jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lukman Lukman | Diny Dinarti | Ulfah Juniarti Siregar | Maman Turjaman | Sudarsono Sudarsono
Source: Biodiversitas Journal of Biological Diversity (article, 2022-09-23)
Field: Chemistry — Organic Chemistry

Characterization and identification of agarwood-producing plants (Aquilaria spp.) from North Aceh, Indonesia, based on morphological and molecular markers Abstract. Lukman, Dinarti D, Siregar UJ, Turjaman M, Sudarsono. 2022. Characterization and identification of agarwood-producing plants (Aquilaria spp.) from North Aceh, Indonesia, based on morphological and molecular markers. Biodiversitas 23: 4861-4871. Agarwood is one of the non-timber export commodities important as raw materials for bioindustry. There are 26 agarwood-producing plant species in Indonesia belonging to three families (Thymelaeaceae, Euphorbiaceae, and Fabaceae). This study aims to identify the agarwood-producing plant species in North Aceh District, Aceh Province, Indonesia, based on their morphological and molecular characters. The evaluated morphological characteristics include the bark and leaf structures of endemic plants. Molecular characterization was carried out by sequencing of matK, ITS, and trnL-trnF genes. The collected data were analyzed using the appropriate software, such as R software, BlastX, Geneious Prime and MEGA X. The evaluated 66 accessions were clustered into two major groups based on their morphology. Group 1 consisted of 10.61% of the evaluated accessions is identified as Aquilaria beccariana. Group 2 was further classified into two subclusters (Group 2a and 3b). Group 2a consisted of 10,61% of the accessions as A. malaccensis and Group 2b consisted of 78,79% of the accessions as A. microcarpa. All samples are identified as A. malaccensis based on the matK DNA sequences. Meanwhile, Groups 1 are identified as A. beccariana and Group 2a and 2b as A. microcarpa based on the ITS sequences. Based on the trnL-trnF sequences, Groups 1 and 2a was identified as A. malaccensis and Group 2b as A. microcarpa. Agarwood ; Biology ; Thymelaeaceae ; Botany Wood and Agarwood Research ; Identification and Quantification in Food ; Forest Ecology and Conservation
Authors: Rania El-Newashy | H. El-Sayed
Source: Egyptian Journal of Chemistry (article, 2022-08-02)
Field: Materials Science — Polymers and Plastics

Physical Evaluation and CLO3D Simulation of Some Characteristics of Bio-treated Knitted Polyester/Lycra Fabrics The knitted fabrics which are used in the manufacture of sportswear should be fitting to some parts of the body with enough stretch-ability; namely the breast area including the under-arms. Herein, we adopt CLO3D simulation system to assign the proper blending ratio and fabric weight of selected bio-treated knitted polyester/Lycra (PET/L) blended fabric for manufacture of sportswear. Three different blending ratios (96/4, 94/6 and 92/8) with three different fabric weights; light (160 g/m2), medium (200 g/m2), and heavy (250 g/m2) of PET/L knitted fabrics were fabricated. These fabrics were bio-treated with the lipolytic enzyme Lipolase 100L-EX to enhance the fabric hydrophilicity and to reduce the accumulation of electrostatic charge on the fabric surface without severe loss in fabric weight and burst force. Results of this investigation revealed that the light and medium weight bio-treated PET/L (92/8) knitted fabric exhibited the highest hydrophilicity and lowest electrostatic charge; thus they have been selected for evaluation by CLO3D simulation system. The selected bio-treated samples were found to have appropriate fitting (pressure) and stretch-ability at the shoulders, under-arms, and breast areas of a soft bra usually used in some women’s sportswear. Bio-treatment of the said fabric with Lipolase 100L-EX had no significant effect on the fabric thickness and air permeability. The polyester component of the bio-treated PET/L knitted fabrics was found to be dyeable with the cationic dye C.I. Basic Red 18. The scanning electron microscopy revealed no deterioration in bio-treated knitted fabrics which assures that the used lipase enzyme is a benign reagent for activation of the polyester fibre surface. Polyester ; Composite material ; Materials science Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies
Authors: James A. Stewart | Joseph D. Olles | Mitchell Wood
Source: Journal of Applied Physics (article, 2022-03-16)
Field: Materials Science — Materials Chemistry

