jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mihail Douhaniaris
Source: Aaltodoc (Aalto University) (article, 2019-10-22)
Field: Materials Science — Polymers and Plastics

Fully convolutional networks for segmentation of wearable sensor data Wearable sensor-based activity recognition is an area of pattern recognition dealing with detecting the actions and activities of a human agent using motion sensors worn or incorporated on the agent's body. Current state-of-the-art methods use a sliding window approach to partition the sensor signals into smaller fixed size windows which are then classified into activities by a deep neural network. However, this arbitrary partitioning gives rise to the so-called multiclass window problem where the partitioned window contains data from multiple activities which can result in incorrect classifications and missed activities, particularly when trying to detect sporadic activities which are irregularly occurring and short in duration. \n\nIn this work, we propose a novel approach for wearable sensor-based activity recognition based on fully convolutional networks. Our model, which we coin SensorFCN, automatically segments a motion sensor signal stream of arbitrary length into activities by dense samplewise classification. Because of this, our approach is unaffected by the multiclass window problem and the model can precisely detect sporadic activities. A public activity recognition dataset consisting of motion and orientation sensor data originating from 67 subjects performing 11 different activities is used to train and validate the proposed model. A series of experiments is performed in order to find the optimal model configuration which achieves an overall sample accuracy of 96.6%. In addition, we perform occlusion sensitivity analysis in order to qualitatively measure our model's robustness to perturbations in the input signals and to better understand the model's predictions. Our work shows that fully convolutional networks are a promising family of models for wearable sensor-based activity recognition and are effective in overcoming the multiclass window problem. Computer science ; Segmentation ; Wearable computer ; Artificial intelligence ; Computer vision ; Convolutional neural network ; Embedded system Textile materials and evaluations ; Context-Aware Activity Recognition Systems
Authors: Adeyemi Adegbenjo
Source: eScholarship@McGill (McGill) (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Non-destructive assessment of chicken egg fertility using hyperspectral imaging technique You are all acknowledged for your encouragement, helpful comments, and supports.I must but appreciate my spiritual family including the youth group and the entire members of the Redemption Bible Church, Montreal QC, CA Hyperspectral imaging ; Environmental science ; Remote sensing ; Biology ; Artificial intelligence ; Computer science ; Geography Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality
Authors: Boas Pucker
Source: PUB – Publications at Bielefeld University (Bielefeld University) (article, 2019-01-01)
Field: Materials Science — Biomaterials

De novo Nd-1 genome assembly reveals genomic diversity of Arabidopsis thaliana and facilitates genome-wide non-canonical splice site analysis across plant species Pucker B. &lt;em&gt;De novo Nd-1 genome assembly reveals genomic diversity of Arabidopsis thaliana and facilitates genome-wide non-canonical splice site analysis across plant species&lt;/em&gt;. Bielefeld: Universität Bielefeld; 2019. Genome ; Arabidopsis thaliana ; Biology ; splice ; Genetics ; Computational biology ; Evolutionary biology ; Gene Diatoms and Algae Research ; Genomics and Phylogenetic Studies ; Plant Molecular Biology Research
Authors: Lisa Andina | Revita Saputri | Aristha Novyra Putri | Endang Lukitaningsih | Abdul Rohman
Source: Journal of Food and Pharmaceutical Sciences (article, 2019-11-29)
Field: Chemistry — Analytical Chemistry

Analysis of Adulterated Pangasius Hypopthalmus Oil by ATR-FTIR Spectroscopy and Chemometric In this recent study, ATR-FTIR spectroscopy and chemometrics have been successfully used for theclassification and quantitative analysis of adulterated Pangasius Hypopthalmus (P. hypopthalmus) oil. The aimof this research was to evaluate the ability of ATR-FTIR spectroscopy and chemometric to perform theclassification and quantitative analysis of adulterated P. hypopthalmus oil in a binary mixture with palm oil(PO) and coconut oil (CO). In the development of FTIR spectroscopy combined with chemometrics for theclassification and quantitative analysis of P. hypopthalmus oil, P. hypopthalmus oil (MP and LFP) mixed withother oils such as coconut oil (CO) and palm oil (PO) at concentrations of 1-99% v/v. Classification of P.hypopthalmus oil, PO and CO were performed by the principal component analysis (PCA) and thequantification analysis was carried out by partial least square (PLS). Based on the optimization process, thebest classification results were obtained using the first derivative spectra at wave numbers of 1400-1100 cm-1.The prediction of percentage adulterated oil by PLS method also showed very good values of R2 greater than0.9999 and low standard error values in the range of 0.0176-0.703. The prediction was also perform at1400-1100 cm-1 wavenumbers using the first derivative spectra. Chemometrics ; Fourier transform infrared spectroscopy ; Partial least squares regression ; Chemistry ; Principal component analysis ; Chromatography ; Palm oil ; Analytical Chemistry (journal) ; Food science ; Mathematics Spectroscopy and Chemometric Analyses
Authors: Davide Sala | Linda Cerofolini | Marco Fragai | Andrea Giachetti | Claudio Luchinat | Antonio Rosato
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-07-30)
Field: Chemistry — Spectroscopy

