jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Miranda F. Kamal | Azza A. Gazy | MARWA K. EL-JAMAL
Source: Archives of Pharmaceutical Sciences Ain Shams University (article, 2020-12-01)
Field: Chemistry — Analytical Chemistry

Inversely Calibrated Curvilinear Artificial Neural Network Model for Simultaneous Assay of Ternary Cardiovascular Drug Mixture Novel chemometric design, tailored for pre-clinical multiple drug screening, goals for bioanalytical future scope. A highly sensitive, non-linear multivariate Artificial Neural Network (ANN) is developed and applied for simultaneous spectrophotometric determination of three commonly concomitant cardiovascular drugs in laboratory made mixtures and spiked human plasma samples. Ticagrelor, Irbesartan and Hydrochlorothiazide have been simultaneously quantified in the curvilinear ranges of 0-30 µg/mL, 0-10 µg/mL and 0-3 µg/mL respectively. Highly overlapping Near UV absorption spectra of three drugs, in the region of 215-280 nm, have been recorded 1-nm range in synthetic ternary mixtures and trained iteratively. By inversely relating the concentration matrix (x-block) with its corresponding absorption one (y-block), gradient-descent back-propagation ANN calibration could be computed and optimized. All proposed mathematical modeling was manipulated using MATLAB® 2007, reaching down to sixth order exponential Mean Square Error, MSE. To validate, independent set of ternary synthetic mixtures has been constructed and examined, where excellent recovery results has been obtained. Furthermore, application of suggested model to varying ratios synthetic ternary mixtures as well as spiked plasma samples has resulted in accurate, precise and robust estimations with no background interference. ANN method was compared to a reference HPLC method; Student’s t-test and F-variance ratio were calculated and showed insignificant difference. This chemometric approach is an eco-friendly green assay, time-saving, and economic method. It initiates a pathway for clinical drug screening through affordable spectroscopic instrumentation. Ternary operation ; Artificial neural network ; Chemometrics ; Chromatography ; Mean squared error ; Lapatinib ; Chemistry ; Matrix (chemical analysis) ; Bioanalysis ; Mathematics ; Biological system ; Analytical Chemistry (journal) ; Computer science ; Artificial intelligence ; Statistics Analytical Methods in Pharmaceuticals ; Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Daniel Dodoo | Samuel Kofi Tulashie | Thomas Dodoo | Francis Kwaw
Source:  (preprint, 2020-11-17)
Field: Chemistry — Organic Chemistry

Assessing the effects of Sunlight on the Photooxidation of Tropical Oils This study aims to investigate the influence of sunlight on the photooxidation of tropical oils (TOs). Coconut oil (CNO), palm oil (PO), and palm kernel oil (PKO) were chosen for determining the indicators of photooxidation when exposed to and in the absence of sunlight for seven weeks. The results showed a significant (p &lt; 0.05) increase in free fatty acid (FFA) levels and peroxide value (PV) when the TOs were exposed to sunlight. The iodine value (IV) and colour content decreased significantly (p &lt; 0.05) due to the decomposition of unsaturated FFAs owing to the breaking-down of the π-bonds and the degradation of colour pigments during photooxidation. FTIR analysis showed strong vibrational absorptions at 1721 and 3505 cm, 1720 and 3560 cm, and 1721 and 3554 cm for the CNO, PO, and PKO samples exposed to sunlight, respectively. These bands can be attributed to the presence of secondary oxidation products, which were absent in the TOs that were not exposed to sunlight. A simulation was performed to support the FTIR results, which also indicated peaks from the secondary oxidation products at 1744 and 3660 cm. The study also revealed that the rate of photooxidation was different for each TOs. The rate of oxidation followed the order PO &gt; PKO &gt; CNO. In contrast, no notable changes were observed in the TOs kept away from the sunlight. These results suggest that exposing TOs to sunlight influences their oxidation stability and quality. Sunlight ; Chemistry ; Peroxide ; Decomposition ; Iodine value ; Fourier transform infrared spectroscopy ; Nuclear chemistry ; Degradation (telecommunications) ; Pigment ; Palm oil ; Photochemistry ; Food science ; Organic chemistry ; Chemical engineering Edible Oils Quality and Analysis ; Coconut Research and Applications ; Spectroscopy and Chemometric Analyses
Authors: Kaan Karaoğlu
Source: Journal of Anatolian Environmental and Animal Sciences (article, 2020-03-17)
Field: Chemistry — Spectroscopy

