek
Source: Preprints.org (preprint, 2021-07-13)
Field: Chemistry — Spectroscopy

Narrow Precursor Mass Range for DIA-MS Enhances Protein Identification and Quantification Data independent acquisition - mass spectrometry (DIA-MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA-MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on Arabidopsis sample with spike-in of known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400-1200 m/z. When combining several DIA-MS analyses with narrow precursor ranges (i.e., 400-650, 650-900 and 900-1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of &amp;lt;6%. These findings represent a 59.4% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the 6-protein mix spike-in. In cDIA only 5 out of the 6-protein mix were quantified while our approach allowed accurate quantitation of all six proteins. Mass spectrometry ; Proteomics ; Quantitative proteomics ; Chemistry ; Label-free quantification ; Chromatography ; Quantitative analysis (chemistry) ; Coefficient of variation ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Costas Poulios | Vassilios Constantoudis
Source: Mathematical Problems in Engineering (article, 2021-06-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Mathematical Analysis of Nanostructured Surfaces: The Period-Scale Transform This work has been motivated by the urgent need for accurate and complete characterization of patterns consisting of almost periodic arrangements of specific features (trenches, bumps, holes, spikes, and so on) amply used in the industries of nanotechnology, microelectronics, and photonics. The quantitative characterization of such surface structures demands mathematical methods able to reveal both period- and feature-scale aspects. Given that the conventional approaches (Fourier or wavelet transform) are limited to either periodicity or feature-scale characterization, our work contributes with the proposal of a transformation which combines Fourier and wavelet merits to quantify simultaneously the period and feature scale of a periodic or almost periodic surface pattern. The output of our study has been (a) a detailed investigation of the mathematical properties of the proposed period-scale transform (PST) along with its relationship with other well-known transforms, (b) a presentation of some examples of PST of model 1D periodic surfaces to identify its benefits, and (c) first applications of PST in real profiles extracted from experimental polymer surfaces after plasma treatment. Fourier transform ; Characterization (materials science) ; Microelectronics ; Feature (linguistics) ; Scale (ratio) ; Wavelet ; Wavelet transform ; Period (music) ; Surface (topology) ; Continuous wavelet transform ; Computer science ; Materials science ; Mathematics ; Nanotechnology ; Artificial intelligence ; Discrete wavelet transform ; Geometry ; Mathematical analysis ; Acoustics ; Physics Liquid Crystal Research Advancements ; Image and Signal Denoising Methods ; Digital Filter Design and Implementation
Authors: Zhiqiang Dong | Yang Liu | Baoxia Ci | Ming Wen | Minghua Li | Xi Lu | Xiaokang Feng | Shuai Wen | Fuyu Ma
Source: Research Square (preprint, 2021-04-09)
Field: Chemistry — Analytical Chemistry

Estimation of nitrate nitrogen content in cotton petioles under drip irrigation based on spectral indices and wavelet neural network Drip irrigation ; Nitrate ; Wavelet ; Nitrogen ; Content (measure theory) ; Irrigation ; Mathematics ; Environmental science ; Agronomy ; Chemistry ; Computer science ; Artificial intelligence ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Smart Agriculture and AI
Authors: Benjamin O’Driscoll
Source: SoftwareX (article, 2021-07-01)
Field: Materials Science — Materials Chemistry

SCRAMBLE: Sweep Comparison Research Application for Multiple Back-Gated FieLd Effect measurements of graphene field effect transistors Graphene Field Effect Transistors (GFETs) are active electronic components which exploit the modulation of charge carriers in a graphene channel for a wide variety of applications such as electronic switching, amplification and biosensing. Herein describes a new software package SCRAMBLE, written in Python and developed with a graphical user interface, to speed up the routine processing of multiple back-gated electrical measurements from GFETs. For forward and reverse sweeps, SCRAMBLE automatically determines the Dirac points, positions of maximum transconductance and calculates the field effect mobilities for electrons and holes. Graphene ; Transconductance ; Field-effect transistor ; Python (programming language) ; Computer science ; Transistor ; Exploit ; Software ; Optoelectronics ; Materials science ; Electrical engineering ; Nanotechnology ; Voltage ; Engineering Graphene research and applications ; Quantum and electron transport phenomena ; Radiation Effects in Electronics
Authors: Cássia Barbosa Gomes | Elaine Carballo Siqueira Corrêa | Renata Braga Soares | Ricardo Adriano Dorledo de Faria | Vanessa Freitas de Cunha Lins | Wellington Lopes
Source: Tecnologia em Metalurgia Materiais e Mineração (article, 2021-01-01)
Field: Materials Science — Metals and Alloys