A protocol to automatically calculate homo-oligomeric protein structures through the integration of evolutionary constraints and ambiguous contacts derived from solid- or solution-state NMR ABSTRACT Protein assemblies are involved in many important biological processes. Solid-state NMR (SSNMR) spectroscopy is a technique suitable for the structural characterization of samples with high molecular weight and thus can be applied to such assemblies. A significant bottleneck in terms of both effort and time required is the manual identification of unambiguous intermolecular contacts. This is particularly challenging for homo-oligomeric complexes, where simple uniform labeling may not be effective. We tackled this challenge by exploiting coevolution analysis to extract information on homo-oligomeric interfaces from NMR-derived ambiguous contacts. After removing the evolutionary couplings (ECs) that are already satisfied by the 3D structure of the monomer, the predicted ECs are matched with the automatically generated list of experimental contacts. This approach provides a selection of potential interface residues that is used directly in monomer-monomer docking calculations. We validated the protocol on tetrameric L-asparaginase II and dimeric Sod1. Monomer ; Bottleneck ; Nuclear magnetic resonance spectroscopy ; Coevolution ; Chemistry ; Chemical shift ; Intermolecular force ; Biological system ; Computer science ; Computational chemistry ; Materials science ; Polymer ; Molecule ; Stereochemistry ; Biology ; Organic chemistry Advanced NMR Techniques and Applications ; Advanced MRI Techniques and Applications ; Solid-state spectroscopy and crystallography
Authors: Р. Романцов | R. Romancov | Инна Серых | E. V. Chernysheva
Source: Bulletin of Belgorod State Technological University named after V G Shukhov (article, 2019-08-06)
Field: Materials Science — Materials Chemistry

APPLICATION OF PLASMA SILICATION METHOD TO WEAR RESISTANCE OF THE PART Modern technologies are the most important component for any state. Today, advanced technologies allow to create any mechanisms at the level of atoms and molecules. For the production of machines, aggregates and their individual components, new nanomaterials and nanotechnologies are used, which reduce friction repeatedly and with high efficiency, protect parts from damage, save energy and increase the reliability of machine parts as a whole. Virtually in any mechanism, some parts focus on the main load. In this study, such a detail is the steel clamping collet 65G. A method of plasma siliconizing is proposed for hardening its inner surface. The raise of this characteristics will allow to increase its service life, and therefore will ensure more reliable operation of both a separate mechanism and production as a whole. This allows the enterprise to become cost-effective and competitive. In this paper, the magnitude of the effect of the silicon atoms introduction into the surface layer of a part on wear resistance and durability is investigated. Research and subsequent processing of the results using Statistica software for statistical analysis shows an increase in the strength characteristics by 2.6 times. Clamping ; Durability ; Wear resistance ; Reliability (semiconductor) ; Service life ; Computer science ; Mechanism (biology) ; Component (thermodynamics) ; Production (economics) ; Hardening (computing) ; Materials science ; Reliability engineering ; Mechanical engineering ; Layer (electronics) ; Engineering ; Nanotechnology ; Composite material Metal Alloys Wear and Properties ; Advanced Machining and Optimization Techniques ; Engineering Technology and Methodologies
Authors: Daniel Weisz-Patrault | Charles Francart | Gabriel Seisson
Source: SPIRE - Sciences Po Institutional REpository (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Uncertainty estimation and hierarchical Bayesian analysis of mechanical dynamic tests International audience Bayesian probability ; Estimation ; Computer science ; Bayes estimator ; Bayesian hierarchical modeling ; Econometrics ; Statistics ; Artificial intelligence ; Machine learning ; Bayesian inference ; Mathematics ; Engineering High-Velocity Impact and Material Behavior ; Probabilistic and Robust Engineering Design ; Structural Response to Dynamic Loads
Authors: Tawfik Taher Ajaal.
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2019-09-20)
Field: Chemistry — Organic Chemistry