Detection of Hg2+ in Aqueous Media by A New Xanthene Based Schiff Base Sensor A xanthene-based colorimetric sensor, 2-((5-chloro-2-oxoindolin-3-ylidene)amino)-3',6'-bis(diethylamino)spiro[isoindoline-1,9'-xanthen]-3-one, was designed and its metal sensing properties was evaluated in aqueous solutions. The sensor showed colorimetric response toward Hg2+ from colorless solution to pink among various metal ions such as Na+, K+, Mg2+, Ca2+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+, Zn2+, Al3+, Cd2+ and Pb2+. The addition of Hg2+ exhibit an absorption enhancement of the sensor based on a spirocycle ring‐opening process and a subsequent hydrolysis reaction. The detection limit of the sensor for Hg2+ was found to be 7.88×10−8 M. Xanthene ; Schiff base ; Detection limit ; Chemistry ; Aqueous solution ; Metal ions in aqueous solution ; Rhodanine ; Isoindoline ; Absorption (acoustics) ; Hydrolysis ; Aqueous medium ; Metal ; Inorganic chemistry ; Nuclear chemistry ; Medicinal chemistry ; Photochemistry ; Polymer chemistry ; Chromatography ; Organic chemistry ; Materials science Molecular Sensors and Ion Detection ; Analytical Chemistry and Sensors ; Advanced Chemical Sensor Technologies
Authors: Geneviève Dusson | Markus Bachmayr | Gábor Cśanyi | Ralf Drautz | Simon Etter | Cas van der Oord | Christoph Ortner
Source: arXiv (Cornell University) (preprint, 2020-04-23)
Field: Materials Science — Materials Chemistry

Approximation of Atomic Interactions with Spherical Harmonics The Atomic Cluster Expansion (Drautz, Phys. Rev. B 99, 2019) provides a\nframework to systematically derive polynomial basis functions for approximating\nisometry and permutation invariant functions, particularly with an eye to\nmodelling properties of atomistic systems. Our presentation extends the\nderivation by proposing a precomputation algorithm that yields immediate\nguarantees that a complete basis is obtained. We provide a fast recursive\nalgorithm for efficient evaluation and illustrate its performance in numerical\ntests. Finally, we discuss generalisations and open challenges, particularly\nfrom a numerical stability perspective, around basis optimisation and parameter\nestimation, paving the way towards a comprehensive analysis of the convergence\nto a high-fidelity reference model.\n Spherical harmonics ; Harmonics ; Spin-weighted spherical harmonics ; Physics ; Computational physics ; Theoretical physics ; Quantum mechanics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Advanced Chemical Physics Studies
Authors: Zachariah Baird | Oliver Järvik | Rivo Rannaveski | Vahur Oja
Source:  (preprint, 2020-12-07)
Field: Chemistry — Organic Chemistry

Properties of kukersite shale oil Inspite of the increasing focus on reducing carbon dioxide emissions, production of shale oil continues to be economically favorable, and production has even increased in recent years. Producing and handling shale oil requires data on its properties, and to provide this data we have undertaken an extensive project to experimentally measure the properties of Estonian kukersite shale oil. In this article we describe the sample preparation methods and present experimental data on key properties of the shale oil samples. Included is data on the densities, refractive indexes, average boiling points, and molar masses of distillation fractions with narrow boiling ranges. A major component of kukersite shale oil is phenolic compounds, and to investigate their effect on the properties we used extraction to obtain samples with either fewer or more phenols than commonly found in the oil. The effect of composition on the properties is discussed. We also present correlations for calculating one of these properties if two others are known. This article lays the groundwork for future articles which will go into further detail on specific properties of these samples. Oil shale ; Shale oil ; Distillation ; Petroleum engineering ; Boiling ; Boiling point ; Environmental science ; Shale oil extraction ; Tight oil ; Mineralogy ; Geology ; Materials science ; Chemistry ; Organic chemistry ; Paleontology Chemical Thermodynamics and Molecular Structure ; Chemical and Physical Properties in Aqueous Solutions
Authors: Ji‐il Kim | Cheong Hee Park
Source: Energies (article, 2020-10-19)
Field: Materials Science — Materials Chemistry

