jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: G Suresh Babu | V. Rama Krishna | V Dharma Teja | Surbhi Yadav
Source: International Journal of Engineering & Technology (article, 2018-04-18)
Field: Chemistry — Analytical Chemistry

Milk quality testing using intelligent inference performance evaluation system integrated with IoT One of the major used food item in day to day life is milk. Many large-scale industries are in the distribution of milk products. Quality of milk is one of the major factor in the food processing system and customers appreciate quality products. IoT is revolution and it is using extensively in our day to day life. Our project is about maintaining the quality of the milk as it’s a perishable product. In this paper we concentrated on how the milk is depending on the different factors available in it and each one effects the quality. An attempt is made to analyze the data from the sensors with IoT used in the milk production with the help of Artificial Neural Network (ANN). The results are exhibited through an example. Internet of Things ; Quality (philosophy) ; Product (mathematics) ; Computer science ; Production (economics) ; Embedded system ; Mathematics Spectroscopy and Chemometric Analyses ; Food Supply Chain Traceability ; Advanced Chemical Sensor Technologies
Authors: Nikhil Kalathil | John Byrnes | Lucien Randazzese | Daragh P. Hartnett | Christina Freyman
Source: Frontiers in Research Metrics and Analytics (article, 2018-01-28)
Field: Materials Science — Materials Chemistry

Application of Text Analytics to Extract and Analyze Material–Application Pairs from a Large Scientific Corpus When assessing the importance of materials (or other components) to a given set of applications, machine analysis of a very large corpus of scientific abstracts can provide an analyst a base of insights to develop further. The use of text analytics reduces the time required to conduct an evaluation, while allowing analysts to experiment with a multitude of different hypotheses. Because the scope and quantity of metadata analyzed can, and should, be large, any divergence from what a human analyst determines and what the text analysis shows provides a prompt for the human analyst to reassess any preliminary findings. In this work, we have successfully extracted material-application pairs and ranked them on their importance. This method provides a novel way to map scientific advances in a particular material to the application for which it is used. Approximately 438,000 titles and abstracts of scientific papers published from 1992 to 2011 were used to examine sixteen materials. This analysis used co-clustering text analysis to associate individual materials with specific clean energy applications, evaluate the importance of materials to specific applications, and assess their importance to clean energy overall. Our analysis reproduced the judgements of experts in assigning material importance to applications. The validated methods were then used to map the replacement of one material with another material in a specific application (batteries). Computer science ; Data science ; Metadata ; Set (abstract data type) ; Analytics ; Scope (computer science) ; Cluster analysis ; Scientific literature ; Information retrieval ; World Wide Web ; Artificial intelligence Machine Learning in Materials Science ; Topic Modeling
Authors: S Akbey | Philipp Ehses | Roland Stirnberg | M Zaiß | Tony Stöcker
Source: MPG.PuRe (Max Planck Society) (article, 2018-06-01)
Field: Materials Science — Materials Chemistry

Single-shot whole-brain CEST imaging using centric-reordered 3D-EPI We present a 3D CEST sequence that allows 2mm isotropic whole-brain acquisition within 6s per frequency offset. The 4.5s CEST preparation is followed by a 1.5s centric-reordered 3D-EPI readout with water excitation. The single-shot readout improves robustness against physiological noise and provides complete freedom in the design of the saturation block. We acquired whole-brain CEST data at 7T and show metabolite maps obtained from a Lorentzian fit to the Z-spectra. Single shot ; Computer science ; Neuroimaging ; Artificial intelligence ; Pattern recognition (psychology) ; Physics ; Psychology ; Optics ; Neuroscience Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Medical Imaging Techniques and Applications
Authors: Lucía Trilla‐Fuertes | Andrea Zapater‐Moros | Angelo Gámez‐Pozo | Jorge M. Arevalillo | Guillermo Prado-Vázquez | Mariana Díaz‐Almirón | María Ferrer-Gómez | Rocío López‐Vacas | Hilario Navarro | Enrique Espinosa | Paloma Maı́n | Juan Ángel Fresno Vara
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-05-10)
Field: Chemistry — Spectroscopy

