jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: B. Mylemans | Theo Killian | Laurens Vandebroek | Luc Van Meervelt | Jeremy R. H. Tame | Tatjana N. Parac‐Vogt | Arnout Voet
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-04-12)
Field: Materials Science — Materials Chemistry

Crystal structures of Scone, pseudosymmetric folding of a symmetric designer protein Abstract Recent years have seen a raise in the development of computational proteins including symmetric ones. We recently developed a nine-fold symmetric β -propeller protein named Cake. Here we wanted to further engineer this protein to a three-fold symmetric nine-bladed propeller using computational design. Two nine-bladed propeller proteins were designed, named Scone-E and Scone-R. Crystallography however revealed the structure of both designs to adopt an eight-fold conformation with distorted termini, leading to a pseudo-symmetric protein. One of the proteins could only be crystallized upon addition of a polyoxometalate highlighting the usefulness of these molecules as a crystallisation additive. Protein crystallization ; Propeller ; Crystallization ; Fold (higher-order function) ; Folding (DSP implementation) ; Crystallography ; Protein folding ; Protein engineering ; Chemistry ; Computer science ; Engineering ; Biochemistry ; Mechanical engineering ; Marine engineering Enzyme Structure and Function ; Protein Structure and Dynamics ; Porphyrin Metabolism and Disorders
Authors: Mostafa G. Fadl | Zenat Kamel Mohamed
Source: Preprints.org (preprint, 2021-03-25)
Field: Chemistry — Inorganic Chemistry

Characterization of Binding Sites and Optimization of Cell Free Bacteria Condition for Metal Bio-Sorbents Bacteria a Microscopic organisms are the most inexhaustible and flexible of microorganisms and constitute a huge division of the whole living earthly biomass, certain microorganisms were found to amass metallic components at a high limit Was Known as Bacterial Bio-sorption Due to their little size, capacity to become under controlled conditions, and their Accommodation to an extensive variety of ecological situations; Potent metal bio-sorbents among microorganisms, at low pH esteems, cell divider ligands are protonated and contend essentially with metals for official. With expanding pH, more ligands, such as amino and carboxyl groups, could be exposed, leading to attraction between these negative charges and the metals, and consequently increment bio-sorption onto the cell surface. Starting with Isolation and identification of heavy metal-resistant bacteria from rock Ore. Studying Factors Affecting Uranium Bio-sorption, Optimization of bacterial growth conditions and optimum for metal uptake by free and immobilized bacterial cells and Desorption ratio of uranium ions adsorbed by Coli. /alginate, All this evidence suggest that functions groups Represented in our study are responsible for metal uptake in our bacterial biomass beside change in peaks position which assigned for it's groups confirm bio-sorption of metal ions from waste due to ions charge interaction comparing with immobilized we found increase in no of binding sites indicate that immobilized bacterial have high efficiency for metal up take which also change in peaks position which assigned for its groups confirm bio-sorption of metal ions from waste due to ions charge interaction, Where the high bio-sorption yield obtained by bacteria, the Uranium &amp;amp; heavy metal bioremediation process expects microorganisms to be joined to a strong surface. Sorption ; Metal ions in aqueous solution ; Metal ; Chemistry ; Adsorption ; Desorption ; Microorganism ; Bacterial cell structure ; Bacteria ; Uranium ; Environmental chemistry ; Inorganic chemistry ; Materials science ; Organic chemistry ; Biology Radioactive element chemistry and processing ; Chromium effects and bioremediation ; Adsorption and biosorption for pollutant removal
Authors: Rezvan Ramezannejad | Morteza Mofid Bojnoordi | Mohammad Armin | Mahnaz Aghdasi
Source: Research Square (preprint, 2021-09-20)
Field: Chemistry — Analytical Chemistry