Partial Discharge Detection Based on Anomaly Pattern Detection Recently, a lot of research has been carried out on partial discharge (PD) using machine learning techniques. However, most of these studies have focused on the identification of multiple PD sources, PD classification, or denoising PD measurements, with few studies on real-time PD occurrence detection. In this paper, we propose a method to detect PD occurrence based on anomaly pattern detection. The proposed method consists of three steps. First, in the data preprocessing step, the pulse sequence data are converted into a feature vector stream by applying a sliding window technique. In the next step, normal data modeling is performed using feature vectors transformed from pulse sequence data collected in a normal state where no PD occurs. Finally, for the monitored pulse sequence, an online process for PD detection is carried out through conversion to a feature vector data stream and an anomaly pattern detection method. Experimental results using simulated PD data demonstrate the capabilities of the proposed method. Pattern recognition (psychology) ; Anomaly detection ; Sliding window protocol ; Preprocessor ; Computer science ; Artificial intelligence ; Feature (linguistics) ; Support vector machine ; Data pre-processing ; Feature vector ; Sequence (biology) ; Partial discharge ; Data mining ; Window (computing) ; Engineering ; Chemistry ; Voltage High voltage insulation and dielectric phenomena ; Electrostatic Discharge in Electronics ; Internet Traffic Analysis and Secure E-voting
Authors: Mostafa Hassanisadi | Morteza G. Khaledi | Mehdi Jalali‐Heravi
Source: Analytical Methods in Environmental Chemistry Journal (article, 2020-06-01)
Field: Chemistry — Spectroscopy

Determination and prediction of peptide mobilities by micellar electro-kinetic chromatography using adaptive neuro-fuzzy inference system as a feature selection method Mobility of 128 peptides composed of up to 14 amino acids is determined for sodium dodecyl sulfate (SDS) micellar systems using micellar electrokinetic chromatography (MEKC). The mobilities of these peptides are predicted using back propagation of error artificial neural networks (BP-ANNs). Adaptive neuro-fuzzy inference system (ANFIS) which can deal with linear and nonlinear phenomena is used to select the inputs of BP-ANN. A 3:4:1 BP-ANN model with four variables of Kappa&nbsp; substituent constant, Kappa(H), number of peptide bonds, (ln(N), molar refractivity of C-terminal, MRC, and steric effects at N-terminal, ES,N, which incorporate substituent, steric and molar refractivity effects as its inputs was developed. Comparison of Multiple Linear Regression (MLR) and ANN results shows the nonlinear characteristic of the phenomena. The nonlinear model was successful in predicting the mobilities of 120 peptides except for the ones (8 peptides) with negatively charged amino acids. Micellar electrokinetic chromatography ; Chemistry ; Substituent ; Artificial neural network ; Sodium dodecyl sulfate ; Adaptive neuro fuzzy inference system ; Capillary electrophoresis ; Feature selection ; Biological system ; Steric effects ; Amino acid ; Chromatography ; Artificial intelligence ; Computer science ; Stereochemistry ; Fuzzy control system ; Fuzzy logic Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies ; Gene expression and cancer classification
Authors: Jun-Kyu Park | Suwoong Lee | Aaron Park | Sung‐June Baek
Source: Mathematics (article, 2020-11-06)
Field: Chemistry — Analytical Chemistry