POLYMER USES IN TISSUE ENGINEERING. The biodegradable polymer, poly(caprolactone) (PCL), was used to dip-coat silicon-stabilized resorbable calcium phosphate ceramic pellets and scaffolds implants. The PCL coatings increased in thickness on the dense ceramic pellets with the number of dipping and did not detach from the ceramic substrates during mechanical testing. The distribution of PCL in the porous scaffolds was not homogeneous, i.e. mostly located along the outer surface areas and at the interconnection of struts. The scaffolds with thick PCL coatings were handled in ways analogous to those that are used in clinical applications, such as drilling, screwing, cutting and grinding, etc.; it was found that this could be done without powdering or shattering. The compressive failure features of the thickly PCL-coated scaffolds were quite different from those of uncoated scaffolds and those with thin PCL coatings. For uncoated scaffolds or those with a thin PCL coating, the compressive strength decreased quickly from the yield point to zero after failure, but for the thick PCL-coated scaffolds, it became nearly constant strength after a quick decrease from the yield point, and started increasing towards the end of a constant strain region. Tissue engineering ; Polymer ; Polymer science ; Engineering ; Materials science ; Biomedical engineering ; Composite material Photopolymerization techniques and applications
Authors: Geert Postma | Jacopo Acquarelli | Twan van Laarhoven | Elena Marchiori | L.M.C. Buydens | Jeroen J. Jansen
Source: Data Archiving and Networked Services (DANS) (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Deep learning for spectroscopic data analysis: an evaluation Computer science ; Artificial intelligence ; Deep learning Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: B. Firdaus Begam | J. Rajeswari | M Hann | R Green | Thomas Engel | Nathan Brown | B Firdausbegam | J Kumar | Matthias Brustle | Bernd Beck | Torsten Schindler | William King | Timothy Mitchell | Timothy Clark | F Tsai | K Pearson | H Hotelling | J Tenenbaum | V Silva | J Langford | Z Zhang | H Zha | B Scholkopf | A Smola | K Muller | Klaus-Robert Muller | Gunnar Ratsch | Soren Sonnenburg | Sebastian Mika | Michael Grimm | Nikolaus Heinrich | Q Kilian | Weinberger | Lawrence Feisha | Saul | S Roweis | L Saul | J Satheeshkumar | Christopher Lipinski | Franco Lombardo | Beryl Dominy | Paul Feeney
Source: International Journal of Innovative Technology and Exploring Engineering (article, 2019-10-11)
Field: Chemistry — Analytical Chemistry

Visualization of Chemical Space using Kernel Based Principal Component Research Principal Component analysis (PCA) is one of the important and popular multivariate statistical methods applied over various data modeling applications. Traditional PCA handles linear variance in molecular descriptors or features. Handling complicated data by standard PCA will not be very helpful. This drawback can be handled by introducing kernel matrix over PCA. Kernel Principal Component Analysis (KPCA) is an extension of conventional PCA which handles non-linear hidden patterns exists in variables. It results in computational efficiency for data analysis and data visualization. In this paper, KPCA has been applied over dug-likeness dataset for visualization of non-linear relations exists in variables. Kernel principal component analysis ; Principal component analysis ; Visualization ; Principal component regression ; Kernel (algebra) ; Pattern recognition (psychology) ; Computer science ; Artificial intelligence ; Data mining ; Kernel method ; Data visualization ; Mathematics ; Support vector machine Spectroscopy and Chemometric Analyses ; Computational Drug Discovery Methods
Authors: Nabin Kandel
Source: Journal of International Crisis and Risk Communication Research (article, 2019-01-01)
Field: Materials Science — Biomaterials

