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11,506 results for “Dynamics”
Molecular dynamics simulations with grand-canonical reweighting suggest cooperativity effects in RNA structure probing experiments
<p>Molecular dynamics simulations of an RNA GAAA tetraloop interacting with SHAPE reagent 1-Methyl-7-nitroisatoic anhydride (1m7) in different numer of copies (1 to 19). See also https://arxiv.org/abs/2209.12640 and https://github.com/bussilab/paper-shapemd.</p>
Data from high throughput SNP-chip as cost effective new monitoring tool for assessing invasion dynamics in the comb jelly Mnemiopsis leidyi
<p class="MsoNormal"><span>High throughput low-density SNP arrays provide a cost-effective solution for population genetic studies and monitoring of genetic diversity as well as population structure commonly implemented in real time stock assessment of fish species. However, the application of high throughput SNP arrays for monitoring of invasive species has so far not been implemented. We developed a species-specific SNP array for the invasive comb jelly <em>Mnemiopsis leidyi</em> based on whole genome resequencing data. Initially, </span><span>a total of</span><span> </span><span>1,</span><span>395</span><span> </span><span>high quality </span><span>SNPs</span><span> were identified</span><span> </span><span>u</span><span>sing stri</span><span>ngent</span><span> filtering criteria</span><span>. From those, 192 assays were designed and validated, resulting in the final panel of 116 SNPs. Markers were diagnostic between the northern and southern <em>M. leidyi</em> lineages and highly polymorphic to distinguish populations. Despite using a reduced representation of the genome, our SNP panel yielded comparable results to using a whole genome resequencing approach (832,323 SNPs), recovering similar values of genetic differentiation between samples and detecting the same clustering groups when performing Structure analyses. The resource presented here provides a cost-effective, high throughput solution for population genetic studies, allowing to routinely genotype large number of individuals. Monitoring of genetic diversity and effective population size estimations in this highly invasive species will allow for the early detection of new introductions from distant source regions or hybridization events. Thereby, this SNP chip represents an important management tool in order to understand invasion dynamics and </span><span>opens the door for implementing such methods for a wider range of alien invasive species.</span></p> <div></div>
Evidence that catecholaminergic systems mediate dynamic colour change during explosive breeding events in toads
<p><span>Many animals communicate by rapidly (within minutes or seconds) changing their body coloration. We know, however, little about the physiology of this behaviour. Here we study how catecholaminergic hormones regulate rapid colour change in explosive breeding toads (<em>Duttaphrynus melanostictus</em>), where large groups of males gather and quickly change their colour from brown to bright yellow during reproduction. We find that both epinephrine (EP) and/or norepinephrine (NE) cause the toads' skin to become yellow in minutes, even in the absence of social and environmental cues associated with explosive breeding. We hypothesize that natural selection drives the evolution of rapid colour change by co-opting the functional effects of catecholaminergic action. If so, then hormones involved in "fight or flight" responsivity may mechanistically facilitate the emergence of dynamic visual signals that mediate communication in a sexual context. </span></p>
Figure 6 in Dynamic of fish trophic guilds in the plateau-plain gradient in the Paraguay River, Northern Pantanal
Figure 6. Difference between trophic guilds in the sampled segments in Paraguay River. (A) herbivores. (B) piscivores. (C) invertivores. * indicates statistical difference at the 0.05 significance level.
Figure 2 in Dynamic of fish trophic guilds in the plateau-plain gradient in the Paraguay River, Northern Pantanal
Figure 2. Limnological characteristics in the sampled segments in the Paraguay River, Mato Grosso, Brazil, from July to November 2017 and August 2018. (A) temperature. (B) water transparency. * indicates statistical difference at the 0.05 significance level.
Figure 4 in Dynamic of fish trophic guilds in the plateau-plain gradient in the Paraguay River, Northern Pantanal
Figure 4. Principal Component Analysis (PCA) of the limnological and environmental variables in the segments in the Paraguay River, from July to November 2017 and August 2018. (A) variables contribution. (B) sampled areas ordination.
