jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tedy Juliandhy | Timbul Haryono | Eka Firmansyah | Indra Perdana
Source: International Journal of Engineering and Technology (article, 2018-12-31)
Field: Materials Science — Materials Chemistry

Breakdown Voltage SF6 Versus CF3CHCl2 Gas as Alternative for Gas Insulation Applied Sulfur Hexafluoride Gas is a filling gas in Gas Insulated Switchgear equipment whose existence starts to be limited and reduced in accordance with amendments to the Kyoto Protocol. The utilization of new gas included in the list of recommendations for the Kyoto Protocol enters the implementation and application phases. Dichlorotriflouroethane gas has equivalent capability even better than SF 6 gas so it is feasible to be recommended as a potential gas for SF 6 gas replacement. Experimental HV testing showed the gas capability to withstand breakdown voltage reaching 837 kV and had a technoeconomic value 0.2 times cheaper than SF 6 gas. In the future CF 3 CHCl 2 gas is very feasible and can be recommended as an environmentally friendly gas and is feasible as a potential alternative gas substitute for circuit breaker equipment in substation equipment that uses gas as a substitute for SF 6 gas. Breakdown voltage ; Materials science ; Environmental science ; Voltage ; Engineering ; Electrical engineering High voltage insulation and dielectric phenomena ; Advanced Battery Technologies Research ; Power Transformer Diagnostics and Insulation
Authors: Yuchen He | Sung Ha Kang
Source: arXiv (Cornell University) (preprint, 2018-12-19)
Field: Materials Science — Materials Chemistry

Lattice Identification and Separation: Theory and Algorithm Motivated by lattice mixture identification and grain boundary detection, we present a framework for lattice pattern representation and comparison, and propose an efficient algorithm for lattice separation. We define new scale and shape descriptors, which helps to considerably reduce the size of equivalence classes of lattice bases. These finitely many equivalence relations are fully characterized by modular group theory. We construct the lattice space $\mathscr{L}$ based on the equivalent descriptors and define a metric $d_{\mathscr{L}}$ to accurately quantify the visual similarities and differences between lattices. Furthermore, we introduce the Lattice Identification and Separation Algorithm (LISA), which identifies each lattice patterns from superposed lattices. LISA finds lattice candidates from the high responses in the image spectrum, then sequentially extracts different layers of lattice patterns one by one. Analyzing the frequency components, we reveal the intricate dependency of LISA's performances on particle radius, lattice density, and relative translations. Various numerical experiments are designed to show LISA's robustness against a large number of lattice layers, moiré patterns and missing particles. Lattice (music) ; Algorithm ; Mathematics ; Reciprocal lattice ; Lattice field theory ; Equivalence relation ; Statistical physics ; Pure mathematics ; Physics ; Optics ; Diffraction ; Mathematical physics Machine Learning in Materials Science ; Advanced biosensing and bioanalysis techniques ; Nanopore and Nanochannel Transport Studies
Authors: Patrick Schuenke | RO Floca | CJ Goch | Marco Nolden | M Zaiß | Johannes Windschuh | HN Dang | Carl W David | Roeloffs | Peter Bachert | Mark E. Ladd
Source: Max Planck Digital Library (article, 2018-06-01)
Field: Materials Science — Materials Chemistry

Towards a Routine Clinical Application of Chemical Exchange Sensitive MRI Chemical exchange saturation transfer (CEST) and chemical exchange sensitive spinlock (CESL) were shown to have potential to provide molecular information for diagnosing a wide range of diseases. However, the lack of standardized acquisition protocols and freely available post-processing software prohibited the widespread application of these promising techniques until now. In this work, we present a modularly designed CEST/CESL preparation block that is easy to operate and can be used with arbitrary MRI readouts. Further, we developed and provide a C++ based open-source software that offers many CEST/CESL specific functionalities for the post-processing of the acquired data. Computer science ; Medicine Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Alexandre Néron | Réjean Girard | Jonathan Tremblay | L. Paul Bédard | Kévin Bouchard
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Surfaces, Coatings and Films