Elucidating size effects on the yield strength of single-crystal Cu via the Richtmyer–Meshkov instability Capturing the dynamic response of a material under high strain-rate deformation often demands challenging and time consuming experimental effort. While shock hydrodynamic simulation methods can aid in this area, a priori characterizations of the material strength under shock loading and spall failure are needed in order to parameterize constitutive models needed for these computational tools. Moreover, parameterizations of strain-rate-dependent strength models are needed to capture the full suite of Richtmyer–Meshkov instability (RMI) behavior of shock compressed metals, creating an unrealistic demand for these training data solely on experiments. Herein, we sweep a large range of geometric, crystallographic, and shock conditions within molecular dynamics (MD) simulations and demonstrate the breadth of RMI in Cu that can be captured from the atomic scale. Yield strength measurements from jetted and arrested material from a sinusoidal surface perturbation were quantified as YRMI=0.787±0.374 GPa, higher than strain-rate-independent models used in experimentally matched hydrodynamic simulations. Defect-free, single-crystal Cu samples used in MD will overestimate YRMI, but the drastic scale difference between experiment and MD is highlighted by high confidence neighborhood clustering predictions of RMI characterizations, yielding incorrect classifications. Instability ; Spall ; Strain rate ; Richtmyer–Meshkov instability ; Mechanics ; Materials science ; Shock (circulatory) ; Molecular dynamics ; Bauschinger effect ; Deformation (meteorology) ; Statistical physics ; Composite material ; Physics High-Velocity Impact and Material Behavior ; Laser-Plasma Interactions and Diagnostics ; High-pressure geophysics and materials
Authors: Franziska Erlmeier | Na Sun | Jian Shen | Annette Feuchtinger | Achim Buck | Verena M. Prade | Thomas Kunzke | Peter Schraml | Holger Moch | Michael Autenrieth | Wilko Weichert | Arndt Hartmann | Axel Walch
Source: Oncology (article, 2022-10-05)
Field: Chemistry — Spectroscopy

Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging: Diagnostic Pathways and Metabolites for Renal Tumor Entities In summary, we performed a classification system with a mean accuracy in tumor discrimination of 85.13%. Furthermore, we detected tumor-specific biomarkers for the four most common primary renal tumors by MALDI-MSI. This method is a useful tool in differential diagnosis and biomarker detection. Clear cell renal cell carcinoma ; Chemistry ; Cancer research ; Biochemistry ; Biology ; Renal cell carcinoma ; Pathology ; Medicine Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Cancer, Hypoxia, and Metabolism
Authors: Wenjun Fu | Ying Xu | Yan Gao
Source: Computational Intelligence and Neuroscience (article, 2022-05-23)
Field: Materials Science — Materials Chemistry

A Study on Insulation Monitoring Technology of High-Voltage Cables in Underground Coal Mines Based on Decision Tree The insulation state of high-voltage cables in coal mines directly influences the reliability of power supply in coal mines and the level of safe production. In this paper, the degradation mechanism of cable insulation is analyzed, and an online monitoring technology of cable insulation in coal mines based on decision tree is proposed, the technical principle of the judgment method of cable degradation based on decision tree is studied, the feasibility of this technology is verified through simulation, the existing online monitoring solutions for cable insulation are analyzed, and a wide-area synchronous measurement and monitoring system for cable insulation is designed. This technology has been applied in Chinese coal mine enterprises in China and achieved a good effect. Coal mining ; Reliability (semiconductor) ; Coal ; Decision tree ; Power (physics) ; Environmental science ; Power cable ; Automotive engineering ; Degradation (telecommunications) ; Reliability engineering ; Computer science ; Mining engineering ; Engineering ; Waste management ; Electrical engineering ; Materials science High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Power Transformer Diagnostics and Insulation
Authors: Hao Zhou | Cai Chen | Feng Feng | Changsheng Zhou | Wenling Zhang | Wei‐Tao Wu
Source: Gels (article, 2022-12-26)
Field: Materials Science — Polymers and Plastics