Figure 3 in Composition and dynamics of mixed flocks of birds in a remnant of Submontane Atlantic Rain Forest in southern Brazil
Figure 3. Distribution of the three sampling sectors (I, II, and III) in the study area, in Parque Nacional Aparados da Serra, municipality of Praia Grande, southern Santa Catarina state, Brazil.
Figure 1 in Composition and dynamics of mixed flocks of birds in a remnant of Submontane Atlantic Rain Forest in southern Brazil
Figure 1. Location of the study area in Parque Nacional Aparados da Serra, municipality of Praia Grande, southern Santa Catarina state, Brazil.
Figure 7 in Composition and dynamics of mixed flocks of birds in a remnant of Submontane Atlantic Rain Forest in southern Brazil
Figure 7. Monthly variation of the average size (in the number of individuals) of the mixed flocks of birds, in Parque Nacional Aparados da Serra, municipality of Praia Grande, southern Santa Catarina, Brazil, between October 2016 and September 2017.
Figure 4 in Composition and dynamics of mixed flocks of birds in a remnant of Submontane Atlantic Rain Forest in southern Brazil
Figure 4. Simple linear regression of the relationship between species richness and the number of individuals from mixed flocks of birds, in Parque Nacional Aparados da Serra, municipality of Praia Grande, southern Santa Catarina state, Brazil, between October 2016 and September 2017.
Quantitative biogeography: Decreasing and more variable dynamics of keystone and foundation species in an iconic meta-ecosystem
<p>Ecosystem stability has intrigued ecologists for decades, and the realization that the global climate was changing sharpened and focused this interest. Determination of climate change effects on community stability, however, requires long-term studies of structure and underlying dynamics, including bottom-up and top-down effects in natural ecosystems. Although relevant datasets were rare in the early years of community ecology, such information has increased in recent decades. In a rocky intertidal system, we investigated the changes in ecological subsidies (nutrients, phytoplankton, prey colonization), several performance metrics of the dominant space occupier (mussels) and its primary predator (sea stars), and rate of predation by sea stars on mussels in relation to climatic oscillations, temperature, and disease. We focused on spatio-temporal changes in the mean and variability of these metrics. The research protocol involved annually repeated multiyear (~1999–2018), multisite (13 sites nested within 5 regions along ~260 km of the Oregon coast) observations, measurements, and experiments. We analyzed associations between environmental variables and ecological performance of key elements of the sea-star-mussel-dominated mid-intertidal system. We found that upwelling declined in some regions, but became more variable across all study regions. Air and water temperatures oscillated, but their mean and variation increased through time, with peak values coinciding with the 2014–16 combined El Niño and Marine Heat Wave. Ecological subsidies generally declined during the study period, and bottom-up processes increased in variability. Excepting growth rate, mussel (<em>Mytilus</em> <em>californianus</em>) performance (condition index, reproductive output) generally decreased and became more variable. Primarily due to a sea star wasting epidemic, reproductive output of the top predator <em>Pisaster</em> <em>ochraceus</em> decreased and became more variable, and predation rate on mussels also dropped abruptly. Analyses indicated that the primary drivers of these changes were temperature-related environmental factors. Since declining means and increasing variability of ecological performances are thought to typify destabilizing ecosystems, and environmental trends are toward ever more stressful conditions, the outlook for this iconic ecosystem is discouraging. Immediate and rapid action to mitigate and ultimately reverse climate change likely is the only option available to prevent an irreversible shift in the future of this, and most other ecosystems.</p>
Interaction of the inhibitory peptides ShK and HmK with the voltage-gated potassium channel KV1.3: Role of conformational dynamics