Artificial Neural Network Modeling To Predict And Optimize Phenolic Acids Production From Callus Culture of Lactuca Undulata Abstract The present study aims to model and optimize phenolic acids productions from Lactuca undulate root and leaf-derived callus using the feed-forward Artificial Neural Network (ANN) model. For this purpose, the effect of different concentrations (0, 0.1, 0.5, 1, and 2 mg/l) of Kin in combinations with or without 2,4-D and/or NAA was investigated on callus induction and phenolic acids production. A multi-layer perceptron ANN was applied to correlate the output parameters (cichoric acid, chlorogenic acid and caffeic acid contents) to input (Kin, 2,4-D and NAA) training parameters. A single hidden layer with 5, 10, 15, 20, 25, 30, 35 and 40 neurons was used to optimize ANN architecture. Sum squared error (SSE), Relative Error (RE) and correlation factor (R 2 ) were applied to identify the performance of ANN models. According to the obtained data, the feed-forward neural network with tangent-sigmoid (3-30-1), tangent-tangent (3-15-1) and tangent-tangent (3-35-1) activation function was found as the best model to predict cichoric acid, chlorogenic acid and caffeic acid production from leaf-derived callus, respectively. Meanwhile, ANN with activation function of tangent-tangent (3-20-1), tangent-tangent (3-25-1) and sigmoid-sigmoid (3-20-1) were the most effective models to predict the amount of cichoric acid, chlorogenic acid and caffeic acid from root-derived callus, respectively. In the current study, there was a strong correlation between experimental and predicted data. These results demonstrated that the selected ANN model could predict the effects of plant growth regulators on phenolic acids production using callus culture method. Chlorogenic acid ; Caffeic acid ; Sigmoid function ; Callus ; Botany ; Artificial neural network ; Activation function ; Chemistry ; Biological system ; Mathematics ; Biology ; Biochemistry ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses
Authors: Samuel Beaulieu | Michael Schüler | Jakub Schusser | Shuo Dong | Tommaso Pincelli | Julian Maklar | Alexander Neef | F. Reinert | Martin Wolf | Laurenz Rettig | J. Minář | Ralph Ernstorfer
Source: npj Quantum Materials (preprint, 2021-11-15)
Field: Materials Science — Materials Chemistry

Unveiling the orbital texture of 1T-TiTe2 using intrinsic linear dichroism in multidimensional photoemission spectroscopy Abstract The momentum-dependent orbital character in crystalline solids, referred to as orbital texture, is of capital importance in the emergence of symmetry-broken collective phases, such as charge density waves as well as superconducting and topological states of matter. By performing extreme ultraviolet multidimensional angle-resolved photoemission spectroscopy for two different crystal orientations linked to each other by mirror symmetry, we isolate and identify the role of orbital texture in photoemission from the transition metal dichalcogenide 1T-TiTe 2 . By comparing our experimental results with theoretical calculations based on both a quantitative one-step model of photoemission and an intuitive tight-binding model, we unambiguously demonstrate the link between the momentum-dependent orbital orientation and the emergence of strong intrinsic linear dichroism in the photoelectron angular distributions. Our results represent an important step towards going beyond band structure (eigenvalues) mapping and learning about electronic wavefunction and orbital texture of solids by exploiting matrix element effects in photoemission spectroscopy. Angle-resolved photoemission spectroscopy ; Photoemission spectroscopy ; Inverse photoemission spectroscopy ; Linear dichroism ; Condensed matter physics ; Texture (cosmology) ; Electronic structure ; Physics ; X-ray photoelectron spectroscopy ; Single crystal ; Chemistry ; Crystallography ; Circular dichroism ; Nuclear magnetic resonance 2D Materials and Applications ; Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides
Authors: Nikolai Bardarov | Vladislav Todorov | Nicole Christoff
Source: Sustainability (article, 2021-07-06)
Field: Chemistry — Organic Chemistry

Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels The need to identify wood by its anatomical features requires a detailed analysis of all the elements that make it up. This is a significant problem of structural wood science, the most general and complete solution of which is yet to be sought. In recent years, increasing attention has been paid to the use of computer vision methods to automate processes such as the detection, identification, and classification of different tissues and different tree species. The more successful use of these methods in wood anatomy requires a more precise and comprehensive definition of the anatomical elements, according to their geometric and topological characteristics. In this article, we conduct a detailed analysis of the limits of variation of the location and grouping of vessels in the observed microscopic samples. The present development offers criteria and quantitative indicators for defining the terms shape, location, and group of wood tissues. It is proposed to differentiate the quantitative indicators of the vessels depending on their geometric and topological characteristics. Thus, with the help of computer vision technics, it will be possible to establish topological characteristics of wood vessels, the extraction of which would be used to develop an algorithm for the automatic classification of tree species. Identification (biology) ; Computer science ; Tree (set theory) ; Artificial intelligence ; Topology (electrical circuits) ; Pattern recognition (psychology) ; Mathematics ; Biology ; Ecology ; Combinatorics Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Forest ecology and management
Authors: Itsaso Leceta | Cristina Alcalde | Marta Urdanpilleta | Pedro Guerrero | Koro de la Caba | Ana Burusco
Source: Computers & Chemical Engineering (article, 2021-06-17)
Field: Materials Science — Biomaterials