Study of Thixotropic Characteristics of a Kerosene Gel Propellant by Bayesian Optimization The rheological behavior of gel propellants is crucial for their practical applications, especially in the rocket engine and ramjet fields. The thixotropic characteristics of gel propellants are an important component of their rheological properties and have a notable impact on their flow and injection process. However, most gel propellants contain rich, dynamic cross-linked network structures, which impart complex non-Newtonian fluid properties, and it is difficult to establish a unified mathematical model. In view of this, this study addresses the thixotropy of a prepared RP-3 kerosene gel and determines the mathematical model and model parameters describing its thixotropy. Experiments show that the kerosene gel exhibits shear-thinning properties as well as thixotropy. To describe the microstructural changes in the gel, three thixotropic constitutive models are introduced to analyze the rheological data, and the constitutive equation parameters are optimized. The three models are all structural dynamic models, which can be used to describe microstructural changes within the material. In addition, the fitting of the constitutive equation is a multiparameter optimization problem, and an appropriate optimization method must be used for parameter fitting. Therefore, the Bayesian optimization method combined with Gaussian process regression and the upper confidence bound (UCB) acquisition function is used in the multiparameter fitting of the constitutive models. Both experiments and numerical results show that the thixotropic model, which introduces a pre-factor with shear strain and assumes that the breakdown of the gel structure is related to energy dissipation rather than the shear rate, has a better fitting effect and prediction ability with regard to the gel. Combined with transient experiments at different shear rates, the model parameters of the constitutive law can be determined quickly by applying the Bayesian optimization method. Thixotropy ; Propellant ; Constitutive equation ; Rheology ; Materials science ; Mechanics ; Shear thinning ; Parametric statistics ; Thermodynamics ; Composite material ; Mathematics ; Finite element method ; Engineering ; Physics ; Statistics ; Aerospace engineering Polymer crystallization and properties ; Rheology and Fluid Dynamics Studies ; Polysaccharides Composition and Applications
Authors: Junjie Hou | Jifeng Wang | Fuquan Yang | Tao Xu
Source: Biophysics Reports (article, 2022-01-01)
Field: Chemistry — Spectroscopy

DIA-MS2pep: a library-free framework for comprehensive peptide identification from data-independent acquisition data Identifying peptides directly from data-independent acquisition (DIA) data remains challenging due to the highly multiplexed MS/MS spectra. Spectral library-based peptide detection is sensitive, but it is limited to the depth of the library and mutes the discovery potential of DIA data. We present here, DIA-MS2pep, a library-free framework for comprehensive peptide identification from DIA data. DIA-MS2pep uses a data-driven algorithm for MS/MS spectrum demultiplexing using the fragments data without the need of a precursor. With a large precursor mass tolerance database search, DIA-MS2pep can identify the peptides and their modified forms. We demonstrate the performance of DIA-MS2pep by comparing it to conventional library-free tools in accuracy and sensitivity of peptide identifications using publicly available DIA datasets of varying samples, including HeLa cell lysates, phosphopeptides, plasma, <i>etc</i>. Compared with data-dependent acquisition-based spectral libraries, spectral libraries built directly from DIA data with DIA-MS2pep improve the accuracy and reproducibility of the quantitative proteome. Identification (biology) ; Peptide ; Computer science ; Multiplexing ; Proteome ; Data acquisition ; Reproducibility ; HeLa ; Data mining ; Chemistry ; Computational biology ; Chromatography ; Biology ; Cell ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Identification and Quantification in Food
Authors: Zhang Jiang | Jin Wang | Matthew V. Tirrell | Juan J. de Pablo | Wei Chen
Source: Journal of Synchrotron Radiation (article, 2022-04-22)
Field: Materials Science — Materials Chemistry

Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis. Hamiltonian MCMC, a state-of-the-art development in the field of MCMC, has become popular in recent years. It utilizes Hamiltonian dynamics for indirect but much more efficient drawings of the model parameters. We described the principle of the Hamiltonian MCMC for inversion problems in X-ray scattering analysis by estimating high-dimensional models for several motivating scenarios in small-angle X-ray scattering, reflectivity, and X-ray fluorescence holography. Hamiltonian MCMC with appropriate preconditioning can deliver superior performance over the random-walk MCMC, and thus can be used as an efficient tool for the statistical analysis of the parameter distributions, as well as model predictions and confidence analysis. Markov chain Monte Carlo ; Hamiltonian (control theory) ; Hybrid Monte Carlo ; Markov chain ; Monte Carlo method ; Estimation theory ; Scattering ; Markov process ; Markov chain mixing time Radiation Shielding Materials Analysis ; Markov Chains and Monte Carlo Methods ; Advanced X-ray Imaging Techniques
Authors: Henri Lösel | Navid Shakiba | Soeren Wenck | Phat Le Tan | Maike Arndt | Stephan Seifert | Thomas Hackl | Markus Fischer
Source: Food Analytical Methods (article, 2022-06-10)
Field: Chemistry — Analytical Chemistry

