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3,139 results for “fits”
Frankenstein fits
<p>Frankenstein brightness profiles, visibility fits and pseudo-2D images for interferometric datasets. Current datasets are: </p> <p>- Taurus survey (see <a href="https://ui.adsabs.harvard.edu/abs/2018ApJ...869...17L/abstract">Long et al. 2018</a>, <a href="https://ui.adsabs.harvard.edu/abs/2019ApJ...882...49L/abstract">2019</a>): 23 disks (Jennings et al. accepted - <a href="http://arxiv.org/abs/2206.11308">arXiv</a>) </p> <p>- DSHARP survey (see <a href="https://ui.adsabs.harvard.edu/abs/2018ApJ...869L..41A/abstract">Andrews et al. 2018</a>): 20 disks (Jennings et al. 2022 - <a href="https://ui.adsabs.harvard.edu/abs/2022MNRAS.509.2780J/exportcitation">ADS</a>) </p> <p>The <em>.fits</em> pseudo-2D image of each frank brightness profile is reprojected according to the source geometry (inclination, PA), which is given in the header of the corresponding <em>*_visibility_fit.txt </em>file. The <em>.fits</em> image centers the profile at (dRA, dDec) = (0, 0).</p> <p>Please cite the linked paper if using fits from that work, thanks! </p> <p>Frankenstein is on <a href="https://github.com/discsim/frank">GitHub</a> and <a href="https://discsim.github.io/frank/">Read the Docs</a>.</p>
Experiments with Frequency Fitness Assignment in a (1+1) EA on the Traveling Salesperson Problem
<p><strong>1. Introduction</strong></p> <p>The implementation and experimental results of the (1+1) EA with and without Frequency Fitness Assignment (FFA) to solve the <code>EUC_2D</code> Traveling Salesperson Problem (TSP) instances from <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">TSPLIB</a>.</p> <p>A TSP is defined by a fully-connected weighted graph of <code>n</code> cities. The goal is to find the overall shortest tour that visits each cities exactly once and returns to its starting point. The TSP is NP-hard. We consider 18 symmetric Euclidean instances from the well-known <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">TSPLIB</a>.</p> <p>Solutions in our work are stored in the path representation, where such a tour is encoded as a permutation <code>x</code> of the numbers <code>1</code> to <code>n</code>, each identifying a city. If a city appears at index <code>j</code> in the permutation <code>x</code>, then it will be the <code>j</code><sup>th</sup> city to be visited. This means that a tour <code>x</code> will pass the following edges: <code>(x[1], x[2])</code>, <code>(x[2], x[3])</code>, <code>(x[3], x[4])</code>, … <code>(x[n-1], x[n])</code>, <code>(x[n], x[1])</code>.</p> <p>The (1+1) EA is the most basic evolutionary algorithm and also be considered as a randomized local search. It starts with one random solution/permutation <code>xc</code> and computes its length <code>yc=f(xc)</code>. In each iteration, it applies a unary search operator <code>op</code> to obtain a new tour <code>xn=op(xc)</code> and computes its length <code>yn=f(xn)</code>. If <code>yn<=yc</code>, then it will accept the new tour and set <code>xn=xn</code> and <code>yc=yn</code>.</p> <p>FFA is a fitness assignment process that takes place before this last step in the EA. We integrate FFA into the (1+1) EA and obtain the (1+1) FEA. This algorithm uses an additional table <code>H</code> which counts, for any tour length <code>y</code>, how often it has been seen during the search so far. After the new tour <code>xn</code> is created and its objective value <code>yn</code> is computed, the (1+1) FEA sets <code>H[yc] = H[yc] + 1</code> and <code>H[yn] = H[yn] + 1</code>. It will accept <code>xn</code> if and only if <code>H[yn] <= H[yc]</code> and, only in this case, set <code>xn=xn</code> and <code>yc=yn</code>.</p> <p>We apply both EAs with two operators. <code>swap</code> exchanges two randomly chosen cities in the permutation. <code>reverse</code> reverses a randomly chosen subsequence of the tour.</p> <p><strong>2. Directory Structure</strong></p> <p>This archive contains the following directories:</p> <ul> <li><code>results_and_evaluation</code> contain the results of two experiments as well as their evaluation. <ul> <li><code>performance</code> contains the results and evaluation of the main experiment, namely the 21 runs on 18 <code>EUC_2D</code> Traveling Salesperson Problem (TSP) instances from <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">TSPLIB</a>. <ul> <li><code>results</code> is the directory with the log files</li> <li><code>evaluation</code> is a folder with the extracted evaluation and figures</li> <li><code>evaluation.py</code> is a Python script that generates all the files in <code>evaluation</code> from the data it finds in <code>results</code>. It requires the <a href="https://thomasweise.github.io/moptipy"><code>moptipy</code></a> package being installed for running.