Reducing the Learning Population Size for Morphological Classification of Natural Materials: Example of Gold Grains from Backscattered Electron Images An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button. Natural (archaeology) ; Materials science ; Content (measure theory) ; Population ; Electron ; Action (physics) ; Mineralogy ; Physics ; Geography ; Mathematics ; Chemistry ; Nuclear physics ; Demography ; Sociology ; Mathematical analysis Electron and X-Ray Spectroscopy Techniques
Authors: Hazren A. Hamid | Hasnida Harun | Norshuhaila Mohamed Sunar | Faridahanim Ahmad | Latifah Jasmani | Norhidayah Suleiman
Source: International Journal of Engineering & Technology (article, 2018-11-30)
Field: Materials Science — Biomaterials

Predicting the Capability of Oxidized CNW Adsorbents for the Remediation of Copper Under Optimal Operating Conditions Using RSM and ANN Models Metal pollutants such as copper released into the aqueous environment have been increasing as a result of anthropogenic activities. Adsorption-based treatment technologies offer opportunities to remediate metal pollutants from municipal and industrial wastewater effluent. The aim of this work was to evaluate the capability of modified cellulose nanowhisker (CNW) adsorbents for the remediation of copper from water matrices under realistic conditions using response surface methodology (RSM) and artificial neural network (ANN) models. Considerations for design and application to remediate Cu(II) from wastewater by developing a continuous flow experiment are described in this study. However, the physical structure of modified CNW adsorbents renders them unsuitable for use in column operation. Therefore, a more detailed study of the mechanical properties of CNW adsorbents would be necessary in order to improve the strength and stability of the adsorbents. This work has demonstrated that modified CNW are promising adsorbents to remediate copper from water matrices under realistic conditions including wastewater complexity and variability. The use of models to predict the test parameter system and account for matrix variability when evaluating CNW adsorbents for remediating Cu from a real-world wastewater matrix may also provide the foundation for assessing other treatment technologies in the future. Environmental remediation ; Wastewater ; Pollutant ; Adsorption ; Effluent ; Environmental science ; Groundwater remediation ; Sewage treatment ; Copper ; Artificial neural network ; Response surface methodology ; Process engineering ; Computer science ; Environmental engineering ; Materials science ; Contamination ; Engineering ; Chemistry ; Machine learning Advanced Cellulose Research Studies ; Adsorption and biosorption for pollutant removal
Authors: R. R. Lavshchenko | Олексій Водка
Source: Scientific Bulletin of UNFU (article, 2018-12-27)
Field: Materials Science — Materials Chemistry

Розроблення алгоритмів візуалізації властивостей гетерогенних та композиційних матеріалів Сьогодні у людській діяльності використовують дуже велику кількість різних матеріалів. Ці матеріали відрізняться між собою механічними властивостями, кольором, хімічним складом. Широке розмаїття матеріалів становить завдання про збереження інформації про них та про її візуалізацію. Створено базу даних матеріалів та веб-застосунок, який дає можливість отримати доступ до інформації про різні види металів та їхні сплави, а також підібрати найближчі аналоги за допомогою функції інтелектуального пошуку. Для створення бази даних використано систему керування базами даних MySQL. Наповнення цієї бази даних відбувалось способом розроблення спеціальної програми-парсера. Ця програма переглядала сторінки з мережі Інтернет та виділяла інформацію про властивості матеріалів і зберігала їх до бази даних. Для візуалізації даних використано алгоритми зниження розмірності. Ці алгоритми спрямовані на відшукання такої проекції високовимірних даних на низьковимірний простір. Під час використання цієї проекції зберігаються всі внутрішні взаємозв'язки між даними. Це дало змогу побудувати відображення великовимірних даних на площину та візуалізувати їх. Для цього використано алгоритми Isomap, MDS, t-SNE. В такий спосіб розроблено базу даних матеріалів. Доступ до бази даних відбувається за допомогою веб-застосунку. Для зібраних даних побудовано візуалізації. За результатами візуалізації виявлено кластери матеріалів, які відповідають вже відомим класам матеріалів. Це підтверджує коректність побудови моделей візуалізації та зниження розмірності, а також правильність зібраної інформації. Isomap ; Computer science ; Artificial intelligence ; Dimensionality reduction ; Nonlinear dimensionality reduction Material Properties and Failure Mechanisms ; Statistical and Computational Modeling ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: RUSHIKESH ASHTEKAR | PROF. N. S. KULKARNI | VIKRAM NIKAM | AKSHY GITE
Source: Zenodo (CERN European Organization for Nuclear Research) (review, 2018-06-20)
Field: Materials Science — Polymers and Plastics

