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114 results for “Hybrid systems”
Nanosegregation in arene-perfluoroarene π-systems for hybrid layered Dion-Jacobson perovskites
<p>Structural, optoelectronic, photovoltaic, and supplementary characterization data for “Nanosegregation in arene-perfluoroarene π-systems for hybrid layered Dion-Jacobson perovskites”, DOI:10.1039/d1nr08311b.</p> <ul> <li>Figure_2_XRD.opju: Data described in Figure 2 (XRD patterns) as Origin (.opj) software file.</li> <li>Figure 2_GIWAXS.zip: Data described in Figure 2 (GIWAXS images) as tiff files</li> <li>Figure_3_NMR.mnova: Data described in Figure 3 (NMR spectra) as MestReNova (.mnova) software file. </li> <li>Figure_4_spectra.opj: Data described in Figure 4 (UV-vis absorption and PL spectra) as Origin (.opj) software files.</li> <li>Figure_5_spectra.opj: Data described in Figure 5 (UV-vis absorption spectra and XRD patterns upon hydration) as Origin (.opj) software files.</li> <li>Figure_SI.zip: Data described in the Supporting Information Figures S1–S3 (NMR data as MestReNova (.mnova) software file) as well as Figures S4–S6 (XRD data, reciprocal space maps, radial profiles of q-maps, UV-vis absorption and PL spectra) as Origin (.opj) and image (.tif) files.</li> </ul>
Data Repository Accompanying "Controllable single Cooper pair splitting in hybrid quantum dot systems"
<p>Code and datasets associated with the manuscript " Controllable single Cooper pair splitting in hybrid quantum dot systems". With the code and data included here, all necessary fits and analysis can be conducted to produce the figures given in the manuscript and its supplementary material. The only exception is that we include the results of the quantum dot stability diagram simulation, however this simulation involves no new physics and the procedure is described in detail in the manuscript's supplementary information.</p>
A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines
<p>The dataset used for evaluating the hybrid feature location technique presented in the paper: "A Hybrid Feature Location Technique for Re-engineering Single Systems into Software Product Lines". This enables reproducibility, evaluation, and comparison of our study.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Dataset" contains for each subject system used:</p> <p>(i) the artificial variants and their configurations;</p> <p>(ii) the ECCO repository containing the traces;</p> <p>(iii) the ground truth and composed variants;</p> <p>(iv) the metrics results.</p> <p>_________________________________________________________________________________________________________</p> <p>Folder "Scenarios" contains for each subject system used:</p> <p>(i) the videos recorded from exercising features on GUI.</p>
Fig. 6 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig. 6. UPGMA clustering of biotypes by Mahalanobis distances calculated for body measurements and indices separately. Rectangles bounds the clusters with more than 90 % AU-support.
Fig 5. 95 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig 5. 95 % confidence ellipses of the biotypes in the morphospace of four between-group principal components calculated for indices. Mean groups of each biotype is marked with black point and designation.
Fig. 3. 95 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig. 3. 95 % confidence interval ellipses of the biotypes in the morphospace of bgPC1 and bgPC2 calculated for log10-transformed absolute traits. Each biotype means are marked with black points and names. The biotypes are explained in table 1.
Fig. 4. 95 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig. 4. 95% confidence interval ellipses of the biotypes in the morphospace of bg PC3 and bgPC4 A calculated for log10 transformed absolute traits. Designations the same as on fig. 3.
Fig. 2 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig. 2. Body measurements for Cobitis. Th e original fish image is from Wilhelm von Wright out of Fries, 1895.
Fig. 1 in Morphometric Variation Of Hybridizing Species And Gynogenetic Biotypes Of Spined Loaches (Cobitidae, Cobitis) In River Systems Of Ukraine
Fig. 1. Collection points of spined loaches in the river systems of Ukraine. Th e decoding of the numbering of samples is given in Material and methods.