Impact of Freeze-Drying on the Determination of the Geographical Origin of Almonds (Prunus dulcis Mill.) by Near-Infrared (NIR) Spectroscopy Abstract Near-infrared (NIR) spectroscopy is a proven tool for the determination of food authenticity, mainly because of good classification results and the possibility of industrial use due to its easy and fast application. Since water shows broad absorption bands, the water content of a sample should be as low as possible. Freeze-drying is a commonly used preparatory step for this to reduce the water content in the sample. However, freeze-drying, also known as lyophilization, is very time-consuming impeding the widespread usage of NIR analysis as a rapid method for incoming goods inspections. We used a sample set of 72 almond samples from six economically relevant almond-producing countries to investigate the question of how important lyophilization is to obtain a well-performing classification model. For this approach, the samples were ground and lyophilized for 3 h, 24 h, and 48 h and compared to non-freeze-dried samples. Karl-Fischer titration of non-lyophilized samples showed that water contents ranged from 3.0 to 10.5% and remained constant at 0.36 ± 0.13% after a freeze-drying period of 24 h. The non-freeze-dried samples showed a classification accuracy of 93.9 ± 6.4%, which was in the same range as the samples which were freeze-dried for 3 h (94.2 ± 7.8%), 24 h (92.5 ± 8.7%), and 48 h (95.0 ± 9.0%). Feature selection was performed using the Boruta algorithm, which showed that signals from lipids and proteins are relevant for the origin determination. The presented study showed that samples with low water content, especially nuts, can be analyzed without the time-consuming preparation step of freeze-drying to obtain robust and fast results, which are especially required for incoming goods inspection. Prunus dulcis ; Freeze-drying ; Chemistry ; Near-infrared spectroscopy ; Sample preparation ; Chromatography ; Titration ; Analytical Chemistry (journal) ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Bee Products Chemical Analysis ; Nuts composition and effects
Authors: Man Chen | Youliang Ni | Chengqian Jin | Zheng LIU | Jinshan XU
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Spectral inversion model of the crushing rate of soybean under mechanized harvesting Rapid and timely acquisition of the crushing rate can help in assessing the performance of combine harvesters, which is very important for agricultural production. The spectral reflectance of soybean provides an alternative method to the classical physical and chemical analysis of the crushing rate of soybean in laboratory. Therefore, hyperspectral imaging can be used to rapidly obtain the crushing rate of soybean. In this study, the hyperspectral method was employed, and the application of inter-correlation analysis was explored in the optimization and quantitative analysis of hyperspectral bands. The crushing rate of 130 soybean samples collected from a combine harvester was investigated through physical analysis in the laboratory. Subsequently, the raw hyperspectral reflectance of soybean samples was measured using a spectroradiometer equipped with a high intensity contact probe under darkroom conditions. Next, the raw spectral reflectance (REF) and the logarithmic reciprocal pretreatment spectrum data (LR) were analyzed and compared. The effective wavelengths were selected according to the results of the inter-correlation analysis. Regression models of the crushing rate with different indices were established using a least squares support vector machine (LS-SVM). The inversion results of the model were validated and compared with each other. The experimental results show that sensitive bands from REF are 1061, 1068, 1074, 1090, 2085, 2092, 2095, and 2103 nm. Sensitive bands from LR are 677, 1039, 1078, 1093, 1101, 1956, 2088, and 2107 nm. The results showed that REF was the optimal spectral index in the LS-SVM regression model (Rc2 was 0.939, and Rp2 was 0.915). The inter-correlation analysis method could not only support efficient selection of hyperspectral bands, but also retain the original sample information. The REF hyperspectral inversion model based on LS-SVM can realize rapid on-line monitoring of the performance (crushing rate) of grain combine harvesters in the future. Hyperspectral imaging ; Spectroradiometer ; Reflectivity ; Support vector machine ; Remote sensing ; Partial least squares regression ; Environmental science ; Inversion (geology) ; Mathematics ; Biological system ; Computer science ; Statistics ; Optics ; Geology ; Artificial intelligence ; Biology ; Physics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Smart Agriculture and AI
Authors: Carmine Zuccarini | Karthikeyan Ramachandran | S. Lo Russo | Yasith C. Jayakody | D.D. Jayaseelan
Source: International Journal of Ceramic Engineering & Science (article, 2022-11-12)
Field: Materials Science — Ceramics and Composites