Molecular Basis of Membrane Pore Formation by Amyloid Beta Peptide Alzheimer's Disease (AD) is a neurodegenerative disorder that affects around 50 million people worldwide and causes cognitive decline, brain atrophy and death. Despite extensive basic and clinical studies and drug development efforts, currently no effective treatments are available for AD. The amyloid β (Aβ) peptide is neurotoxic and is tightly associated with AD pathology, but the molecular mechanism of its action remains unclear. There are various forms of Aβ in the brain, ranging from the full length Aβ1-42 to shorter peptides, such as a strongly toxic Aβ25-35 fragment. The Amyloid Cascade Hypothesis (ACH) postulated that extracellular Aβ deposits cause the disease. More recently, the soluble Aβ oligomers came into the focus of research as they proved to be the major neurotoxic entities. One of the mechanisms by which Aβ peptides, including Aβ25-35, kill neurons is membrane perforation and disruption of cellular homeostasis. Although direct membrane interaction and pore formation by Aβ has been documented, the detailed structural aspects of membrane pores remain elusive. Here, we quantitatively describe the structure of Aβ25-35 in aqueous buffer and in lipid environment, its binding to membranes, pore formation, and the details of membrane pores. We have shown that membrane binding of Aβ25-35 is electrostatically driven. Aβ25-35 forms β-barrel like structures ranging from hexamers to octamers and then assemble into supra-molecular structures forming calcium-conducting pores in the membrane with radius of 6 Å to 7 Å. The structural features of Aβ25-35 pores depend on the content of cholesterol in the membranes. Moreover, the aggregation and structural changes of a series of Aβ fragments have been analyzed to identify the segment(s) of highest propensity for fibrillogenesis that might serve as initiators of Aβ aggregation and conversion into toxic species. Finally, the structures of the full-length Aβ1-42 and a hypertoxic version pEAβ 3-42, in lipid environment have been analyzed by solid state nuclear magnetic resonance. Collectively, these studies will elucidate the structural details of membrane pores formed by Aβ peptides as targets for new anti-AD therapies. Amyloid (mycology) ; Peptide ; Chemistry ; Membrane ; BETA (programming language) ; Biophysics ; Biochemistry ; Biology ; Computer science Supramolecular Self-Assembly in Materials ; Lipid Membrane Structure and Behavior ; Alzheimer's disease research and treatments
Authors: McKayla Patterson
Source: Journal of the Arkansas Academy of Science (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Use of Aerial Imagery and Novel Experimental Design to Determine the Distribution of Foliar Diseases on Soybean and Improve Efficiency of Product Testing Soybeans are grown on approximately 1.3 million ha in Arkansas generating an estimated $1.7 billion annually. Foliar diseases on soybean can result in economic losses. Growers spend significant time and money on disease scouting via crop consultants and often (subsequent) fungicide applications. Fungicide trials are often arranged in small plots designs. In these scenarios, spatial variability of foliar disease is minimized. While it is advantageous to minimize variance outside of treatment differences, another limitation with many small plot trials is ample disease pressure or having only lower severity. Within a commercial production field, soil types and disease severities vary. Logically, by designing trials that take advantage of sub-field variability, efficacy of foliar fungicides could be determined in multiple zones of disease severity and factors that contribute to disease incidence, severity, or product efficacy could be determined. This work sought to understand foliar diseases distributions and how fungicide product evaluation might be improved. Because of the size of these trials, it was hypothesized that aerial imagery might be useful to determine sub-field variability of plant disease or other factors that influence disease. In 2017-18, strip trials were established in nine soybean fields throughout Southeast Arkansas. Fungicides were applied between full bloom and beginning pod. Fungicide strips were georeferenced with points spread approximately equidistant throughout the length of the field. Foliar diseases were identified, and disease levels determined across the test areas. Disease distributions were mostly significantly clustered and product efficacy changed as disease severity changed. Aerial imagery was captured on wheat, barley, and canola trials using a sUAS with visual (RGB) and near infrared sensors. Images of all test crops were captured at three different altitudes, and bloom percentage on canola and ground coverage for barley and wheat trials were assessed. Plot images were human rated and assessed using disease quantification software and plots were rated by field observations. Human rated and software quantifications of images were similar confirming plot assessment by sUAS is possible for some applications and could be useful in larger research trials such as the commercial field strip trials used in this work. Product (mathematics) ; Computer science ; Distribution (mathematics) ; Artificial intelligence ; Agricultural engineering ; Process engineering ; Environmental science ; Remote sensing ; Mathematics ; Engineering ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Leaf Properties and Growth Measurement
Authors: Muhammad Zainul Arifin | Arli Aditya Parikesit
Source: Indonesian Journal of Life Sciences (article, 2019-01-17)
Field: Materials Science — Materials Chemistry