Majorana modes with side features in magnet-superconductor hybrid systems
<p>This repository contains the file parameters_Nb36Mn1_rel_fm_40bandTB.dat with all tight-binding parameters for the normal-state 40-band model, in our paper "Majorana modes with side features in magnet-superconductor hybrid systems".</p>
PhytoNodes for Environmental Monitoring: Stimulus Classification based on Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System
<p>Cities worldwide are growing, putting bigger populations at risk due to urban pollution. Environmental monitoring is essential and requires a major paradigm shift. We need green and inexpensive means of measuring at high sensor densities and with high user acceptance. We propose using phytosensing: using natural living plants as sensors. In plant experiments we gather electrophysiological data with sensor nodes. We expose the plant <em>Zamioculcas zamiifolia</em> to five different stimuli: wind, temperature, blue light, red light, or no stimulus. Using that data we train ten different types of artificial neural networks to classify measured time series according to the respective stimulus. We achieve good accuracy and succeed in running trained classifying artificial neural networks online on the microcontroller of our small energy-efficient sensor node. To indicate later possible use cases, we showcase the system by sending a notification to a smartphone application once our continuous signal analysis detects a given stimulus.</p> <p> </p> <p>Data repository for our paper "PhytoNodes for Environmental Monitoring: Stimulus Classification based on<br> Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System", submitted to the GoodIT conference. Please refer to the paper for more information.</p> <p> </p> <p><strong>Contents of this repository</strong></p> <ul> <li><em>mu_interface:</em> Code for our data collection plant experiments, based on Raspberry Pis and the <a href="http://cybertronica.co/?q=products/phytosensor">Cybertronica phytosensing and phytoactuating system</a>.</li> <li><em>raw_data: </em>The datasets from our plant experiments for the stimuli wind, temperature, red light, blue light, and no stimulus.</li> <li><em>dl-4-tsc:</em> Deep learning framework developed by <a href="https://doi.org/10.1007/s10618-019-00619-1">Fawaz et. al (Deep learning for time series classification: a review)</a> and adapted to our use case. Find the training and testing datasets in the archives folder as well as the trained classifiers in the results folder.</li> <li><em>classification_results.ods: </em>Overview of the results from the deep learning framework (accuracy, precision, recall, training time).</li> <li><em>TFLite_Models: </em>The trained classifiers in TensorFlow Lite Format.</li> <li><em>00_AI_BLE_MeasuringOnlyWind: </em>Source code for classification on STM-based PhytoNodes (using MCDCNN two-class classifier) and Bluetooth communication. The code is written for the STM32WB55 Nucleo board and can be transferred to the dongle.</li> <li><em>zavrsniProjekt_iOS: </em>Source code of the iOS app used to receive data from the STM-based PhytoNodes.</li> <li><em>Watchplant_application_documentation.pdf: </em>Instructions to build and use the iOS app.</li> </ul>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 3. Hybrid EMD-BP approach for one trail feature extraction
<p>In this work, we propose a direct nonlinear approach to extract the more relevant IMFs corresponding to the different frequency components in the and bands and then obtain the BP in order to use them as features for mental task classification (see Fig. 3). The feature vector p used for the demonstration in this paper is composed, for each sample I, 1 < i < 2048, in a given trial (among a total of 160 trials) of four bandpower, calculated of the rhythms and in positions C3 and C4 Trad et al., 2011).</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 3. Hybrid EMD-BP approach for one trail feature extraction
<p>In this work, we propose a direct nonlinear approach to extract the more relevant IMFs corresponding to the different frequency components in the and bands and then obtain the BP in order to use them as features for mental task classification (see Fig. 3). The feature vector pi used for the demonstration in this paper is composed, for each sample I, 1 < i < 2048, in a given trial (among a total of 160 trials) of four bandpower, calculated of the rhythms and in positions C3 and C4 (Trad et al., 2011).</p>