Fast Search Method Based on Vector Quantization for Raman Spectroscopy Identification In spectroscopy, matching a measured spectrum to a reference spectrum in a large database is often computationally intensive. To solve this problem, we propose a novel fast search algorithm that finds the most similar spectrum in the database. The proposed method is based on principal component transformation and provides results equivalent to the traditional full search method. To reduce the search range, hierarchical clustering is employed, which divides the spectral data into multiple clusters according to the similarity of the spectrum, allowing the search to start at the cluster closest to the input spectrum. Furthermore, a pilot search was applied in advance to further accelerate the search. Experimental results show that the proposed method requires only a small fraction of the computational complexity required by the full search, and it outperforms the previous methods. Computer science ; Search algorithm ; Principal component analysis ; Vector quantization ; Algorithm ; Matching (statistics) ; Cluster analysis ; Beam search ; Hierarchical clustering ; Nearest neighbor search ; Pattern recognition (psychology) ; Mathematics ; Data mining ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Risti Suryantari | Flaviana Catherine
Source: Journal of Photonic Materials and Technology (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The Temperature Dependence of Optical Texture in Chiral Nematic Liquid Crystal Observed by Polarizing Microscope Study the optical-thermal dependence of liquid crystal based on the quantity data of image texture is important to get more information accurately. In this research, the optical-thermal dependence of chiral nematic liquid crystals ink sample was investigated based on the texture and color changes of the sample at various temperatures. The textures of the samples were recorded by the crossed-polarizing optical microscope attached to the hot stage and a camera. The temperature dependence of textures are represented by the hue parameter values taken from the HSV image type. The result obtained from the graph of the increase mean hue parameter against the temperatures was in accordance with the preceding results done by the various techniques. The results show that the higher the temperature of the material, the higher the average hue value. The increase in the hue parameter relates to the color changes of texture from red-dominant to green-dominant. The color difference appeared in various wavelengths represent a diffraction pattern caused by its optically active and the twisted molecular structure. Approaching to the Bragg diffraction equation, the pitch obtained at 0.7 <i>µ</i>m. Furthermore, the relation of the different textures and the twist structure of the sample was evaluated. Considering the sample thickness of 100 µm carries out to the conclusion that there are hundreds of twisted nematic liquid crystal molecules in various alignment on a volume space. Liquid crystal ; Hue ; Materials science ; Texture (cosmology) ; Optics ; Diffraction ; Optical microscope ; Microscope ; Wavelength ; Thermal ; Optoelectronics ; Physics ; Scanning electron microscope ; Image (mathematics) ; Thermodynamics Liquid Crystal Research Advancements ; Optical Polarization and Ellipsometry ; Advanced Fluorescence Microscopy Techniques
Authors: Jinning Mao | Meng Jiang | Xingliang Dai | Guodong Liu | Zhixiang Zhuang | Jun Dong
Source: Research Square (preprint, 2020-10-26)
Field: Materials Science — Biomaterials

Superparamagnetic iron oxide nanoparticles enhance glioma radiosensitivity via inducing cell cycle arrest and apoptosis Abstract Aim: Superparamagnetic iron oxide nanoparticles (SPIONs) is a widely used biomedical material for imaging and targeting drug delivery. We synthesized SPIONs and tested their effects on the radiosensitization of glioma. Methods : Acetylated 3-aminopropyltrimethoxysilane (APTS)-coated iron oxide nanoparticles (Fe 3 O 4 NPs) were synthesized via a one-step hydrothermal approach and the surface was chemically modified with acetic anhydride to generate surface charge-neutralized NPs. NPs were characterized by TEM and ICP-AES. Radiosensitivity of U87MG glioma cells was evaluated by MTT assay. Cell cycle and apoptosis in glioma cells were examined by flow cytometry. Results: APTS-coated Fe 3 O 4 NPs had a spherical or quasi-spherical shape with average size of 10.5±1.1 nm. NPs had excellent biocompatibility and intracellular uptake of NPs reached the peak 24 hours after treatment. U87 cell viability decreased significantly after treatment with both X-ray and NPs compared to X-ray treatment alone. Compared to X-ray treatment alone, the percentage of cells in G2/M phase (31.83%) significantly increased in APTS-coated Fe 3 O 4 NPs plus X-ray treated group (P&lt;0.05). In addition, the percentage of apoptotic cells was significant higher in APTS-coated Fe 3 O 4 NPs plus X-ray treated group than in X-ray treatment alone group (P&lt;0.05). Conclusion: APTS-coated Fe 3 O 4 NPs achieved excellent biocompatibility and increased radiosensitivity for glioma cells. Radiosensitivity ; Apoptosis ; Cell cycle checkpoint ; Glioma ; Cell cycle ; Superparamagnetism ; Cancer research ; Nanoparticle ; Iron oxide nanoparticles ; Chemistry ; Cell biology ; Nanotechnology ; Materials science ; Radiation therapy ; Medicine ; Biology ; Biochemistry ; Internal medicine ; Physics Nanoparticle-Based Drug Delivery ; Glioma Diagnosis and Treatment ; MicroRNA in disease regulation
Authors: Sourav Kumar Das | Bulbul Ahmed | Rony Mia | A. Abu Bakar | Injamam Ul Huq | Dan Xie
Source: Advances in Nanoparticles (article, 2020-01-01)
Field: Materials Science — Biomaterials