<p><strong>ABSTRACT: </strong>Peptide toxins that adopt the ShK fold can inhibit the voltage-gated potassium channel K<sub>V</sub>1.3 with IC<sub>50</sub> values in the pM range, and are therefore potential leads for drugs targeting autoimmune and neuroinflammatory diseases. NMR relaxation measurements and pressure-dependent NMR have shown that, despite being cross-linked by disulfide bonds, ShK itself is flexible in solution. This flexibility affects the local structure around the pharmacophore for K<sub>V</sub>1.3 channel blockade and, in particular, the relative orientation of the key Lys and Tyr side chains (Lys22 and Tyr23 in ShK), and has implications for the design of K<sub>V</sub>1.3 inhibitors. In this study, we have performed molecular dynamics (MD) simulations on ShK and a close homolog, HmK, in order to probe the conformational space occupied by the Lys and Tyr residues, and docked the different conformations with a recently determined cryo-EM structure of the K<sub>V</sub>1.3 channel. Although ShK and HmK have 60% sequence identity, their dynamic behaviors are quite different, with ShK sampling a broad range of conformations over the course of a 5 μs MD simulation, while HmK is relatively rigid. We also investigated the importance of conformational dynamics, in particular the distance between the side chains of the key dyad Lys22 and Tyr23, for binding to K<sub>V</sub>1.3. Although these peptides have quite different dynamics, the dyad in both adopts a similar configuration upon binding, revealing a conformational selection upon binding to K<sub>V</sub>1.3 in the case of ShK. Intriguingly, the more flexible peptide, ShK, binds with nearly 300-fold higher affinity than HmK.</p>
Molecular dynamics simulations data of Caspase-3 enzyme with pentapeptide ligand DEVDG and its chiral mutant DEVdG having D-Asp at fourth position
<p>Amino acids in proteins are maintained in one specific L chiral form in the body. D-amino acids are not normally incorporated into proteins and their accumulation has been associated with several conditions including schizophrenia, amyotrophic lateral sclerosis, and other age-related disorders. However, the mechanisms by which the accumulation of D-amino-acids in proteins may lead to pathophysiological consequences remain poorly understood. In this work, we studied a model protease system, caspase-3 that specifically hydrolyses the 4’–5’ peptide bond of the pentapeptide substrate DEVDG. Through extensive molecular dynamics simulations, free energy calculations and distance maps, we reveal that caspase-3 naturally rejects the pentapeptide containing D-Asp substrate, DEVdG and prevents catalytic activity by caspase. The importance of this chiral discriminating capacity is evident from chiral-selective in vivo experimental assays to detect caspase-bound D-Asp in Drosophila where altering the chiral balance created impaired caspase activity and impaired apoptosis, increased tumour formation, and premature death. The modelling data reveals the molecular level charge balancing that enforces the chiral recognition necessary to maintain homeostasis across the cell, tissue, and organ level.</p>
Dataset for "Towards Better Evaluation for Dynamic Link Prediction"
<p>These are the datasets used in <em>Towards Better Evaluation for Dynamic Link Prediction</em></p> <p>For preparing the datasets, we closely follow the baseline methods' data preparation strategy.<br> The original networks are saved as <network>.csv.</p> <p>The networks are formatted as follows:<br> * Each edge is denoted in one line.<br> * Each line has the following format: source_node, destination_node, timestamp, edge_label, comma-separated arrays of edge features.<br> * Please note that if there is no edge label available, the edge_label column will be filled with 0s only for loading purpose; these labels are not used in the link prediction task.<br> * The first line denotes the network format.<br> * Edge features should include at least one feature. If there is no edge feature available, a 0 value is used for all the edges.</p> <p>The network edge-lists are pre-processed for different methods to use them (Specifically, for preprocessing the data, we use the scripts available in "preprocess_data.py" file of the corresponding baseline).