New algorithm for the elucidation of functional properties of gelatin-based materials In the present work, fish gelatin was employed to develop renewable and biodegradable materials, reducing environmental problems associated with conventional petroleum-based materials. Glycerol was used as plasticizer and gallic acid was added in order to enhance the functional properties of the material. L-fuzzy concept analysis was applied for modelling the formulations and properties of the films. These new methodology is used in the design of the material avoiding the traditional inefficient trial an error approach usually employed. Two applications of the developed bio-based material were analyzed: fatty food packaging application in food area and wound healing in the biomedical field. The functional properties requirements of water contact angle (CA), water vapour transmission rate (WVTR), colour L* and b* values, tensile strength (TS), elongation at break (EB) and gloss values were specified for both applications. Applying the proposed algorithm, the required formulations were estimated and the experimental results showed a high accordance with the predicted values of the final properties, as well as with the requirements. This analysis allowed finding the required formulations in a highly cost-effective way. Gloss (optics) ; Gelatin ; Ultimate tensile strength ; Process engineering ; Algorithm ; Plasticizer ; Materials science ; Computer science ; Biological system ; Biochemical engineering ; Composite material ; Chemistry ; Coating ; Engineering ; Organic chemistry biodegradable polymer synthesis and properties ; Nanocomposite Films for Food Packaging ; Collagen: Extraction and Characterization
Authors: Don S. Munasinghe | Seneviratnege Somaratne | S. R. Weerakoon | Chandani Ranasinghe
Source: The EuroBiotech Journal (article, 2021-04-01)
Field: Chemistry — Organic Chemistry

<i>In vitro</i> production of sesquiterpenes by electro-elicitation in <i>Gyrinops walla</i> Gaetner calli and cell suspension cultures Abstract Aloeswood or Agarwood has long been perfumery commodity traded between Mediterranean Region and Southeast Asia since ancient times. Oil or chips are obtained by destructive harvesting of several Thymeleaceous genera includes Aquilaria and Gonystylus and are expensive and highly demanded ingredients in the global market. The recent recovery of Gyrinops walla as a potential producer of market-quality agarwood in mature damaged woods and branches, the intense illicit felling and exportation G. walla leading to the verge of extinction from Sri Lankan flora. The sustainable utilization of G. walla undoubtedly enhances the foreign exchange of the country and the non-destructive utilization G. walla through biotechnology is the only option available for sustainable exploitation and conservation of the vulnerable G. walla species. An electro-elicitation apparatuses were designed and built to stimulate calli and cell suspensions. The elicited and calli and cell suspensions were harvested at different time periods to extract sesquiterpenes. Current intensities of 10 mA and 50 mA, and 0.1 mA were the optimum values for the induction of sesquiterpenes; γ-selinene, β-caryophyllene, α-cadinol and α-guaiene, production in both calli and cell suspension after 8 weeks and 6 hours, respectively. The findings of the study led to conclude the possibility of induction of production of sesquiterpenes through electro-elicitation of G. walla calli and cell suspension in an in vitro system for sustainable utilization and conservation endeavours. Agarwood ; Horticulture ; Geography ; Botany ; Biology ; Agroforestry ; Traditional medicine Wood and Agarwood Research ; Plant tissue culture and regeneration ; Plant Pathogens and Fungal Diseases
Authors: Aliefia Noor | Meri Hamdini | Salsabila Ramadina | Yuant Tiandho
Source: Jurnal Geliga Sains Jurnal Pendidikan Fisika (review, 2021-01-10)
Field: Materials Science — Materials Chemistry