Bayesian Networks established functional differences between breast cancer subtypes Abstract Breast cancer is a heterogeneous disease. In clinical practice, tumors are classified as hormonal receptor positive, Her2 positive and triple negative tumors. In previous works, our group defined a new hormonal receptor positive subgroup, the TN-like subtype, which has a prognosis and a molecular profile more similar to triple negative tumors. In this study, proteomics and Bayesian networks were used to characterize protein relationships in 106 breast tumor samples. Components obtained by these methods had a clear functional structure. The analysis of these components suggested differences in processes such as metastasis or proliferation between breast cancer subtypes, including our new subtype TN-like. In addition, one of the components, mainly related with metastasis, had prognostic value in this cohort. Functional approaches allow to build hypotheses about regulatory mechanisms and to establish new relationships among proteins in the breast cancer context. Author Summary Breast cancer classification in the clinical practice is defined by three biomarkers (estrogen receptor, progesterone receptor and HER2) into hormone receptor positive, HER2+ and triple negative breast cancer (TNBC). Our group recently described a new ER+ subtype with molecular characteristics and prognosis similar to TNBC. In this study we propose a mathematical method, the Bayesian networks, as a useful tool to study protein interactions and differential biological processes in breast cancer subtypes, characterizing differences in relevant processes such as proliferation or metastasis and associated them with patient prognosis. Breast cancer ; Context (archaeology) ; Progesterone receptor ; Cancer ; Oncology ; Metastasis ; Estrogen receptor ; Triple-negative breast cancer ; Internal medicine ; Medicine ; Biology ; Cancer research ; Bioinformatics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Computational Drug Discovery Methods
Authors: Yasin Turanlı | Füsun Acartürk
Source: Journal of Literature Pharmacy Sciences (article, 2018-01-01)
Field: Materials Science — Biomaterials

Nanofibers and Applications as Colon Specific Drug Delivery System Nanoteknoloji birçok alanda olduğu gibi farmasötik teknolojide de büyük ilerlemeler sağlamıştır. Nanoteknoloji ile geliştirilen yeni ilaçlar zamanla konvansiyonel ilaçların yerini almaktadır. Geliştirilen üretim yöntemleriyle elde edilen yeni ilaçların vücutta belirli bölgelere hedefleme etkinliği artırılmakta; salım bölgesi, zamanı ve oranı belirlenebilmektedir. Böylece ilacın dozu ve buna bağlı olarak da ilacın yan etkisi azalmaktadır. Ayrıca, ilacın kan konsantrasyonunda meydana gelen dalgalanmalar ve ilaç molekülünün etki bölgesinden önce zarar görüp etkisiz duruma gelmesi engellenmektedir. Hasta uyuncunun en yüksek olduğu ilaç uygulama yolu oral yoldur. Bu nedenle ilaçların büyük çoğunluğu oral yoldan kullanılabilecek şekilde geliştirilmeye çalışılmaktadır. Ancak, ilaçların oral yoldan kullanılmasında bazı problemlerle karşılaşılmaktadır. Örneğin; bazı ilaçlar mide asidine, mide-barsak kanalındaki enzimlere karşı dayanıksızdır veya emilim problemi bulunmaktadır. Kolon, gastrointestinal sistemde ilaç hedeflendirilmesi için en uygun bölgelerden biridir. Çünkü kolonda ilaçların kalış süresi uzundur. Ayrıca kolon, sahip olduğu geniş yüzey alanı ve enzim aktivitesinin gastrointestinal sistemin diğer bölgelerine oranla daha düşük olmasından dolayı ilaç hedeflendirilmesi için oldukça avantajlıdır. Elektro-çekim yöntemiyle hazırlanmış nanolifler ilaç taşıyıcı sistem olarak başarılı sonuçlar vermektedir. Doğal veya sentetik çeşitli polimerlerin ve etken maddelerin uygun çözücüde çözülmesiyle elde edilen çözeltinin yüksek voltaj uygulanarak lif hâline getirilmesi esasına dayanan elektro-çekim yöntemi, kolona özgü ilaç taşıyıcı sistem hazırlanmasında da kullanılabilmektedir. Ancak, bu konuda yapılan çalışmaların az olması ve bu çalışmalarda in-vivo çalışmaların olmaması büyük bir eksikliktir. Gelecekte araştırmacıların bu konu üzerinde daha fazla yoğunlaşması gerekmektedir. Molecular biology ; Gynecology ; Medicine ; Chemistry ; Biology Electrospun Nanofibers in Biomedical Applications
Authors: Gür Emre Güraksın | Harun Uğuz
Source: International Journal of Computational and Experimental Science and Engineering (article, 2018-03-15)
Field: Chemistry — Analytical Chemistry