A Review Of Fatigue And Life Prediction Of Unidirectional Fiber-Reinforced Composite <strong><strong> </strong>A detailed review on fatigue damage of unidirectional fiber composites and life prediction is covered in this paper. In order to summarize and present current work,the detailed work is divided in four parts in order to complete the overall review;fatigue of unidirectional composites,damage mechanism,failure criteria and composite Fatigue life prediction. The review starts with study on factors affecting the fatigue of composites. This is trailed by a fairly broad depiction of the composite and an outline of normally utilized fatigue criteria for expectation. Also,towards the end,models and techniques for weariness and life forecast of composites are condensed and disc ussed.</strong> <strong>https://www.ijiert.org/paper-details?paper_id=141296</strong> Composite number ; Materials science ; Fiber ; Fiber-reinforced composite ; Structural engineering ; Composite material ; Engineering Natural Fiber Reinforced Composites ; Structural Behavior of Reinforced Concrete
Authors: Norberto Feito Sánchez | J. López-Puente | Ana M. Marín Sánchez | María Henar Miguélez Garrido
Source: Revista iberoamericana de ingeniería mecánica. (article, 2018-10-01)
Field: Materials Science — Materials Chemistry

Análisis numérico del proceso de taladrado de materiales compuestos de fibra de carbono para diferentes geometrías de broca Durante los últimos años, el uso de materiales compuestos poliméricos reforzados con fibra ha experimentado un alza considerable en la industria, especialmente en el ámbito aeronáutico. Esto se debe, principalmente, a la excelente relación resistencia-peso, que lo sitúa como unos materiales idóneos capaz de reemplazar a materiales tradicionales como el acero. Una de las operaciones más comunes que se realiza sobre estos materiales es el taladrado de agujeros, especialmente en la producción de grandes estructuras donde la unión de piezas mediante tornillos es inevitable. El presente trabajo se centra en estudiar esta operación, analizando la influencia de la broca tanto en la fuerza de corte como en el daño generado durante el taladrado. Dos geometrías distintas (una convencional y otra escalonada) se han ensayado sobre material polimérico reforzado con fibra de carbono (CFRPs por sus siglas en inglés). Los resultados mostraron la mejora de la calidad de los agujeros en el caso de usar una broca escalonada, pero solo trabajando a bajas velocidades de avance. Con la intención de realizar un estudio paramétrico más profundo, se ha desarrollado un modelo numérico tridimensional. Mediante resultados experimentales, el modelo ha sido validado y utilizado para estudiar la influencia de diversos factores que afectan a la calidad del taladro, como pueden ser el soporte de apoyo del laminado o el espesor del mismo. Humanities ; Art Material Selection and Properties ; Natural Fiber Reinforced Composites ; Engineering and Information Technology
Authors: Nur Ali | Khairiyah Mohd‐Yusof | Mohd Fauzi Othman | R. Latip | Muhammad Saiful Nidzam Ismail
Source: UiTM Institutional Repositories (Universiti Teknologi MARA) (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Adaptive Neuro Fuzzy Inference System (ANFIS) modelling for quality estimation in palm oil refining process / Nur Syuhada Ali ...[et al.] Palm oil refining is a process of removing the unwanted compounds from crude palm oil to produce a refined, bleached and deodorized (RBD) palm oil. It consists of three main processes which are degumming, bleaching and deodorization. In this study, an adaptive neuro-fuzzy inference system was developed to predict the FFA content in the RBD palm oil. The FFA content is non-linearly correlated to the input quality and the operating condition at the refining processes. Feed flow rate, FFA content (input), moisture, IV, phosphoric acid, bleaching earth, bleaching temperature, bleaching vacuum pressure, deodorizer temperature, deodorizer vacuum pressure, heating temperature, sparging steam pressure, and pre-stripper sparging steam were used to build the ANFIS model. Subtractive clustering method was selected for the ANFIS model. The performance of the model was evaluated using RMSE and R2 value. This study demonstrates that ANFIS are useful for estimating the FFA quality at the palm oil refining process. Sparging ; Adaptive neuro fuzzy inference system ; Refining (metallurgy) ; Pulp and paper industry ; Palm oil ; Environmental science ; Raffinate ; Process engineering ; Mathematics ; Chemistry ; Fuzzy logic ; Computer science ; Fuzzy control system ; Chromatography ; Extraction (chemistry) ; Engineering ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Oil Palm Production and Sustainability ; Edible Oils Quality and Analysis
Authors: Yuedong Yang | Jiqing Chen | Fengchong Lan | Wu Zeng | Zhengwei Ma
Source: MATEC Web of Conferences (article, 2018-01-01)
Field: Materials Science — Biomaterials