<br> Ater preprocessing the network edge-list, there are three files that are used by the models:<br> * <ml_network>.csv: this file contains the timestamp edge-list.<br> * <ml_network>.npy: this file contains the edge features in the dense `npy` format that has the features in binary format.<br> * <ml_network_node>.npy: this file contains the node features in the dense `npy` format that contains the node features in binary format.<br> Please note that when the edge features or node features are absent, we use a vector of zeros is used as the node/edge features in line with the baseline methods.</p>
Dynamic viscosity of liquid rubidium at different temperatures
<p><strong>Dynamic viscosity of liquid rubidium at different temperatures</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>Rubidium is the second most reactive metal and is very soft, with a silvery-white lustre. Rubidium and cesium often occur together in nature. Rubidium, however, is more widely scattered and seldom forms a natural mineral; it is found only as an impurity in other minerals, ranging in content up to 5 percent in such minerals as lepidolite, pollucite, and carnallite. Brine samples have also been analyzed that contain up to 6 parts per million of rubidium. In the principal commercial process of rubidium production, small amounts of rubidium are obtained from the mixture of alkali metal carbonates remaining after lithium salts are extracted from lepidolite. Primarily a potassium carbonate, this by-product also contains approximately 23 percent rubidium and 3 percent cesium carbonates. The primary difficulty associated with the production of pure rubidium is that it is always found together with cesium in nature and is also mixed with other alkali metals. Because these elements are very similar chemically, their separation presented numerous problems before the advent of ion-exchange methods and ion-specific complexing agents such as crown ethers. Once pure salts have been prepared, it is a straightforward task to convert them to the free metal. This can be done by electrolysis of the fused cyanide or by reduction with calcium or sodium followed by fractional distillation. Rubidium is difficult to handle because it ignites spontaneously in air, and it reacts violently with water to yield a solution of rubidium hydroxide and hydrogen, which bursts into flames. If a metal sample has a large enough surface area, it can burn to form superoxides. Rubidium superoxide is a yellow powder. Rubidium peroxides can be formed by oxidation of the metal with the required amount of oxygen. Rubidium forms two other oxides. Rubidium and cesium are miscible in all proportions and have complete solid solubility.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>50 0.542</p> <p>100 0.435</p> <p>150 0.365</p> <p>200 0.316</p> <p>250 0.28</p> <p>300 0.252</p> <p>350 0.23</p> <p>400 0.212</p> <p>450 0.197</p> <p>500 0.185</p> <p>550 0.174</p> <p>600 0.165</p> <p>650 0.157</p> <p>700 0.15</p> <p>750 0.143</p> <p>800 0.138</p> <p>850 0.133</p> <p>900 0.128</p> <p>950 0.124</p> <p>1000 0.12</p> <p>1050 0.117</p> <p>1100 0.114</p> <p>1150 0.111</p> <p>1200 0.108</p> <p>1250 0.105</p> <p>1300 0.103</p> <p>1350 0.101</p> <p>1400 0.099</p> <p>1450 0.097</p> <p>1500 0.095</p> <p>1550 0.093</p> <p>1600 0.092</p> <p>1650 0.09</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>
Dynamic viscosity of liquid potassium at different temperatures
<p><strong>Dynamic viscosity of liquid potassium at different temperatures</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>Potassium metal is soft and white with a silvery lustre, has a low melting point, and is a good conductor of heat and electricity. Potassium imparts a lavender colour to a flame, and its vapour is green. The potassium content of the Dead Sea is estimated at approximately 1.7 percent potassium chloride, and many other salty bodies of water are rich in potassium. The waste liquors from certain saltworks may contain up to 40 grams per litre of potassium chloride and are used as a source of potassium. Most potassium is present in igneous rocks, shale, and sediment in minerals such as muscovite and orthoclase feldspar that are insoluble