Comparison of Different Training Data Reduction Approaches for Fast Support Vector Machines Based on Principal Component Analysis and Distance Based Measurements Support vector machine is a supervised learning algorithm, which is recommended for classification and nonlinear function approaches. Support vector machines require remarkable amount of memory with time consuming process for large data sets in the training process. The main reason for this is the solving a constrained quadratic programming problem within the algorithm. In this paper, we proposed three approaches for identifying the non-critical points in training set and remove these non-critical points from the original training set for speeding up the training process of support vector machine. For this purpose, we used principal component analysis, Mahalanobis distance and Euclidean distance based measurements for the elimination of non-critical training instances in the training set. We compared the proposed methods in terms of computational time and classification accuracy between each other and conventional support vector machine. Our experimental results show that principal component analysis and Mahalanobis distance based proposed methods have positive effects on computational time without degrading the classification results than the Euclidean distance based proposed method and conventional support vector machine. Mahalanobis distance ; Support vector machine ; Principal component analysis ; Euclidean distance ; Computer science ; Artificial intelligence ; Relevance vector machine ; Pattern recognition (psychology) ; Process (computing) ; Set (abstract data type) ; Quadratic programming ; Machine learning ; Data mining ; Mathematics ; Mathematical optimization Spectroscopy and Chemometric Analyses ; Advanced Algorithms and Applications ; Face and Expression Recognition
Authors: Abubakar Dabet | Hiroomi Homma | Hiroki Homma | Suardi
Source: Mechanical Engineering Journal (article, 2018-01-01)
Field: Materials Science — Polymers and Plastics

Statistical approach to tensile strength of abaca single fiber Related to the importance of selectivity to natural fibers that can be used and qualify as one of the raw material composite engineering substitute for Fiber Reinforced Plastics (FRP) or Fiber Reinforced Metals (FRM), one plants that have the potential of fiber and volume growth is very abundant, namely abaca. This research aims to clarify scattering in tensile strength of an abaca single fiber through statistical approach and to search a way of suppression in the scatter with intention that abaca fibers can be used as a raw material for engineering structural components. Tensile test specimens were prepared from fiber samples from two different areas, East Aceh and North Aceh, Indonesia. Specimen gauge length is 25 mm, then as the holder of a fiber made of paper (20mm x 100mm), where the specimen size for fiber tensile test in accordance with JIS standard K-760. Diameter the specimen fibers obtained varied from 0.060 mm to 0.140 mm. The tensile strength of abaca fiber varies in the wide range from 100 MPa to 900 MPa. Coefficient of variation was calculated for East Aceh abaca fibre 0.32 and North Aceh abaca fibre 0.35. It was examined whether Weibull distribution or log-normal distribution could well express scatted experimental results. The results showed that both the distribution types could well express the experimental probabilty density, but log-normal distribution could be more rational for expression of biologial and chronological effects. To reduce scattering of tensile strength, pre-screening concept was proposed. Ultimate tensile strength ; Materials science ; Fiber ; Composite material ; Weibull distribution ; Natural fiber ; Synthetic fiber ; Tensile testing ; Raw material ; Mathematics Natural Fiber Reinforced Composites ; Textile materials and evaluations ; Leaf Properties and Growth Measurement
Authors: Hamed Abbasi | Ali Balooch | Majid Nazeri
Source:  (article, 2018-02-22)
Field: Chemistry — Analytical Chemistry

Implementation of webcam-based hyperspectral imaging system In the present work, a hyperspectral imaging system (imaging spectrometer) using a commercial webcam has been designed and developed. This system was able to capture two-dimensional spectra (in emission, transmission and reflection modes) directly from the scene in the desired wavelengths. Imaging of the object is done directly by linear sweep (pushbroom method). To do so, the spectrometer is equipped with a suitable collecting lens and a linear travel stage. A 1920 x 1080 pixel CMOS webcam was used as a detector. The spectrometer has been calibrated by the reference spectral lines of standard lamps. The spectral resolution of this system was about 2nm and its spatial resolution was about 1 mm for a 10 cm long object. The hardware solution is based on data acquisition working on the USB platform and controlled by a LabVIEW program. In this system, the initial output was a three-dimensional matrix in which two dimensions of the matrix were related to the spatial information of the object and the third dimension was the spectrum of any point of the object. Finally, the images in different wavelengths were created by reforming the data of the matrix. The free spectral range (FSR) of the system was 400 to 1100 nm. The system was successfully tested for some applications, such as plasma diagnosis as well as applications in food and agriculture sciences. Hyperspectral imaging ; Computer science ; Spectrometer ; Pixel ; USB ; Spectral resolution ; Spectral imaging ; Image resolution ; Imaging spectrometer ; Full spectral imaging ; Detector ; Optics ; Computer vision ; Transmission (telecommunications) ; Artificial intelligence ; Remote sensing ; Physics ; Telecommunications ; Spectral line ; Geology Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Water Quality Monitoring and Analysis
Authors: N. Gokarneshan
Source: Latest Trends in Textile and Fashion Designing (article, 2018-01-24)
Field: Materials Science — Polymers and Plastics