Constitutive Parameters Identification of AZ31B-H24 Magnesium Alloy and Energy-Absorption Analysis in Structural Panel Use As a novel lightweight material, AZ31B magnesium alloy is considered as the most potential material to instead baseline steel in some automotive parts. However, their structural use is quite limited and so far proper numerical modeling has not been developed to represent magnesium alloy. In present study, the Split Hopkinson Pressure Bar (SHPB) test is utilized to investigate material dynamic mechanism for AZ31B-H24 over a wide range of strain rates from 1389 s -1 to 7296 s -1 . Parametric identification for Johnson-Cook (J-C) constitutive model available in the commercial finite element package LS-DYNA is carried out. Proper parameters are obtained by curve fit using genetic algorithm with experimental results. Constitutive model after parametric identification is applied to automotive outer panels for crashworthiness analysis. Energy absorption with magnesium alloy substituted baseline steel under lightweight 51.18% is obtained and the key problem of thin-walled magnesium alloy applied in automotive structure is advanced. Materials science ; Magnesium alloy ; Constitutive equation ; Split-Hopkinson pressure bar ; Finite element method ; Parametric statistics ; Structural engineering ; Automotive industry ; Magnesium ; Crashworthiness ; Metallurgy ; Parametric model ; Composite material ; Strain rate ; Engineering Magnesium Alloys: Properties and Applications ; Aluminum Alloys Composites Properties ; High-Velocity Impact and Material Behavior
Authors: Ilmari Ahonen
Source: UTUPub (University of Turku) (article, 2018-03-03)
Field: Chemistry — Analytical Chemistry