</li> </ul> </li> <li><code>H</code> contains the results of the experiment conducting single runs on the instances and gathering the data of the frequency table <code>H</code> at different objective function evaluations in the log files. <ul> <li><code>results</code> is the directory with the log files</li> <li><code>evaluation</code> is a folder with the extracted evaluation and figures</li> <li><code>evaluation.py</code> is a Python script that generates all the files in <code>evaluation</code> from the data it finds in <code>results</code>. It requires the <a href="https://thomasweise.github.io/moptipy"><code>moptipy</code></a> package being installed for running.</li> </ul> </li> </ul> </li> <li><code>source</code> contains the Python source codes needed to run the <code>performance</code> experiment. <ul> <li><code>moptipy</code> is a local copy of the <a href="https://thomasweise.github.io/moptipy"><code>moptipy</code></a> package used for our experiment.</li> <li><code>tsplib</code> contains the <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">TSPLIB</a> data. This includes the instances used in our experiments as files in text format with suffix <code>.tsp</code>. If an optimal tour is given, it is stored in a text format file with suffix <code>.opt.tour</code> and name prefix identical to the instance file. In other words, the file <code>eil51.tsp</code> contains the TSP instance <code>eil51</code> and the file <code>eil51.opt.tour</code> contains the corresponding optimal tour. Both the TSP instances and optimal tours can be downloaded from <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp/">http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp/</a>. We also include the documentation of TSPLIB in file <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp95.pdf"><code>tsp95.pdf</code></a> documenting them. We further include the <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/TSPFAQ.html">TSPLIB FAQ</a> both as HTML and PDF file (<code>tsplib_faq.html</code> and <code>tsplib_faq.pdf</code>) and the <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/STSP.html">list of known optimal tour lengths</a> as HTML and PDF file (<code>optimal_tour_lengths_of_symmetric_tsps.html</code>, <code>optimal_tour_lengths_of_symmetric_tsps.pdf</code>). Notice that, while the TSP instances we used are Euclidean, all distances are converted to integers as prescribed by the <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp95.pdf">documentation</a>.</li> </ul> </li> </ul> <p><strong>3. What algorithms are included in this experiment?</strong></p> <p>We implement the simple local search with (1+1) EA with and without Frequency Fitness Assignment. We use the common path representation for the TSP with <code>n</code> cities, which encodes each solution as a permutation of the numbers <code>1..n</code>. The value <code>i</code> at position <code>j</code>, i.e., <code>x[j] = i</code>, in such a permutation indicates that the <code>j</code><sup>th</sup> city to be visited by <code>i</code>. We implement two search operators, namely <code>reverse</code>, which reverses a subsequence of the tour, and <code>swap</code> which swaps two cities.</p> <ul> <li>(1+1) EA <ul> <li>with <code>swap</code> operator</li> <li>with <code>reverse</code> operator</li> </ul> </li> <li>(1+1) FEA, i.e., the (1+1) EA with Frequency Fitness Assignment (FFA) <ul> <li>with <code>swap</code> operator</li> <li>with <code>reverse</code> operator</li> </ul> </li> </ul> <p><strong>4. How to Run the Experiment</strong></p> <p>First, you must make sure to have all the dependencies installed that this program requires. You can do this by executing the following command in the terminal:</p> <pre><code>pip install matplotlib numba numpy pandas psutil scikit-learn</code></pre> <p>Now enter the <code>source</code> directory, i.e., the directory containing the <code>run.py</code> file, in your terminal. Depending on your system configuration and whether you run Windows or Linux, you can start the program with <em>one</em> of the commands below. (If running the first command returns with an error, just try the next one in the list.)</p> <ul> <li><code>python3 -m run</code></li> <li><code>python -m run</code></li> <li><code>python run.py</code></li> <li><code>python3 run.py</code></li> </ul> <p>Then the experiment will run. It will automatically create a sub-folder <code>results</code> in <code>source</code> and place all log files that are generated into it. Be careful: The experiment will take a long time. However, if you have multiple CPUs, you can simply start several instances of this program in independent terminals. Each instance will then conduct different runs. This also works if this folder is shared over the network, in which case you can run multiple processes on multiple PCs.