Crystallinity of FRCM/GPM with High PB through Microbial Growth Fiber reinforced composite (FRC) requires a process of grinding, mixing and compounding natural fibers from cellulosic waste streams into a polymer matrix that creates a high-strength fiber composite. In this situation, the specified waste or base raw materials used are the waste thermoplastics and different types of cellulosic waste including rice husk and saw dust. FRC is a high-performance fiber composite achieved and made possible through a proprietary molecular re-engineering process by interlinking cellulosic fiber molecules with resins in the FRC material matrix, resulting in a product of exceptional structural properties. In this feat of molecular re-engineering, selected physical and structural properties of wood are effectively cloned and obtained in the FRC component, in addition to other essential qualities in order to produce superior performance properties to conventional wood. The dynamic characteristics of composite structures are largely extracted from the reinforcing of fibres. The fiber, held in place by the matrix resin, contributes to tensile strength in a composite, enhancing the performance properties in the final part, such as strength and rigidity, while minimizing weight. The advantages of composite materials always beat down their disadvantages. In this analysis, we tried to find out FRC advance manufacturing, recycling technology and future perspective for mankind and next generation development. This research will bring a new horizon for future science with FRC technology and every aspect of modern science which will bring a stable dimensional stability by recycling process with minimizing waste for environment and next generation science. Cellulosic ethanol ; Raw material ; Ultimate tensile strength ; Compounding ; Materials science ; Composite number ; Fiber ; Composite material ; Cellulose fiber ; Crystallinity ; Cellulose ; Engineering ; Chemistry ; Chemical engineering biodegradable polymer synthesis and properties ; Additive Manufacturing and 3D Printing Technologies ; Bone Tissue Engineering Materials
Authors: Muhammad Atiq Ur Rehman Tariq
Source: Computer Engineering and Intelligent Systems (article, 2020-02-01)
Field: Chemistry — Analytical Chemistry

Identification of Rice Quality Through Pattern Classification Using Computer Vision Image Processing Rice is the source of Pakistan agriculture industry and food. For agriculture, industry and the oldest sector in the world use rice for different purpose. There are many challenges in the particular sector such as their analysis. This analysis mostly often related to its texture, color, shape, grain etc. In this study, Vision system used to check the quality of rice using some texture features such as color, shape and characteristics. In this study Computer Vision Image Processing tool applied on three different types of rice. Using this tool we apply pattern classification using nearest neighbor and K-nearest neighbor algorithm. Using these algorithms we get results of three varieties of rice Bastmati, Jasmine and White rice. In both algorithms white rice result show best from Basmati rice and Jasmine rice. White rice result is 93.75 % which is best as quality wise. Other tool also available like as MATLAB, Mazda etc for future more best prediction. Keywords: RST-Invariant features, Histogram features, Texture features, Nearest Neighbor algorithm, K-nearest neighbor algorithm DOI: 10.7176/CEIS/11-2-01 Publication date: February 29 th 2020 Computer science ; k-nearest neighbors algorithm ; Pattern recognition (psychology) ; Artificial intelligence ; Histogram ; White rice ; Nearest neighbour algorithm ; Image processing ; Computer vision ; Image (mathematics) ; Algorithm Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; GABA and Rice Research
Authors: Hülya Demirören | Yeşim Yılmaz
Source: Fırat Üniversitesi Mühendislik Bilimleri Dergisi (article, 2020-02-17)
Field: Materials Science — Metals and Alloys

Biyomalzeme Olarak Kullanılan Titanyum Alaşımının Elektrokimyasal Sentezi Biyomalzeme uygulamalarında kullanılan titanyum ve alaşımları, iyi mekanik özelliklere sahip olmasının yanı sıra yüksek korozyon direnci özelliklerinin nedeni ile tercih edilmektedir. Biyomalzeme olarak kullanılan CP-Ti (Grade 2) ve Ti6Al4V (Grade 5) numuneler 1 saat boyunca 750 oC'ye maruz bırakıldıktan sonra havada soğutulur. 0,5 mol H2S04 + 1 mol HC1 karışık çözeltide analiz edilmiştir. Bu çalışmada bu alaşımların elektrokimyasal davranışları polarizasyon eğrileri elde edilerek incelenmiştir. Isıl işlem ve alaşımlamanın etkisi elektrokimyasal değerler üzerinde belirlendi. Isıl işlemin ve alaşımlamanın titanyumun korozyon direncini artırdığı tespit edilmiştir. Chemistry ; Molecular biology ; Biology Hydrogen embrittlement and corrosion behaviors in metals ; Corrosion Behavior and Inhibition ; Titanium Alloys Microstructure and Properties