Some Significant Advances in Yarn Splicing Technology The article reviews some of the significant researches in the yarn splicing technology. The effect of important factors on the breaking force of wet spliced yarns has been studied by means of a central composite design, which is a statistical tool. The impact of vent pressure on the quality of yarn splicing when twisting and untwisting has been investigated. Modelling, analysis, and simulation of the air splice is done with the integration of two software's, so as to analyse the flow field and obtain the effect of speed and pressure of the inside the splicing chamber when changing the speed and the pressure while maintaining the diameter of the splicing, the vent hole diameter and the relative angle unaltered. The influence of cotton/polyester fibre blend ratios on spliced portion diameter at various splicing air pressures has been studied. Studies have been directed regarding the influence of various yarn splicing parameters on the strength, elongation and the appearance of spliced cotton/flax yarn. A number of independent variables have been considered. A half factorial experimental design has been used with two levels of each variable. The design and analysis of experiments have been achieved with a specific software. Yarn ; RNA splicing ; Computer science ; Computational biology ; Nanotechnology ; Materials science ; Biology ; Composite material ; Genetics ; Gene ; RNA Textile materials and evaluations ; Mechanical stress and fatigue analysis
Authors: Edgar López–Martínez | Octavio Vázquez–Gómez | Héctor Javier Vergara–Hernández | B. Campillo
Source:  (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Archives of Metallurgy and Materials Materials science ; Cracking ; Metallurgy ; Hydrogen ; Thermal ; Materials processing ; Industrial chemistry ; Composite material ; Thermodynamics ; Process engineering ; Chemistry Material Properties and Failure Mechanisms ; Hydrogen embrittlement and corrosion behaviors in metals ; Microstructure and Mechanical Properties of Steels
Authors: Memik Bünyamin Üzümcü | Hüseyin Kadoğlu
Source: TEKSTİL VE KONFEKSİYON (article, 2018-10-01)
Field: Materials Science — Polymers and Plastics

ESTIMATION OF TENSILE STRENGTH AND UNEVENNESS OF COMPACT-SPUN YARNS BY USING HVI FIBER PROPERTIES Compact spinning system, which has begun to gain an important place in textile industry, thanks to its desired yarn characteristics, was developed in the early 2000s.&amp;nbsp; Less hairy yarns can especially be produced with this system, as stated in the literature. Moreover, the system has significant advantages in terms of tensile strength. In this study, yarns were produced with different yarn counts (Ne 40 - Ne 90) and different twist coefficients (αe 3.8, αe 4.2 and αe 4.6) using the compact spinning system. Regression analysis was carried out using the test results of the yarns produced and HVI fiber properties which were measured before the production. It was investigated whether the properties of the yarns can be estimated before production by using specified fiber properties. As a result of the analysis, the derived equations were used to estimate tensile strength and unevenness values of the yarns.&amp;nbsp; Yarn ; Spinning ; Ultimate tensile strength ; Fiber ; Composite material ; Materials science ; Twist ; Textile ; Tensile testing ; Mathematics ; Geometry Textile materials and evaluations ; Mechanical Engineering and Vibrations Research ; Ergonomics and Musculoskeletal Disorders
Authors: Farzad Azadshahraki | Bahareh Jamshidi | Vali Rasooli Sharabiani
Source: Yüzüncü Yıl Üniversitesi Tarım Bilimleri Dergisi (article, 2018-12-31)
Field: Chemistry — Analytical Chemistry