Mathematical modeling and simulation of porosity on thermomechanical properties of UHTCs under hypersonic conditions Abstract Ultrahigh temperature ceramics (UHTCs) were analyzed for their suitability in hypersonic flight conditions using balanced heat equations, transport equation, and finite element modeling technique. Mathematical model was derived on the assumption that the induced porosity follows linear and parabolic solutions of Laplace equation and applied external load mimicking hypersonic conditions with critical heat flux ranging between 7 and 44 MW/m 2 . Simulations were carried out with four different UHTCs combinations and the results outlined a temperature rise exceeding 4700°C with deformation observed on the fixed area and where the heat flux was generated. The influence of porosity had a greater impact on the performance of the material as it led to a reduction in deformation compared to dense samples. Porous UHTCs exhibited a good thermal shock resistance owing to the release of thermal stresses through pores, which also enhanced the thermal insulation of the structure. Porosity ; Materials science ; Thermal shock ; Heat flux ; Mechanics ; Heat transfer ; Deformation (meteorology) ; Finite element method ; Hypersonic speed ; Composite material ; Laplace transform ; Thermodynamics ; Mathematics ; Mathematical analysis ; Physics Advanced ceramic materials synthesis ; Thermal properties of materials ; Advanced materials and composites
Authors: Halil Şenol | Ayhan Kara | Selçuk ATASOY | Mehtap Erşan
Source: Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi (article, 2022-05-26)
Field: Materials Science — Materials Chemistry

Anaerobik Sindirimde Nanopartikül Konsantrasyonunun Cevap Yüzey Yöntemi İle Optimizasyonu Son zamanlarda nanopartiküllerin (NP)’lerin anaerobik sindirim (AS)’de biyogaz üretimi üzerinde verim artırmaya yönelik etkilerinin olduğu keşfedilmiştir. Bu çalışmada Fe3O4, ZnO ve SiO2 NP’lerin AS’ye olan etkileri incelenmiştir. Bazı NP’lerin yüksek konsantrasyonları toksik etki yapmaktadır. Bu nedenle substrat olarak kullanılan sığır gübresinin AS’de en iyi NP konsantrasyonlarını bulmak için Cevap yüzey yöntemi (CYY)’nin Box-Benkhen Tasarımı kullanılmıştır. CYY seçilen bir aralıktaki birkaç deney setine dayalı olarak işletim değişkenlerinden etkilenen yanıt yüzeyini en üst düzeye çıkaran değerli bir istatistiksel araçtır. Sonuç olarak bağımsız değişkenler için en iyi NP konsantrasyon değerleri SiO2 için 150 mg/l, Fe3O4 için 150 mg/l ve ZnO için 150 mg/l değerinde bulunmuştur. NP eklenmeden önceki biyogaz verimi 290 ml/g uçucu katı (UK) değerinde iken bağımsız değişkenlerin optimum koşullarında 320 ml/g UK değerinde tahmin edilmiştir. Varyans analizi ve yüksek regresyon katsayısı (%98), regresyon modeliyle deneysel değerlerin model tarafından iyi bir şekilde tahmin edildiğini doğrulamaktadır. Böylece gelecek çalışmalarda farklı NP’lerin AS’de etkilerinin birlikte incelenmesi önerilmektedir. Physics ; Mathematics ; Chemistry ; Molecular biology ; Biology Nanoparticles: synthesis and applications ; Phytochemicals and Medicinal Plants ; Essential Oils and Antimicrobial Activity