Analysis of heritage stones and model wall paintings by pulsed laser excitation of Raman, laser-induced fluorescence and laser-induced breakdown spectroscopy signals with a hybrid system
<p>Analysis of heritage stone samples, alabaster, gypsum, limestone and marble, and model wall paintings was carried out with a laboratory, hybrid system based on the pulsed laser excitation of Raman, laser-induced fluorescence and laser-induced breakdown spectroscopy signals. The system is based on a nanosecond Q-switched Nd:YAG laser operating at its second (532 nm), third (355 nm) and fourth (266 nm) harmonics and a spectrograph coupled to a time-gated intensified charge coupled device for spectral analysis allowing detection with temporal resolution. For the stone samples, Raman spectra display the characteristic vibration modes of SO<sub>4</sub><sup>2-</sup> of calcium sulfate, in alabaster and gypsum, and of free CO<sub>3</sub><sup>2- </sup>of calcium carbonate, in limestone and marble. Simultaneously acquired laser-induced fluorescence spectra reveal characteristic bands that help to distinguish between heritage stone types. The elemental composition of stone samples is obtained by laser-induced breakdown spectroscopy upon excitation at 355 nm. Spectra of all stone samples reveal their elemental composition that includes Ca, Na, Mn and Sr and the presence of molecular species, such as CN, C<sub>2</sub> and CaO. Additional emission lines, ascribed to Mg, Si, Al and K, appear with different intensities according to the nature of the stone material. Model wall paintings, based on a red pigment, prepared as fresco or mixed with two different binders, were also studied. The complementary information provided by the three spectroscopic modes allows the identification of the pigment as red vermillion and of the different preparations based on the pigment alone or in mixtures with linseed oil and egg yolk binders.</p>
Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)
<p>This video is the sixth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 13/09/2022.</p> <p>Improving triaging from primary care into secondary care using heterogeneous data-driven hybrid machine learning: A real-world case study of decision support system using blood test & GP referral letters - Bing Wang and Prof Weizi (Vicky) Li (University of Reading)</p> <p>Bio: Dr Weizi (Vicky) Li is the PI of the Future Blood Testing Network, an Associate Professor of Informatics and Digital Health, Deputy Director in Informatics Research Centre, Henley Business School, University of Reading. She is an interdisciplinary researcher focusing on using informatics, data science, machine learning, and digital information systems to solve real-world healthcare challenges. She is the academic lead of a large collaborative project of Improving the Quality of Healthcare through an Integrated Clinical Pathway Management Approach and Cloud based Digital Data Integration Platform, which was awarded ESRC O2RB Excellence in Impact Award in 2018 for her research impact on healthcare quality improvement. She is the academic lead of machine learning based decision support system for outpatient management which has successfully been implemented in Royal Berkshire NHS Foundation Trust and has received Research Engagement and Impact award in 2020. She has been PI on projects funded by ESRC, EPSRC, The Health Foundation, NHS and companies, working on data-driven decision support systems that use real-world data (under privacy preserving framework) from multiple sources including Electronic Patient Record in acute, community hospital and primary care settings, remote health monitoring and patient reported outcomes to develop novel technologies (including AI based methods) to support clinical and operational decision makings in patient pathway. Bing Wang is currently a PhD candidate in informatics and system science at the Informatics Research Center, Henley Business School, University of Reading. Bing’s research interests are Natural Language Processing, Machine Learning and Graph Machine Learning. Bing been working as a data scientist at Royal Berkshire NHS Foundation Trust since December 2019 during his PhD.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/W6EH5l80NmU</p>
Hybrid Closed Loop Insulin Delivery System in Hypoglycemia
ClinicalTrials.gov study NCT03215914. IPD Sharing: YES. Countries: 1. Publications: 2.