Bioinformatics tools to Predict N-myristoylation Site a Comparison Study Protein N-myristoylation is the covalent attachment of myrstate, via an amide bond, to the N-terminal glycine residue of a nascent polypeptide assisted by myristol-CoA protein: N-myristoltransferases (NMT). PROSITE motif describes 5 amino acid after glycine site that would give rise to myristoylation site. However, applied to whole database extract, this motif give too many false postive results. Therefore 2 new tools were developed for N-myristoylation prediction.Taking physical properties into consideration inceases prediction scores greatly. However, these algorithms still cannot predict myristoylated site correctly 100% of the time due to limited understanding of the real mechanims underlying N-myristoylation Myristoylation ; Amino acid residue ; Residue (chemistry) ; Covalent bond ; Glycine ; Chemistry ; Amino acid ; Computational biology ; Peptide sequence ; Biochemistry ; Biology ; Membrane Enzyme Structure and Function ; Protein Structure and Dynamics ; Metabolism, Diabetes, and Cancer
Authors: Z. Nussinov | Nicholas B. Weingartner | F. S. Nogueira
Source: arXiv (Cornell University) (preprint, 2019-02-18)
Field: Materials Science — Materials Chemistry

The "glass transition'' as a topological defect driven transition in a distribution of crystals and a prediction of a universal viscosity collapse Topological defects are typically quantified relative to ordered backgrounds. The importance of these defects to the understanding of physical phenomena including diverse equilibrium melting transitions from low temperature ordered to higher temperatures disordered systems (and vice versa) can hardly be overstated. Amorphous materials such as glasses seem to constitute a fundamental challenge to this paradigm. A long held dogma is that transitions into and out of an amorphous glassy state are distinctly different from typical equilibrium phase transitions and must call for radically different concepts. In this work, we critique this belief. We examine systems that may be viewed as simultaneous distribution of different ordinary equilibrium structures. In particular, we focus on the analogs of melting (or freezing) transitions in such distributed systems. The theory that we arrive at yields dynamical, structural, and thermodynamic behaviors of glasses and supercooled fluids that, for the properties tested thus far, are in qualitative and quantitative agreement with experiment. We arrive at a prediction for the viscosity and dielectric relaxations that is universally satisfied for all experimentally measured supercooled liquids and glasses over 15 decades. Supercooling ; Amorphous solid ; Glass transition ; Phase transition ; Statistical physics ; Viscosity ; Work (physics) ; Condensed matter physics ; Materials science ; Dielectric ; Thermodynamics ; Chemical physics ; Theoretical physics ; Physics ; Chemistry ; Polymer ; Crystallography Material Dynamics and Properties ; Theoretical and Computational Physics
Authors: Valdi Rizki Yandri | Herisajani Herisajani | Fitriadi Fitriadi
Source: Elektron Jurnal Ilmiah (article, 2019-06-30)
Field: Materials Science — Materials Chemistry

Perkiraan Tegangan Lewat Denyar Isolator Tegangan Menengah 20 kV Keramik dan Resin Epoksi berdasarkan Data Arus Bocor This paper explains the research results of leakage current data and estimation of flashover voltage on ceramics and epoxy resin as 20 kV outdoor insulator in a chamber with tropical climate conditions. The waveform of leakage current (LC) was measured using a digital oscilloscope. The digital data was transferred to a personal computer using a RS-232 cable. The digital data was analyzed using Fast Fourier Transform. The result showed that LC was affected by various environment conditions like temperature, humidity and pollution. LC of ceramics insulator was higher than epoxy resin insulator in low temperature, high humidity and high pollution condition. Epoxy ; Oscilloscope ; Materials science ; Insulator (electricity) ; Composite material ; Waveform ; Ceramic ; Voltage ; Arc flash ; Electrical engineering ; Acoustics ; Physics ; Engineering High voltage insulation and dielectric phenomena ; Power Line Communications and Noise ; Thermal Analysis in Power Transmission