in water; this makes potassium difficult to obtain. As a result, most commercial potassium compounds are obtained via electrolysis from soluble potassium compounds, such as carnallite, sylvite, polyhalite, and langbeinite, which are found in ancient lake beds and seabeds. Potassium is produced by sodium reduction of molten potassium chloride. Molten potassium chloride is continuously fed into a packed distillation column while sodium vapour is passed up through the column. By condensation of the more volatile potassium at the top of the distillation tower. Efforts to devise a scheme for commercial electrolytic production of potassium have been unsuccessful because there are few salt additives that can reduce the melting point of potassium chloride to temperatures where electrolysis is efficient. There is little commercial demand for potassium metal itself, and most of it is converted by direct combustion in dry air to potassium superoxide, which is used in respiratory equipment because it liberates oxygen and removes carbon dioxide and water vapour.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>100 0.441</p> <p>150 0.358</p> <p>200 0.303</p> <p>250 0.263</p> <p>300 0.234</p> <p>350 0.211</p> <p>400 0.193</p> <p>450 0.178</p> <p>500 0.166</p> <p>550 0.155</p> <p>600 0.146</p> <p>650 0.138</p> <p>700 0.132</p> <p>750 0.126</p> <p>800 0.12</p> <p>850 0.115</p> <p>900 0.111</p> <p>950 0.107</p> <p>1000 0.104</p> <p>1050 0.101</p> <p>1100 0.098</p> <p>1150 0.095</p> <p>1200 0.092</p> <p>1250 0.09</p> <p>1300 0.088</p> <p>1350 0.086</p> <p>1400 0.084</p> <p>1450 0.082</p> <p>1500 0.081</p> <p>1550 0.079</p> <p>1600 0.078</p> <p>1650 0.076</p> <p>1700 0.075</p> <p>1750 0.074</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>
Dynamic viscosity of liquid sodium at different temperatures
<p><strong>Dynamic viscosity of liquid sodium at different temperatures</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>Sodium is a chemical element. It is a soft, silvery-white, highly reactive metal. Many salts of sodium are highly water-soluble: sodium ions have been leached by the action of water from the Earth's minerals over eons, and thus sodium and chlorine are the most common dissolved elements by weight in the oceans. Sodium metal can be easily cut with a knife and is a good conductor of electricity and heat because it has only one electron in its valence shell, resulting in weak metallic bonding and free electrons, which carry energy. Due to having low atomic mass and large atomic radius, sodium is third-least dense of all elemental metals and is one of only three metals that can float on water, the other two being lithium and potassium. The melting and boiling points of sodium are lower than those of lithium but higher than those of the heavier alkali metals potassium, rubidium, and caesium, following periodic trends down the group. Metallic sodium is generally less reactive than potassium and more reactive than lithium.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>200 0.451</p> <p>250 0.387</p> <p>300 0.341</p> <p>350 0.306</p> <p>400 0.278</p> <p>450 0.255</p> <p>500 0.237</p> <p>550 0.221</p> <p>600 0.208</p> <p>650 0.196</p> <p>700 0.186</p> <p>750 0.177</p> <p>800 0.17</p> <p>850 0.163</p> <p>900 0.156</p> <p>950 0.151</p> <p>1000 0.146</p> <p>1050 0.141</p> <p>1100 0.137</p> <p>1150 0.133</p> <p>1200 0.129</p> <p>1250 0.126</p> <p>1300 0.123</p> <p>1350 0.12</p> <p>1400 0.117</p> <p>1450 0.115</p> <p>1500 0.113</p> <p>1550 0.11</p> <p>1600 0.108</p> <p>1650 0.106</p> <p>1700 0.105</p> <p>1750 0.103</p> <p>1800 0.101</p> <p>1850 0.1</p> <p>1900 0.098</p> <p>1950 0.097</p> <p>2000 0.096</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>
Dynamic viscosity of liquid lithium at different temperatures