Dye-Sensitized Solar Cell-Based Photovoltaic Thermal for Ethanol Distillation: A Narrative Review The potential for solar energy in Indonesia is abundant and attractive to be developed into one of the leading renewable energy sources. Photovoltaic or solar cells are devices that can be used to convert solar energy directly into electrical energy. A dye-sensitized solar cell (DSSC) is an exciting type of solar cell to be developed because it is cheap, easy, and can use natural dyes based on plant extracts. However, the performance of DSSC degrades when it is at high operating temperatures. In this article, a narrative review is presented to improve the efficiency of DSSC by integrating with a solar collector in the form of a photovoltaic/thermal (PV/T) system. The solar collector will act as a heat absorbent from the DSSC, and the heat energy obtained will be used to distill ethanol. Optimization in the ethanol distillation system can take advantage of CuO as a nanoparticle in the working fluid or better know as nanofluid. Dye-sensitized solar cell ; Photovoltaic system ; Photovoltaic thermal hybrid solar collector ; Renewable energy ; Solar energy ; Solar cell ; Materials science ; Thermal energy ; Distillation ; Thermal ; Process engineering ; Optoelectronics ; Chemistry ; Electrical engineering ; Engineering ; Physics ; Meteorology ; Thermodynamics ; Chromatography Copper-based nanomaterials and applications ; Solar-Powered Water Purification Methods ; TiO2 Photocatalysis and Solar Cells
Authors: Maxim V. Petoukhov | Petr V. Konarev | В. В. Волков | Andrey A. Mozhaev | Eleonora V. Shtykova
Source: Biochemistry (Moscow) Supplement Series A Membrane and Cell Biology (article, 2021-07-01)
Field: Materials Science — Materials Chemistry

The Ambiguity Issue in Solving Inverse Problems of Small-Angle Scattering: A Consistent Approach Using an Insulin Receptor-Related Receptor as an Example. Methods for Interpreting SAXS Data Abstract The construction of three-dimensional models of protein macromolecules is a serious challenge due to the possible ambiguity of solving the inverse problem of reconstructing a three-dimensional structure from a one-dimensional small-angle scattering profile. The target function of this task can have several local minima, which leads to the dependence of the solution on the initial values of the model parameters and on the method of finding the global minimum. The problem of creating structural models is also complicated by averaging the scattering pattern over all orientations of particles in space and by the size and shape distribution of scattering objects in the case of polydispersity and/or polymorphism. In this study, the issue of ambiguity in solving inverse problems and restoring the three-dimensional structure of a protein is considered using the structure of the ectodomain of an insulin receptor-related receptor (ectoIRR) in solution as an example. The paper presents a consistent approach to solving this problem, starting from the determination of general structural parameters and ab initio reconstruction of shape to modeling by rigid bodies (using molecular tectonics), hybrid methods, and analysis of scattering profiles by singular vector decomposition. Inverse scattering problem ; Maxima and minima ; Scattering ; Inverse problem ; Mathematics ; Mathematical analysis ; Applied mathematics ; Physics ; Mathematical optimization ; Statistical physics ; Optics Enzyme Structure and Function ; Advanced Biosensing Techniques and Applications ; Advanced Proteomics Techniques and Applications
Authors: Segun Emmanuel Adebayo | Norhashila Hashim
Source: Food Research (article, 2021-02-27)
Field: Chemistry — Analytical Chemistry

Prediction of quality attributes and maturity classification of pear fruit using laser imaging and Artificial Neural Network In this study, the application of laser imaging technique was utilized to predict the quality attributes (firmness and soluble solids content) of pear fruit and to classify the maturity stages of the fruit harvested at different days after full bloom (dafb). Laser imaging system emitting at visible and near infra-red region (532, 660, 785, 830 and 1060 nm) was deployed to capture the images of the fruit. Optical properties (absorption ma and reduced scattering ms ʹ coefficients) at individual and combined wavelengths of the laser images of the fruit were used in the prediction and classifications of the maturity stages. Artificial neural network (ANN) was employed in the building of both prediction and classification models. Root mean square error of calibration (RMSEC), root mean square error of crossvalidation (RMSECV), correlation coefficient (r) and bias were used to test the performance of the prediction models while sensitivity and specificity were used to evaluate the classification models. The results showed that there was a very strong correlation between the ma and ms ʹ with pear development. This study had shown that optical properties of pears with ANN as prediction and classification models can be employed to both predict quality parameters of pear and classify pear into different (dafb) non-destructively. PEAR ; Mean squared error ; Artificial neural network ; Correlation coefficient ; Mathematics ; Calibration ; Artificial intelligence ; Pattern recognition (psychology) ; Biological system ; Statistics ; Computer science ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Plant Physiology and Cultivation Studies ; Postharvest Quality and Shelf Life Management
Authors: Elahe Naghdi | Wim De Malsche
Source: Journal of Chromatography A (article, 2021-06-09)
Field: Chemistry — Spectroscopy