Statistical methods for the analysis of high-content organotypic cancer cell culture imaging data Organotypic cancer cell cultures combined with modern imaging technology have greatly expanded the possibilities of in vitro cancer research and drug development. In fact, imaging and subsequent image analyses have become a main component for high content screening in early stage drug discovery. The scale of such screening campaigns is rapidly growing, while at the same time, cell cultures become increasingly complex and now also include multicellular organoids in three-dimensional cultures. As a result of these imaging experiments, large amounts of image data are generated, posing ever-increasing demands to the related analysis methodology. In this doctoral thesis, novel and efficient statistical methods are introduced to meet these demands, spanning a variety of research topics in both statistics and machine learning. As a starting point, the preprocessing and segmentation of the image data are described, leading to the statistical analysis of treatment effects through descriptive features of the multicellular structures. A novel flexible finite mixture regression model is introduced in this context to account for the intra-tumor heterogeneity in the cultures. To gain a more direct interpretation for the treatment effects, an unsupervised analysis sequence is proposed leading to the phenotypic grouping of the cell structures. This is achieved by using a selected set of feature principal components as inputs for clustering algorithms. Finally, the problem of global level novelty detection is formulated and tackled with permutation tests. While the feature analysis and clustering approaches deal with very specific applications, the flexible FMR and global level novelty detection methods represent more abstract problems that are inspired by the challenges in image analysis but are not directly motivated by them. The application of all methods is demonstrated with a real cancer culture dataset in the introductory part of this thesis. High-content screening ; Statistical analysis ; Content (measure theory) ; Cancer ; Content analysis ; Cell culture ; Computer science ; Biology ; Cell ; Statistics ; Mathematics ; Genetics ; Sociology Spectroscopy and Chemometric Analyses
Authors: Jessica J. Jowais
Source: Journal of International Crisis and Risk Communication Research (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Predicting Herbivore Induced Phytochemical Shifts in Helianthus using Spectral Reflectance Induced defense responses in plants vary greatly among species, with many species exhibiting strong upregulation of secondary metabolites under attack by herbivores or pathogens. Secondary metabolite responses are most commonly analyzed using nuclear magnetic resonance or mass spectroscopy, though such approaches are costly and time-intensive. This study explores the use of hyperspectral reflectance as a more time- and cost-efficient method of detecting herbivore-induced secondary metabolite responses in plants. A diverse cross-section of wild sunflowers (genus Helianthus) were grown under controlled conditions and challenged with insect herbivory. Hyperspectral reflectance data was collected and analyzed using a principal component analysis in conjuncture with a support vector classification model to detect herbivore-induced versus control plants. The best model had a 93% accuracy rate at predicting whether a sample came from an induced or control plants when using data from all species tested. However, the changes in hyperspectral reflectance under herbivore induction varied greatly across species. Reflectivity ; Herbivore ; Phytochemical ; Biology ; Remote sensing ; Chemistry ; Botany ; Geology ; Physics ; Optics Spectroscopy and Chemometric Analyses
Authors: . .
Source: Current Science (article, 2018-09-01)
Field: Chemistry — Analytical Chemistry

Science Last Fortnight In Sowa Rigpa, herbs, animal parts, and minerals are used as raw materials for medicine. Though research has identified and authenticated many plant and animal parts, investigations on mineral components of Sowa Rigpa are scarce. Geography ; Biology Heavy Metals in Plants ; Phytochemicals and Medicinal Plants ; Pharmacological Effects of Medicinal Plants
Authors: Maurílio Gustavo Nespeca
Source: LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (article, 2018-08-31)
Field: Chemistry — Analytical Chemistry

Aplicação de espectroscopia no infravermelho próximo e análise multivariada para identificação e quantificação de hidrocarbonetos totais do petróleo em solo Submitted by Maurilio Gustavo Nespeca (mauriliogn@hotmail.com) on 2018-08-31T21:01:07Z&#13;\nNo. of bitstreams: 1&#13;\nTESE - MAURILIO G NESPECA.pdf: 12338235 bytes, checksum: 0ffb2ce70bfeb2d88ea11b6f84d923e9 (MD5) Humanities ; Philosophy Spectroscopy and Chemometric Analyses
Authors: Yueqi Zhong
Source: Advances in Social Science, Education and Humanities Research/Advances in social science, education and humanities research (article, 2018-01-01)
Field: Materials Science — Polymers and Plastics

A Case Study on Master Students with the Textile Background in Tackling Fiber Identification Problems The identification of Wool/Cashmere fibers is an extremely challengeable problem since both fibers possess highly similar morphological features. In this research, we monitored two group of master students with the textile background in tackling this specific task. Both groups have no experience on machine vision. Two learning curves, machine learning, and deep learning were randomly distributed to the groups for them to learn. The entire experimental procedure was carried under the same condition, i.e., computing resources, laboratory facilities, working environment, and weekly discussion with an academic advisor. From our observation, higher accuracy has been reached by the group following the path of deep learning. Comparatively, knowledge of image analysis or hand-crafted feature extraction has empowered the students following the path of machine learning with a more fundamental understanding of feature extraction. Identification (biology) ; Textile ; Computer science ; Fiber ; Textile design ; Data science ; Human–computer interaction ; Artificial intelligence ; Visual arts ; History ; Materials science ; Art ; Biology ; Archaeology Textile materials and evaluations