Non-destructive determination of vitamin C and lycopene contents of intact cv. Newton tomatoes using NIR spectroscopy Lycopene and vitamin C are two vital compositions of tomatoes. Analytical quantification of these components using common destructive methods is expensive and time consuming. In this study, the feasibility of using near-infrared (NIR) spectroscopy at the range of 930-1650nm was assessed to measure the lycopene and vitamin C contents of intact cv. Newton tomatoes. To develop prediction models based on spectral data and analytical measurements achieved using common destructive methods, partial least squares (PLS) regression was utilized. Before modeling, some pre-processing techniques were also used to reduce the irrelevant data from the spectra. The prediction accuracy of the models was evaluated using root mean square error of cross validation (RMSECV), correlation coefficient (rcv) and residual predictive deviation (RPD). The best prediction models had RMSECV of 2.256 µg g-1 and 1.087 mg 100g-1, rcv of 0.840 and 0.818, and RPD of 1.835 and 1.701 for lycopene and vitamin C contents, respectively. Results indicated that NIR spectroscopy can predict the lycopene and vitamin C contents of tomato non-destructively with good and fair accuracy, respectively. Lycopene ; Partial least squares regression ; Correlation coefficient ; Coefficient of determination ; Near-infrared spectroscopy ; Residual ; Chemistry ; Mathematics ; Mean squared error ; Linear regression ; Chromatography ; Analytical Chemistry (journal) ; Carotenoid ; Food science ; Statistics ; Biology ; Algorithm Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity ; Water Quality Monitoring and Analysis
Authors: Mohammad Wafaa | I. Nassar | Abdel-Salam Khalid | Ahmed Attia | Ahmed Abdelhalim | Ahmad A. Mohamad | Rady Said | Ahmed M. Fathy | Rady Fathy | Ayman Gaber | A Gaber | N Ali | N Abdelwahab | H El-Fatatry | W Osman | M Nassar | K Attia | A Abouserie | R Said | Abdel-Kareem Rf | R Brereton | A Yehia | H Mohamed | P Armitage | G Berry
Source: International journal of advanced research in chemical sciences (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

UV Spectrophotometric Determination of Allopurinol and Benzbromarone in their Binary Mixture using Artificial Neural Networks and Genetic Algorithm- Artificial Neural Networks Allopurinol (ALP), figure (1), is (1, 5-Dihydro-4H-Pyrazolo [3, 4-d] pyrimidin-4-one). (1) It is used in gout and hyperuricemia to inhibit the enzyme xanthine oxidase, thus preventing the oxidation of hypoxanthine to xanthine and xanthine to uric acid resulting in the reduction of urate and uric acid concentrations in plasma and urine. enzbromarone (BENZ), figure (2), is (3, 5-dibromo-4-hydroxyphenyl)-(2-ethyl-3-benzofuranyl) methanone. (1) It is a uricosuric drug that reduces plasma concentrations of uric acid by blocking renal tubular reabsorption. ombination of ALP and BENZ has the advantages of greater therapeutic effect than with either drug alone. This combination causes manifold reduction in uric acid concentrations in plasma and urine as compared to double dose of the individual drug when used alone. Also, this combination helps to decrease the dose of each active ingredient, and as a result, decreases the side effects of each of component if given separately in high doses. eviewing the literature in hand, only four reports have been published for determination of the studied mixture, the first and second reports manipulated UV spectrophotometric methods. The third and fourth reports manipulated TLC-densitometric and RP-HPLC methods. he developed work aimed to develop and validate simple and sensitive chemometric assisted spectrophotometric methods for the simultaneous determination of ALP and BENZ in powdered forms, laboratory prepared mixtures and in pharmaceutical formulation namely, artificial neural networks and genetic algorithm artificial neural networks. The proposed methods have been optimized and validated as per the International Conference on Harmonization (ICH) guidelines ICH, and were found to comply with the acceptance criteria. gure3. Structural formula of ALP Abstract: Chemometric assisted spectrophotometric models were suggested for the selective quantitative determination of allopurinol and benzbromarone without previous separation. Multivariate artificial neural networks and genetic algorithm artificial neural networks were developed. The proposed methods were validated and successfully applied for the determination of the drugs in their commercial preparation. Artificial neural network ; Allopurinol ; Benzbromarone ; Binary number ; Genetic algorithm ; Computer science ; Artificial intelligence ; Artificial Sweetener ; Algorithm ; Pattern recognition (psychology) ; Mathematics ; Machine learning ; Chemistry ; Hyperuricemia ; Uric acid Analytical Methods in Pharmaceuticals