Análise da influência das condições de envelhecimento na resistência mecânica e à corrosão do aço UNS S31803 A presena da fase sigma () nos aos inoxidveis duplex pode fragilizar esses materiais alm de reduzir a resistncia corroso. Considerando esta abordagem, este trabalho investigou os efeitos das condies do tratamento trmico de envelhecimento na resistncia mecnica e corroso do ao inoxidvel duplex UNS S31803. A avaliao da evoluo microestrutural foi feita por meio de microscopia ptica e eletrnica de varredura, as propriedades mecnicas a partir de ensaios de trao, flexo e microdureza Vickers enquanto o estudo da corroso por meio dos ensaios de polarizao potenciodinmica. A precipitao da fase sigma ocorreu para as duas temperaturas de envelhecimento, 800 C e 900 C, e dois tempos de encharque, 20 e 60 minutos. A resistncia mecnica aumentou em relao ao estado solubilizado para os dois modos de caracterizao (trao e flexo), mas a ductilidade variou em funo do modo de caracterizao. A menor resistncia corroso ocorreu para o envelhecimento realizado a 800 C durante 60 minutos. Resist ; Materials science ; Composite material ; Layer (electronics) Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability
Authors: Amorndej Puttipipatkajorn | Amornrit Puttipipatkajorn
Source: International journal of agricultural and biological engineering (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Spectroscopic measurement approaches in evaluation of dry rubber content of cup lump rubber using machine learning techniques Dry rubber content (DRC) is an important factor to be considered in evaluating the quality of cup lump rubber. The DRC analysis requires prolonged laboratory validation. To develop fast and effective DRC determination methods, this study proposed methods to evaluate the DRC of cup lump rubber using different spectroscopic measurement approaches. This involved a complete fundamental analysis leading to an efficient measurement method based on either point-based measurement using NIR reflectance spectrometer or area-based measurement using hyperspectral imaging. A dataset was prepared that 120 samples were randomly divided into a calibration set of 90 samples and a validation set of 30 samples. To obtain an average spectrum to represent a cup lump rubber sample, the spectral data were collected by locating and scanning for point-based and area-based measurement, respectively. The spectral data were calibrated using partial least squares regression (PLSR) and the least-squares support vector machine (LS-SVM) methods against the reference values. The experiments showed that the area-based measurement approach with both algorithms performed outstandingly in predicting the DRC of cup lump rubber and was clearly better than the point-based measurement approach. The best predictions of PLSR represented by the coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the residual predictive deviation (RPD) were 0.99, 0.72% and 15.17, while the best prediction of LS-SVM were 0.99, 0.64% and 16.83, respectively. In summary, the area-based measurement based on the LS-SVM prediction model provided a highly accurate estimate of the DRC of cup lump rubber. Keywords: cup lump rubber, dry rubber content, spectroscopic measurement, machine learning, partial least squares regression, least-squares support vector machine DOI: 10.25165/j.ijabe.20211403.6298 Citation: Puttipipatkajorn A, Puttipipatkajorn A. Spectroscopic measurement approaches in evaluation of dry rubber content of cup lump rubber using machine learning techniques. Int J Agric & Biol Eng, 2021; 14(3): 207–213. Natural rubber ; Partial least squares regression ; Calibration ; Coefficient of determination ; Support vector machine ; Residual ; Mean squared error ; Mathematics ; Hyperspectral imaging ; Least squares support vector machine ; Statistics ; Artificial intelligence ; Computer science ; Algorithm ; Materials science ; Composite material Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis