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12,393 results for “materiality”
CBMICD1.0: China's building material intensity coefficient dataset (1949-2015)
<p>The building material intensity coefficients is the most commonly used method to estimated building material stock and resource recycling potential in the urban building system at various spatial-temporal scales because of its high accuracy, efficiency and conciseness. With the circular economy become the research hotspot, some building material intensity coefficients datasets have been reported in diverse type of literature (e.g., journals, books and reports). These scattered datasets are being compiled, and building material intensity coefficients are currently for some countries (e.g., Japan, Germany and Sweden) except for in an important country of world, China which has the most rapid urbanization. Therefore, in this study, we carried out an extensive survey and critical review of the literature (from 1949-2017) on building material intensity coefficients in China and developed China’s building material intensity coefficient dataset (CBMICD1.0). This dataset consists of 813 different aged buildings with different structures located in 30 provinces in China and their associated background information (e.g. geographical location, building application and building structure).The dataset which provides essential supporting information for researchers on circular economy, is helping to provide a better understanding of the availability of resources in the city and its future potential supply for recycling as well as to develop strategies for the management of construction and demolition waste. </p>
Replication materials for Schmutte (2014) "Free to Move? A Network Approach to the Analysis of Job Mobility"
<p>This folder contains datasets and coded needed to replicate results published in Schmutte, Ian M. (2014) "Free to Move? A Network Approach to the Analysis of Job Mobility, " Labour Economics vol.29 pp.49--61</p>
Heterogeneously catalyzed continuous flow reactors with highly insulating wall materials for the production of hydrogen by steam reforming
<p><strong>Heterogeneously catalyzed continuous flow reactors with highly insulating wall materials for the production of hydrogen by steam reforming</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>Catalysts may be classified generally according to their physical state, their chemical nature, or the nature of the reactions that they catalyze. Catalysts may be gases, liquids, or solids. In homogeneous catalysis, the catalyst is molecularly dispersed in the same phase (usually gaseous or liquid) as the reactants. In heterogeneous catalysis the reactants and the catalyst are in different phases, separated by a phase boundary. Most commonly, heterogeneous catalysts are solids, and the reactants are gases or liquids. When the catalyst and the reacting substances are present together in a single state of matter, usually as a gas or a liquid, it is customary to classify the reactions as cases of homogeneous catalysis. Oxides of nitrogen serve as catalysts for the oxidation of sulfur dioxide in the lead chamber process for producing sulfuric acid, an instance of homogeneous catalysis in which the catalyst and reactants are gases. Traces of water vapour catalyze some gas reactions, for example, the interaction of carbon monoxide and oxygen, which proceeds only slowly in dry conditions. Sulfuric acid used as a catalyst for the formation of diethyl ether from ethyl alcohol is an example of homogeneous catalysis in the liquid phase (when the products, water and ether, are continuously removed by distillation); by this method, considerable quantities of alcohol can be converted to ether with a single charge of sulfuric acid. The inversion of cane sugar and the hydrolysis of esters by acid solutions also are examples of homogeneous catalysis in the liquid phase.</p> <p>Streamwise distance (meter), Heterogeneous reaction rate along the length of the reactor (mole per square meter per second)</p> <p>0 2.51969</p> <p>0.00025 2.52898</p> <p>0.0005 2.55637</p> <p>0.00075 2.59905</p> <p>0.001 2.65199</p> <p>0.00125 2.71215</p> <p>0.0015 2.779</p> <p>0.00175 2.85188</p> <p>0.002 2.929</p> <p>0.00225 3.007</p> <p>0.0025 3.08264</p> <p>0.00275 3.15412</p> <p>0.003 3.22107</p> <p>0.00325 3.28478</p> <p>0.0035 3.34725</p> <p>0.00375 3.40961</p> <p>0.004 3.47145</p> <p>0.00425 3.53115</p> <p>0.0045 3.58689</p> <p>0.00475 3.63782</p> <p>0.005 3.68446</p> <p>0.00525 3.72848</p> <p>0.0055 3.77185</p> <p>0.00575 3.81555</p> <p>0.006 3.85919</p> <p>0.00625 3.90117</p> <p>0.0065 3.93975</p> <p>0.00675 3.9745</p> <p>0.007 4.00595</p> <p>0.00725 4.03554</p> <p>0.0075 4.06508</p> <p>0.00775 4.09527</p> <p>0.008 4.1257</p> <p>0.00825 4.15508</p> <p>0.0085 4.18203</p> <p>0.00875 4.20586</p> <p>0.009 4.22692</p> <p>0.00925 4.24666</p> <p>0.0095 4.26675</p> <p>0.00975 4.28804</p> <p>0.01 4.31009</p> <p>0.01025 4.33162</p> <p>0.0105 4.35124</p> <p>0.01075 4.36833</p> <p>0.011 4.38322</p> <p>0.01125 4.39748</p> <p>0.0115 4.41272</p> <p>0.01175 4.42943</p> <p>0.012 4.44708</p> <p>0.01225 4.46422</p> <p>0.0125 4.47947</p> <p>0.01275 4.49245</p> <p>0.013 4.50367</p> <p>0.01325 4.51438</p> <p>0.0135 4.52587</p> <p>0.01375 4.53892</p> <p>0.014 4.55319</p> <p>0.01425 4.56709</p> <p>0.0145 4.57965</p> <p>0.01475 4.59029</p> <p>0.015 4.59928</p> <p>0.01525 4.60791</p> <p>0.0155 4.61738</p> <p>0.01575 4.62855</p> <p>0.016 4.64119</p> <p>0.01625 4.6539</p> <p>0.0165 4.665</p> <p>0.01675 4.67399</p> <p>0.017 4.68163</p> <p>0.01725 4.68922</p> <p>0.0175 4.69783</p> <p>0.01775 4.70789</p> <p>0.018 4.71927</p> <p>0.01825 4.73043</p> <p>0.0185 4.74005</p> <p>0.01875 4.74791</p> <p>0.019 4.75432</p> <p>0.01925 4.76037</p> <p>0.0195 4.7674</p> <p>0.01975 4.77614</p> <p>0.02 4.78619</p> <p>0.02025 4.79589</p> <p>0.0205 4.80412</p> <p>0.02075 4.81091</p> <p>0.021 4.81662</p> <p>0.02125 4.82204</p> <p>0.0215 4.8285</p> <p>0.02175 4.83678</p> <p>0.022 4.84603</p> <p>0.02225 4.85522</p> <p>0.0225 4.8636</p> <p>0.02275 4.87063</p> <p>0.023 4.87617</p> <p>0.02325 4.88134</p> <p>0.0235 4.88764</p> <p>0.02375 4.89563</p> <p>0.024 4.90453</p> <p>0.02425 4.91307</p> <p>0.0245 4.92044</p> <p>0.02475 4.92599</p> <p>0.025 4.92992</p> <p>0.02525 4.93332</p> <p>0.0255 4.93759</p> <p>0.02575 4.94309</p> <p>0.026 4.94878</p> <p>0.02625 4.95359</p> <p>0.0265 4.95679</p> <p>0.02675 4.95736</p> <p>0.027 4.95533</p> <p>0.02725 4.95189</p> <p>0.0275 4.94807</p> <p>0.02775 4.94582</p> <p>0.028 4.94248</p> <p>0.02825 4.9391</p> <p>0.0285 4.93625</p> <p>0.02875 4.93336</p> <p>0.029 4.93052</p> <p>0.02925 4.92708</p> <p>0.0295 4.92401</p> <p>0.02975 4.92139</p> <p>0.03 4.91781</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Heterogeneously catalyzed steam reforming reactors with highly insulating wall materials for hydrogen production
<p><strong>Heterogeneously catalyzed steam reforming reactors with highly insulating wall materials for hydrogen production</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>The design relates to a thermally coupled monolith reactor, used to thermally contact endothermic and exothermic reaction streams in adjacent channels. The geometry allows intimate thermal contact whilst keeping the streams from becoming mixed. The reactor body is constructed by modification of a substantially rigid and essentially nonporous monolith honeycomb. Prior to modification the monolith consists of a honeycombed body having a matrix of thin walls defining a multiplicity of discrete channels which pass through the body of the structure from one face to the opposing face. The monolith is modified in such a way as to produce a rigid body containing at least two discreet process flow paths which have a number of dividing walls in common. For the purpose of this design, a channel is defined as any individual passageway through the monolith body and a flow path is the group of channels used for a single reaction. The monolith body may be constructed from a number of materials using a range of techniques. Suitable materials include ceramics with a low coefficient of thermal expansion which are readily extrudable. These include, but are not limited to, mullite, corderite, alumina, and silica. Other materials include metals which may be extruded, welded, brazed, or diffusion bonded to make such structures. Using metals, it is sometimes useful to start with metal oxide powders, which are then bonded and reduced to the metallic state. Suitable metals include copper, aluminium, stainless steel, iron, titanium, and mixtures or alloys thereof.</p> <p>Streamwise distance (meter), Heterogeneous reaction rate along the length of the reactor (mole per square meter per second)</p> <p>0 5.24167</p> <p>0.00025 5.35038</p> <p>0.0005 5.59568</p> <p>0.00075 5.86537</p> <p>0.001 6.11865</p> <p>0.00125 6.34243</p> <p>0.0015 6.53109</p> <p>0.00175 6.68219</p> <p>0.002 6.79554</p> <p>0.00225 6.87267</p> <p>0.0025 6.91642</p> <p>0.00275 6.93001</p> <p>0.003 6.91683</p> <p>0.00325 6.88071</p> <p>0.0035 6.82557</p> <p>0.00375 6.75504</p> <p>0.004 6.67218</p> <p>0.00425 6.58003</p> <p>0.0045 6.48092</p> <p>0.00475 6.37655</p> <p>0.005 6.26889</p> <p>0.00525 6.15969</p> <p>0.0055 6.05031</p> <p>0.00575 5.9419</p> <p>0.006 5.83551</p> <p>0.00625 5.73198</p> <p>0.0065 5.63166</p> <p>0.00675 5.53473</p> <p>0.007 5.44181</p> <p>0.00725 5.35303</p> <p>0.0075 5.26832</p> <p>0.00775 5.18794</p> <p>0.008 5.11205</p> <p>0.00825 5.0406</p> <p>0.0085 4.9734</p> <p>0.00875 4.91027</p> <p>0.009 4.85116</p> <p>0.00925 4.79592</p> <p>0.0095 4.74421</p> <p>0.00975 4.69592</p> <p>0.01 4.6509</p> <p>0.01025 4.60897</p> <p>0.0105 4.57006</p> <p>0.01075 4.53403</p> <p>0.011 4.50066</p> <p>0.01125 4.46966</p> <p>0.0115 4.44077</p> <p>0.01175 4.41409</p> <p>0.012 4.38962</p> <p>0.01225 4.36729</p> <p>0.0125 4.34699</p> <p>0.01275 4.32857</p> <p>0.013 4.31176</p> <p>0.01325 4.29635</p> <p>0.0135 4.28232</p> <p>0.01375 4.26966</p> <p>0.014 4.2583</p> <p>0.01425 4.24794</p> <p>0.0145 4.23865</p> <p>0.01475 4.23021</p> <p>0.015 4.22255</p> <p>0.01525 4.21587</p> <p>0.0155 4.21007</p> <p>0.01575 4.20509</p> <p>0.016 4.20091</p> <p>0.01625 4.1973</p> <p>0.0165 4.19387</p> <p>0.01675 4.19079</p> <p>0.017 4.1885</p> <p>0.01725 4.18682</p> <p>0.0175 4.18524</p> <p>0.01775 4.18388</p> <p>0.018 4.18298</p> <p>0.01825 4.18213</p> <p>0.0185 4.18136</p> <p>0.01875 4.18095</p> <p>0.019 4.1809</p> <p>0.01925 4.1808</p> <p>0.0195 4.18068</p> <p>0.01975 4.18095</p> <p>0.02 4.18151</p> <p>0.02025 4.18213</p> <p>0.0205 4.18266</p> <p>0.02075 4.18322</p> <p>0.021 4.18389</p> <p>0.02125 4.18446</p> <p>0.0215 4.18499</p> <p>0.02175 4.18578</p> <p>0.022 4.18649</p> <p>0.02225 4.18705</p> <p>0.0225 4.18769</p> <p>0.02275 4.18848</p> <p>0.023 4.18913</p> <p>0.02325 4.18948</p> <p>0.0235 4.18969</p> <p>0.02375 4.18992</p> <p>0.024 4.18989</p> <p>0.02425 4.18952</p> <p>0.0245 4.18926</p> <p>0.02475 4.18907</p> <p>0.025 4.18838</p> <p>0.02525 4.18717</p> <p>0.0255 4.18578</p> <p>0.02575 4.18424</p> <p>0.026 4.18227</p> <p>0.02625 4.17979</p> <p>0.0265 4.17704</p> <p>0.02675 4.17371</p> <p>0.027 4.16989</p> <p>0.02725 4.16595</p> <p>0.0275 4.16173</p> <p>0.02775 4.15674</p> <p>0.028 4.15105</p> <p>0.02825 4.14506</p> <p>0.0285 4.13866</p> <p>0.02875 4.13164</p> <p>0.029 4.12371</p> <p>0.02925 4.11536</p> <p>0.0295 4.1047</p> <p>0.02975 4.07045</p> <p>0.03 4.04272</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Microchannel steam reforming reactors with insulating wall materials for hydrogen production
<p><strong>Microchannel steam reforming reactors with insulating wall materials for hydrogen production</strong></p> <p>Junjie Chen</p> <p>Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com</p> <p> </p> <p>In one form, the design includes a monolithic catalytic reactor with a primary flow path comprising a number of tubes which are lined with a catalyst. As chemical reactants are fed into the primary flow path the chemicals react, with the aid of the catalyst, to produce an exothermic reaction. In the same catalytic reactor is a secondary flow path, also comprising a number of tubes and also lined with a catalyst. In this secondary flow path, a different collection of chemical reactants are fed and, through the aid of the catalyst, will produce an endothermic reaction. The tubes of the primary and secondary flow paths are interspersed with one another within the monolith such that the heat generated from the exothermic reaction may conduct through the tube walls and serve as a heat source for the endothermic reaction. Furthermore, the microchannel steam reforming reactor design includes a method for enhancing one or more catalytic chemical reactions in terms of rate, product yield, energy and other parameters. Here, the initiating an exothermic reaction within one flow path of the monolithic reactor serves the dual purpose of creating a product yield as a result of that exothermic reaction and as a heat source. With the aid of this heat source, a second and endothermic reaction may be initiated in a secondary flow path which may absorb the heat from the exothermic reaction thereby enhancing product yield and making efficient use of available energy. To optimize the use of this heat, the reactions are controlled through one of many factors such as feed rate of the reactants, catalyst quality, reactant concentration and others. The flow paths may be co-current, countercurrent or other such variation as necessary to maximize heat transfer between the two reactions.</p> <p>Streamwise distance (meter), Heterogeneous reaction rate along the length of the reactor (mole per square meter per second)</p> <p>0 8.97706</p> <p>0.00025 9.12983</p> <p>0.0005 9.45292</p> <p>0.00075 9.76459</p> <p>0.001 10.009</p> <p>0.00125 10.1761</p> <p>0.0015 10.2678</p> <p>0.00175 10.2901</p> <p>0.002 10.2514</p> <p>0.00225 10.1611</p> <p>0.0025 10.0284</p> <p>0.00275 9.86268</p> <p>0.003 9.67153</p> <p>0.00325 9.46156</p> <p>0.0035 9.23929</p> <p>0.00375 9.01005</p> <p>0.004 8.77805</p> <p>0.00425 8.54661</p> <p>0.0045 8.31863</p> <p>0.00475 8.09598</p> <p>0.005 7.87987</p> <p>0.00525 7.67157</p> <p>0.0055 7.47194</p> <p>0.00575 7.28144</p> <p>0.006 7.10033</p> <p>0.00625 6.92886</p> <p>0.0065 6.76695</p> <p>0.00675 6.61432</p> <p>0.007 6.47076</p> <p>0.00725 6.33601</p> <p>0.0075 6.20963</p> <p>0.00775 6.09103</p> <p>0.008 5.98024</p> <p>0.00825 5.87692</p> <p>0.0085 5.78047</p> <p>0.00875 5.6906</p> <p>0.009 5.60703</p> <p>0.00925 5.5293</p> <p>0.0095 5.45708</p> <p>0.00975 5.38993</p> <p>0.01 5.3273</p> <p>0.01025 5.26922</p> <p>0.0105 5.2156</p> <p>0.01075 5.1662</p> <p>0.011 5.12058</p> <p>0.01125 5.07842</p> <p>0.0115 5.03943</p> <p>0.01175 5.00345</p> <p>0.012 4.9703</p> <p>0.01225 4.93973</p> <p>0.0125 4.91161</p> <p>0.01275 4.88587</p> <p>0.013 4.86227</p> <p>0.01325 4.84055</p> <p>0.0135 4.82058</p> <p>0.01375 4.80242</p> <p>0.014 4.78598</p> <p>0.01425 4.77087</p> <p>0.0145 4.75708</p> <p>0.01475 4.74449</p> <p>0.015 4.73297</p> <p>0.01525 4.72248</p> <p>0.0155 4.71307</p> <p>0.01575 4.70472</p> <p>0.016 4.69726</p> <p>0.01625 4.69071</p> <p>0.0165 4.68471</p> <p>0.01675 4.67933</p> <p>0.017 4.67489</p> <p>0.01725 4.67115</p> <p>0.0175 4.66781</p> <p>0.01775 4.66491</p> <p>0.018 4.6626</p> <p>0.01825 4.66054</p> <p>0.0185 4.65865</p> <p>0.01875 4.65713</p> <p>0.019 4.65599</p> <p>0.01925 4.65505</p> <p>0.0195 4.6543</p> <p>0.01975 4.65386</p> <p>0.02 4.65375</p> <p>0.02025 4.65363</p> <p>0.0205 4.6535</p> <p>0.02075 4.6538</p> <p>0.021 4.65451</p> <p>0.02125 4.65516</p> <p>0.0215 4.65575</p> <p>0.02175 4.65657</p> <p>0.022 4.65718</p> <p>0.02225 4.65771</p> <p>0.0225 4.65857</p> <p>0.02275 4.65952</p> <p>0.023 4.66024</p> <p>0.02325 4.66071</p> <p>0.0235 4.66111</p> <p>0.02375 4.66146</p> <p>0.024 4.66145</p> <p>0.02425 4.66101</p> <p>0.0245 4.66041</p> <p>0.02475 4.65975</p> <p>0.025 4.65862</p> <p>0.02525 4.65679</p> <p>0.0255 4.65471</p> <p>0.02575 4.65255</p> <p>0.026 4.6498</p> <p>0.02625 4.64634</p> <p>0.0265 4.64254</p> <p>0.02675 4.63791</p> <p>0.027 4.63242</p> <p>0.02725 4.62651</p> <p>0.0275 4.62008</p> <p>0.02775 4.61266</p> <p>0.028 4.60415</p> <p>0.02825 4.59488</p> <p>0.0285 4.585</p> <p>0.02875 4.57438</p> <p>0.029 4.5624</p> <p>0.02925 4.54979</p> <p>0.0295 4.5335</p> <p>0.02975 4.47929</p> <p>0.03 4.43516</p> <p>Contributor: Junjie Chen, ORCID: 0000-0001-5055-4309, E-mail address: komcjj@gmail.com, Department of Energy and Power Engineering, School of Mechanical and Power Engineering, Henan Polytechnic University, 2000 Century Avenue, Jiaozuo, Henan, 454000, P.R. China</p>
Guided wave representations dataset for material property estimation and generation
<p>Material property identification in composite materials is necessary for material degradation as well as non-destructive characterization. The inverse problem needs a forward simulator. Ultrasonic-guided waves are sensitive to material properties and can be used for the purpose. The stiffness matrix method and group velocity calculation routine are used as the forward solver. The solver outputs polar group velocity curves of two fundamental Lamb wave modes for different material properties and ply layup sequences. The curves can be converted into binary images (black and white) named polar representations for image processing algorithms. The datasets contain polar representations corresponding to different material properties and ply layup sequences of a transversely isotropic laminate.</p>
Co-manipulation of soft-materials estimating deformation from depth images
<p>Video describing our work on Co-manipulation of soft-materials estimating deformation from depth images</p>
Supplementary materials for: CNN-based surrogate for the phase field damage mode
<p>We investigate the generalization of a CNN-based surrogate for the phase field model in predicting both damage and maximum/peak load, given the image of an arbitrary 2D microstructure of a unidirectional fiber-reinforced composite. We first discuss the phase field model and the numerical procedure to generate training and test data from synthetic microstructures with different volume fractions and fiber radii. We next present a two-stage approach for predicting peak load, achieved by first transforming a given fiber-encoded microstructure image to a continuous damage field; and second, predicting peak load from the damage field. A key finding is that the direct approach for predicting peak load from the microstructure image using a standard regression model fails to generalize. Instead, the damage field, even if imperfectly predicted, provides valuable cues for the CNN in generalizing across new microstructures. We describe several case studies to demonstrate the capability of the surrogate model to predict damage and peak load and to interpolate over fiber radii and volume fractions. </p>
Supplementary materials for "SPAG9 expression predicts a good prognosis in patients with clear cell renal cell carcinoma: A bioinformatics integrative analysis"
<p>Supplementary materials for "SPAG9 expression predicts a good prognosis in patients with clear cell renal cell carcinoma: A bioinformatics integrative analysis".</p>
Supplementary material for a usability evaluation of a semantic search for biological datasets
<p>We conducted a usability evaluation for a semantic dataset search with 20 biodiversity scholars in June and July 2022 in Germany.</p> <p>Following the TREC guidelines (https://www-nlpir.nist.gov/projects/t9i/spec.html), we setup eight user tasks and surveys with questionnaires to guide users through the evaluation. The zip file provides questionnaires, survey templates and the original results.</p> <p>A Jupyter notebook for data analysis is provided in our GitHub repository: <a href="https://github.com/fusion-jena/semantic-search-usability-analysis">https://github.com/fusion-jena/semantic-search-usability-analysis</a></p>
"RESEARCH & PROJECTS Achievement"-Additional Proof Materials
<p>Additional proof materials for Zongyue ZHANG's achievements regarding research & academic projects he worked on during his Master's education at PSL Research University and Huazhong University of Science & Technology and during various training programs he participated in different labs and institutions in China and Europe.</p>
Supplementary materials. Publication "Three-way relationships between gut microbiota, helminth assemblages and bacterial infections in wild rodent populations" by Bouilloud et al.
<p><strong>Supplementary information</strong></p> <p><strong>Supplementary Figure S1</strong>. Maps showing the sampling area (left) and localities (right) in France. Forests are indicated in green and water in blue. The four sampling localities are represented with a colored polygon. The arrow indicates the North.</p> <p> </p> <p><strong>Supplementary Figure S2</strong>. Composition of the gut bacteriota. The relative abundance of six phyla representing 99% of the total composition is represented. Individuals are grouped by sampling localities, which are ordered from North to South. (A) Bar graph shows individual variation in phyla composition (phylum=color). (B) Box and whisker plots represent median and interquartile values for each phylum. Black dots correspond to mean values, and colored dots correspond to individuals.</p> <p> </p> <p><strong>Supplementary Figure S3</strong>. Variations of alpha diversity with individual factors, for the gut bacteriota (family level), pathogenic bacteria and gastro-intestinal helminths of bank voles. Alpha diversity is estimated using the specific richness (A, B and C) and the Shannon index (D, E and F). In graphs C and F, the blue line corresponds to the linear regression line.</p> <p> </p> <p><strong>Supplementary Figure S4</strong>. Relationships between the composition of the gut bacteriota, pathogenic bacteria and gastro-intestinal helminth communities: The db-RDA triplot shows the structure of the gut bacteriota at the phylum level and the correlations with the intra-host parasite communities. The arrows correspond to the significant explanatory variables. Each point corresponds to an individual, and the colors correspond to the different sampling localities.</p> <p> </p> <p><strong>Supplementary Table S1. </strong>Variation of the Firmicutes/Bacteroidetes ratio with localities and individual factors.</p> <p> </p> <p><strong>Supplementary Table S2. </strong>Alpha diversity metrics and statistics for the gut bacteriota, pathogenic bacteria and helminth communities of bank voles.</p> <p> </p> <p><strong>Supplementary Table S3. </strong>Beta diversity metrics and statistics for the gut bacteriota, pathogenic bacteria and helminth communities of bank voles</p>
Dataset supporting publication: "Experimental Characterization of a Smart Material via DIC"
<p>Dataset supporting publication: “Experimental Characterization of a Smart Material via DIC” (publication available in <a href="https://zenodo.org/record/7266424#.Y1_dynbMJPY">GEOFIT Zenodo</a>)</p> <p>Datasets resultant from structural health monitoring activities (accelerometer data).</p> <p>When no extensometer is available in a generic tensile-compression test carried out by a universal testing machine (for instance the model BIONIX from Material Testing Systems (MTS), the test results only provide the relative displacement between the machine grips. The test does not provide any information on the local behaviour of the material. This contribution presents the potential of an application of Digital Image Correlation (DIC) toward the reconstruction of the behaviour along the specimen. In particular, the authors test a Ni-Ti shape memory alloys (SMA) specimen with emphasis on the coupling of the two measurement techniques. The activity reported in this work have been founded by European Union Horizon 2020 research and innovation program under grant agreement No 792210 (GEOFIT).</p>
Supplementary Material for the Article "Field, Capital, and Habitus: The Impact of Pierre Bourdieu on Bibliometrics"
<p>The full dataset of the review "Field, Capital, and Habitus: The Impact of Pierre Bourdieu on Bibliometrics" published in the journal <em>Quantitive Science Studies</em> (Appendix A), as well as the coding scheme (Appendix B), and a list of suggested readings based on the finding of the study (Appendix C). </p>
Materials Project Dataset
<p>Structure-formation energy pairs from February 2022 version of MP database.</p>
Resources of "Declarative RDF Graph Construction: Materialization or Virtualization?"
<p>Resources for the paper "Declarative RDF Graph Construction: Materialization or Virtualization?", currently under double-blind review, thus all information about the authors is redacted.</p> <ul> <li><code>GTFS-MADRID-BENCH.tar.xz</code>: GTFS Madrid Bench with scales 1, 25, 50</li> <li><code>BSBM.tar.xz</code>: BSBM benchmark with scales 5000, 10000, 15000</li> <li>SANTA: <ul> <li><code>PARALLEL-LOADING.tar.xz</code>: parallel loading parameter data with 1, 8, 16, 24, 32 cores.</li> <li><code>DUPLICATES.tar.xz</code>: duplicate values parameter data with 0%, 25%, 50%, 75% and 100% of the data containing duplicates.</li> <li><code>EMPTY-VALUES.tar.xz</code>: empty values parameter data with 0%, 25%, 50%, 75% and 100% of the data containing empty values.</li> <li><code>RAW-DATA.tar.xz</code>: scaling among data records & properties parameter data with 1000, 5000, 25000, 125000 records and 1, 5, 10, 15 properties.</li> <li><code>JOIN-1_1.tar.xz</code>: Join 1-1 data.</li> <li><code>JOIN-1-N.tar.xz</code>: Join 1-N data with relationship N: 3, 5, 10, 15.</li> <li><code>JOIN-N-1.tar.xz</code>: Join N-1 data with relationship N: 3, 5, 10, 15.</li> <li><code>JOIN-N-M.tar.xz</code>: Join N-M data with relationships N-M: 3-3, 3-5, 5-3, 10-5, 5-10.</li> <li><code>JOIN-DUPLICATES.tar.xz</code>: Join duplicates data with 0%, 25%, 50%, 75%, 100% of the joins generating duplicates.</li> <li><code>MAPPINGS.tar.xz</code>: Triples Maps & Predicate Object Maps mapping rules impact parameter data with 1 TM + 15 POMs, 15 TMs + 1 POM, 3 TMs + 5 POMs, 5 TMs + 3 POMs.</li> </ul> </li> <li>Graphs <ul> <li>GTFS-graphs.pdf: GTFS-Madrid-Bench query execution time graph in full resolution</li> <li>BSBM-graphs.pdf: BSBM query execution time graph in full resolution</li> </ul> </li> </ul> <p><strong>Note</strong>: These archives are heavily compressed, make sure you have enough disk space to unpack them.</p> <p>Our <a href="https://github.com/blindreviewing/eswc2023-materialization-virtualization">bench-executor tool</a> can execute these automatically for you, you need to set the <code>--root</code> parameter to the root directory of the unpacked archive and execute them with the <code>run</code> command or list them all with the <code>list</code> command. Extensive instructions on how to use the tool are available in the README of the linked repository.</p>
Detection of SARS-CoV-2 variants by genomic analysis of wastewater ampliconic samples (Galaxy Training Material)
<p>The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater ampliconic samples. (https://training.galaxyproject.org/training-material/)</p>
Detection of SARS-CoV-2 variants by genomic analysis of wastewater metatranscriptomic samples (Galaxy Training Material)
<p>The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater metatranscriptomic samples. (https://training.galaxyproject.org/training-material/)</p>
tellingsounds/lama-data: LAMA Data - Capturing Entities (Persons, Topics, Music, etc.) in Austrian audio(-visual) archive material
<p>Data entered into LAMA (Linked Annotations for Media Analysis), a research software for capturing and visualizing the interaction of music and its contexts, developed by the Telling Sounds project.</p>
Supplementary material to: Using UAV-based photogrammetry coupled with in-situ fieldwork and U-Pb geochronology to decipher multi-phase deformation processes: A case study from Sarclet, Inner Moray Firth Basin, UK.
<p>This dataset represents the supplementary material to: Using UAV-based photogrammetry coupled with in-situ fieldwork and U-Pb geochronology to decipher multi-phase deformation processes: A case study from Sarclet, Inner Moray Firth Basin, UK.</p> <p>Appendix A - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘The Haven and The Stack’ locality in 3D PDF format.<br> Appendix B - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘Muiri Geo’ lo-cality in 3D PDF format.<br> Appendix C - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘The Haven and The Stack’ locality in .obj format.<br> Appendix D - This appendix represents the 3D Digital Outcrop Modell (DOM) of Sarclet ‘Muiri Geo’ lo-cality in .obj format.<br> Appendix E - This appendix represents the orthomosaic of Sarclet ‘Muiri Geo’ locality in GeoTiff format.<br> Appendix F - This appendix represents the orthomosaic of Sarclet ‘Muiri Geo’ locality in GeoTiff format.<br> Appendix G - This appendix represents the analytical conditions and geochronology data of the studied samples.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.