<p><strong>Dynamic viscosity of liquid lithium at different temperatures</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 viscosity of a fluid is a measure of its resistance to deformation at a given rate. For liquids, it corresponds to the informal concept of "thickness": for example, syrup has a higher viscosity than water. Viscosity quantifies the internal frictional force between adjacent layers of fluid that are in relative motion. For instance, when a viscous fluid is forced through a tube, it flows more quickly near the tube's axis than near its walls. In general, viscosity depends on a fluid's state, such as its temperature, pressure, and rate of deformation. However, the dependence on some of these properties is negligible in certain cases. For example, the viscosity of a Newtonian fluid does not vary significantly with the rate of deformation. The dynamic viscosity of the fluid, often simply referred to as the viscosity.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>200 0.566</p> <p>250 0.503</p> <p>300 0.453</p> <p>350 0.412</p> <p>400 0.379</p> <p>450 0.352</p> <p>500 0.328</p> <p>550 0.308</p> <p>600 0.29</p> <p>650 0.275</p> <p>700 0.261</p> <p>750 0.249</p> <p>800 0.238</p> <p>850 0.228</p> <p>900 0.219</p> <p>950 0.211</p> <p>1000 0.204</p> <p>1050 0.197</p> <p>1100 0.191</p> <p>1150 0.185</p> <p>1200 0.18</p> <p>1250 0.175</p> <p>1300 0.17</p> <p>1350 0.166</p> <p>1400 0.162</p> <p>1450 0.158</p> <p>1500 0.155</p> <p>1550 0.151</p> <p>1600 0.148</p> <p>1650 0.145</p> <p>1700 0.142</p> <p>1750 0.139</p> <p>1800 0.137</p> <p>1850 0.135</p> <p>1900 0.132</p> <p>1950 0.13</p> <p>2000 0.128</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>
Dynamic viscosity of liquid cesium at different temperatures
<p><strong>Dynamic viscosity of liquid cesium at different temperatures</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>This silvery metal with a golden cast is the most reactive and one of the softest of all metals. It melts just above room temperature. It is about half as abundant as lead and 70 times as abundant as silver. The primary difficulty associated with the production of pure cesium is that cesium is always found together with rubidium in nature and is also mixed with other alkali metals. Because cesium and rubidium are very similar chemically, their separation presented numerous problems before the advent of ion-exchange methods and ion-specific complexing agents such as crown ethers. Once pure salts have been prepared, it is a straightforward task to convert them to the free metal. Cesium metal is produced in rather limited amounts because of its relatively high cost. Cesium has application in thermionic power converters that generate electricity directly within nuclear reactors or from the heat produced by radioactive decay. Cesium is difficult to handle because it reacts spontaneously in air. If a metal sample has a large enough surface area, it can burn to form superoxides. Cesium superoxide has a more reddish cast. Cesium is the most electropositive and most alkaline element, and thus, more easily than all other elements, it loses its single valence electron and forms ionic bonds with nearly all the inorganic and organic anions. Rubidium and cesium are miscible in all proportions and have complete solid solubility.</p> <p>Temperature (degrees Celsius), Dynamic viscosity (grams per meter per second)</p> <p>50 0.598</p> <p>100 0.469</p> <p>150 0.389</p> <p>200 0.334</p> <p>250 0.294</p> <p>300 0.264</p> <p>350 0.24</p> <p>400 0.221</p> <p>450 0.206</p> <p>500 0.192</p> <p>550 0.181</p> <p>600 0.171</p> <p>650 0.163</p> <p>700 0.156</p> <p>750 0.149</p> <p>800 0.143</p> <p>850 0.138</p> <p>900 0.134</p> <p>950 0.129</p> <p>1000 0.125</p> <p>1050 0.122</p> <p>1100 0.119</p> <p>1150 0.116</p> <p>1200 0.113</p> <p>1250 0.11</p> <p>1300 0.108</p> <p>1350 0.106</p> <p>1400 0.104</p> <p>1450 0.102</p> <p>1500 0.1</p> <p>1550 0.098</p> <p>1600 0.097</p> <p>1650 0.095</p> <p>1700 0.094</p> <p>1750 0.092</p> <p>1800 0.091</p> <p>1850 0.090</p> <p>1900 0.089</p> <p>1950 0.088</p> <p>2000 0.086</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>
Structural Dynamics of an Excited Donor-Acceptor Complex from Ultrafast Polarized Infrared Spectroscopy, Molecular Dynamics Simulations, and Quantum Chemical Calculations
<p>The files contains all the data that are shown in the figures of the article:</p> <p>Rumble, C.; Vauthey, E. Structural Dynamics of an Excited Donor-Acceptor Complex from Ultrafast Polarized Infrared Spectroscopy, Molecular Dynamics Simulations, and Quantum Chemical Calculations. Phys. Chem. Chem. Phys. 21 (2019). 10.1039/C9CP00795D</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.