A Conserved Inhibitory Interdomain Interaction Regulates DNA-binding Activities of Hybrid Two-component Systems in Bacteroides
<p>The study reveals a highly conserved inhibitory mechanism to regulate the activities of hybrid two-component systems (HTCSs) in <em>Bacteroides</em>. HTCSs comprise a major class of transcription regulators of polysaccharide utilization genes in <em>Bacteroides</em>. A conserved sequence motif has been discovered to correlate with the interdomain arrangement of HTCS domains. Presence or absence of this motif is likely predictive of the regulatory mechanism evolved for utilization of different glycans.</p> <p> </p> <p>This dataset includes sequence analyses and structure predictions of HTCSs.</p> <p>List of files:</p> <p>· AlphaFold-HTCS-RR.zip AlphaFold results of all HTCS-RR fragments in <em>B. theta</em></p> <p>· AlphaFold-HTCS-cyto-dimer.zip AlphaFold results of all HTCS-cyto dimers in <em>B. theta</em></p> <p>· HTCSbacteroides-MAFFT-fasta Sequence alignment of 6908 HTCSs from <em>Bacteroides</em></p> <p>· HMM-AllHTCS.hmm HMM of HTCSs generated from the MAFFT alignment</p> <p>· HMM-DBD-PF12833 HMM of HTH18 (Pfam: PF12833) from Interpro</p> <p>· HMM-REC-PF00072 HMM of REC (Pfam: PF00072) from Interpro</p> <p>· B_theta_RR_fasta Sequence alignment of 32 HTCS-RRs in <em>B. theta</em></p> <p>· B_theta_RR-tree A neighbor-joining phylogenetic tree of 32 HTCS-RRs in <em>B. theta</em> </p>
Feasibility of hybrid in-stream generator–photovoltaic systems for Amazonian off-grid communities
<p>While there have been efforts to supply off-grid energy in the Amazon, these attempts have focused on low upfront costs and deployment rates. These "get-energy-quick" methods have almost solely adopted diesel generators, ignoring the environmental and social risks associated with the known noise and pollution of combustion engines. Alternatively, it is recommended, herein, to supply off-grid needs with renewable, distributed microgrids comprised of photovoltaics (PV) and in-stream generators (ISG). Utilization of a hybrid combination of renewable generators can provide an energetically, environmentally, and financially feasible alternative to typical electrification methods, depending on available solar irradiation and riverine characteristics, that with community engagement allows for a participatory codesign process that takes into consideration people's needs. A convergent solution development framework that includes designers—a team of social scientists, engineers, and communication specialists—and communities as well as the local industry is examined here, by which the future negative impacts at the human–machine–environment nexus can be minimized by iterative, continuous interaction between these key actors.</p>
Degradation of pharmaceuticals using the hybrid ozonation-filtration system
<p>The hybrid ozonation-membrane filtration unit allows the simultaneous treatment of the contaminated water with ozone and micro- and nano-filtration (MF/NF) under controlled conditions using commercial single tubular ceramic membranes with an inside-out operation. In total, four commercial ceramic (CM) membranes with different compositions and pore sizes were selected. The composition of the selected membranes is given below</p> <ul> <li>TiO<sub>2</sub>/ZrO<sub>2</sub> composition of three different pore sizes: 50-, 150-, and 300 kDa MWCO) and</li> <li>TiO<sub>2</sub>/ TiO<sub>2</sub>+ZrO<sub>2</sub> composition of one pore size (0.200 μm MWCO).</li> </ul> <p>The files contain information on the degradation of the pharmaceuticals using the different membranes under the three surface modifications; CeO2, CeTiOx and CeO2+CeTiOx.</p> <p>Permeability tests have been performed on all four membranes. The filtration unit can operate from 0.3 -1.5 bar pressure with a permeability flow ranging from 200 - 1900 L.m<sup>-2</sup>.h<sup>-1</sup> at 1 bar, starting from the lowest molecular weight cut-off (MWCO) membrane (50 kDa) and moving to the higher (0,200 μm) one.</p>
Control over epitaxy and the role of the InAs/Al interface in hybrid two-dimensional electron gas systems
<p>Raw and processed 'transport' data for paper the paper "Control over epitaxy and the role of the InAs/Al interface in hybrid two-dimensional electron gas systems". A short readme is given, data organized according to figures of the Main Text and Supplemental Material.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.