Overloading behavior of fenoprofen and naproxen as two model compounds on a non-porous silicon pillar array column Chemistry ; Naproxen ; Adsorption ; Chromatography ; Freundlich equation ; Langmuir adsorption model ; Langmuir ; Analyte ; Phase (matter) ; Methanol ; Porosity ; Analytical Chemistry (journal) ; Organic chemistry Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Protein purification and stability
Authors: Israa Mohammed Hassoon
Source: Iraqi Journal of Science (review, 2021-07-31)
Field: Chemistry — Analytical Chemistry

Shape Feature Extraction Techniques for Fruits: A Review Fruits sorting, recognizing, and classifying are essential post-harvest operations, as they contribute to the quality of food industry, thereby increasing the exported quantity of food. Today, an automated system for fruit classification and recognition is very important, especially when exporting to markets where quality of fruit must be high. In this study, the advantages and disadvantages of the various shape-based feature extraction algorithms and technologies that are used in sorting, classifying, and grading of fruits, as well as fruits quality estimation, are discussed in order to provide a good understanding of the use of shape-based feature extraction techniques. Sorting ; Feature extraction ; Computer science ; Grading (engineering) ; Artificial intelligence ; Pattern recognition (psychology) ; Quality (philosophy) ; Engineering ; Algorithm Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing and Land Use
Authors: Jenna Hershberger | Edwige Gaby Nkouaya Mbanjo | Prasad Peteti | Andrew Ikpan | Kayode Ogunpaimo | Kehinde Nafiu | Ismail Rabbi | Michael A. Gore
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-04-30)
Field: Chemistry — Analytical Chemistry

Low-cost, handheld near-infrared spectroscopy for root dry matter content prediction in cassava ABSTRACT Over 800 million people across the tropics rely on cassava as a major source of calories. While the root dry matter content (RDMC) of this starchy root crop is important for both producers and consumers, characterization of RDMC by traditional methods is time-consuming and laborious for breeding programs. Alternate phenotyping methods have been proposed but lack the accuracy, cost, or speed ultimately needed for cassava breeding programs. For this reason, we investigated the use of a low-cost, handheld NIR spectrometer for field-based RDMC prediction in cassava. Oven-dried measurements of RDMC were paired with 21,044 scans of roots of 376 diverse clones from 10 field trials in Nigeria and grouped into training and test sets based on cross-validation schemes relevant to plant breeding programs. Mean partial least squares regression model performance ranged from R 2 p = 0.62 - 0.89 for within-trial predictions, which is within the range achieved with laboratory-grade spectrometers in previous studies. Relative to other factors, model performance was highly impacted by the inclusion of samples from the same environment in both the training and test sets. Random forest variable importance analysis of root spectra revealed increased importance in a region previously identified as predictive of water content in plants (~950 - 990 nm). With appropriate model calibration, the tested spectrometer will allow for field-based collection of spectral data with a smartphone for accurate RDMC prediction and potentially other quality traits, a step that could be easily integrated into existing harvesting workflows of cassava breeding programs. CORE IDEAS A low-cost, handheld near-infrared spectrometer was tested for phenotyping of cassava roots Plant breeding-relevant cross-validation schemes were used for predictions High prediction accuracies were achieved for cassava root dry matter content A spectral region predictive of plant water content was identified as important Dry matter ; Partial least squares regression ; Spectrometer ; Calibration ; Environmental science ; Near-infrared spectroscopy ; Statistics ; Agricultural engineering ; Mathematics ; Computer science ; Agronomy ; Biology ; Engineering Spectroscopy and Chemometric Analyses ; Cassava research and cyanide ; Banana Cultivation and Research