</p> <p>Side note: This experiment uses the <a href="https://thomasweise.github.io/moptipy"><code>moptipy</code></a> package for implementing its algorithms, running the experiments, and gathering their results. If you want to install <code>moptipy</code> on your system instead of using the version supplied here, you can install it via <code>pip install moptipy</code>.</p> <p><strong>5. Literature</strong></p> <ul> <li>Frequency Fitness Assignment (FFA): <ol> <li>Thomas Weise, Zhize Wu, Xinlu Li, and Yan Chen. Frequency Fitness Assignment: Making Optimization Algorithms Invariant under Bijective Transformations of the Objective Function Value. <em>IEEE Transactions on Evolutionary Computation</em> 25(2):307–319. April 2021. Preprint available at <a href="http://arxiv.org/abs/2001.01416">arXiv:2001.01416v5</a> [cs.NE] 15 Oct 2020. doi:<a href="http://dx.doi.org/10.1109/TEVC.2020.3032090">10.1109/TEVC.2020.3032090</a>. Experimental results and source code are available at doi:<a href="http://doi.org/10.5281/zenodo.3899474">10.5281/zenodo.3899474</a>.</li> <li>Thomas Weise, Zhize Wu, Xinlu Li, Yan Chen, and Jörg Lässig. Frequency Fitness Assignment: Optimization without Bias for Good Solutions can be Efficient. <a href="https://arxiv.org/abs/2112.00229v4">arXiv:2112.00229v4</a> [cs.NE] 25 May 2022.</li> <li>Thomas Weise, Mingxu Wan, Ke Tang, Pu Wang, Alexandre Devert, and Xin Yao. Frequency Fitness Assignment. <em>IEEE Transactions on Evolutionary Computation (IEEE-EC)</em> 18(2):226-243, April 2014. doi:<a href="http://dx.doi.org/10.1109/TEVC.2013.2251885">10.1109/TEVC.2013.2251885</a>.</li> <li>Thomas Weise, Xinlu Li, Yan Chen, and Zhize Wu. Solving Job Shop Scheduling Problems Without Using a Bias for Good Solutions. In <em>Genetic and Evolutionary Computation Conference Companion (GECCO’21 Companion),</em> July 10-14, 2021, Lille, France. ACM, New York, NY, USA. ISBN 978-1-4503-8351-6. doi:<a href="http://doi.org/10.1145/3449726.3463124">10.1145/3449726.3463124</a>.</li> <li>Thomas Weise, Yan Chen, Xinlu Li, and Zhize Wu. Selecting a diverse set of benchmark instances from a tunable model problem for black-box discrete optimization algorithms. <em>Applied Soft Computing Journal (ASOC)</em>, 92:106269, June 2020. doi:<a href="http://dx.doi.org/10.1016/j.asoc.2020.106269">10.1016/j.asoc.2020.106269</a>.</li> <li>Thomas Weise, Mingxu Wan, Ke Tang, and Xin Yao. Evolving Exact Integer Algorithms with Genetic Programming. In <em>Proceedings of the IEEE Congress on Evolutionary Computation (CEC’14), Proceedings of the 2014 World Congress on Computational Intelligence (WCCI’14)</em>, pages 1816-1823, Beijing, China, July 6-11, 2014. Los Alamitos, CA, USA: IEEE Computer Society Press. ISBN: 978-1-4799-1488-3. doi:<a href="http://dx.doi.org/10.1109/CEC.2014.6900292">10.1109/CEC.2014.6900292</a>.</li> </ol> </li> <li>Traveling Salesperson Problem (TSP): <ol> <li>Pedro Larrañaga, Cindy M. H. Kuijpers, Roberto H. Murga, I. Inza, and S. Dizdarevic. Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators. <em>Artificial Intelligence Review,</em> 13(2):129–170, April 1999. Kluwer Academic Publishers, The Netherlands. doi:<a href="https://doi.org/10.1023/A:1006529012972">10.1023/A:1006529012972</a>.</li> <li>Gerhard Reinelt. TSPLIB — A Traveling Salesman Problem Library. <em>ORSA Journal on Computing</em> 3(4):376-384. 1991. <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/</a>.</li> <li>Gerhard Reinelt. TSPLIB95. 1995. Heidelberg, Germany: Universität Heidelberg, Institut für Angewandte Mathematik. <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp95.pdf">http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/tsp95.pdf</a>.</li> <li>Thomas Weise, Raymond Chiong, Ke Tang, Jörg Lässig, Shigeyoshi Tsutsui, Wenxiang Chen, Zbigniew Michalewicz, and Xin Yao. Benchmarking Optimization Algorithms: An Open Source Framework for the Traveling Salesman Problem. <em>IEEE Computational Intelligence Magazine (CIM)</em> 9(3):40-52, August 2014. doi:<a href="http://dx.doi.org/10.1109/MCI.2014.2326101">10.1109/MCI.2014.2326101</a>.</li> <li>Eugene Leighton Lawler, Jan Karel Lenstra, Alexander Hendrik George Rinnooy Kan, and David B. Shmoys. <em>The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization.</em> Wiley Interscience. 1985.</li> <li>David Lee Applegate, Robert E. Bixby, Vasek Chvatal, and William John Cook. <em>The Traveling Salesman Problem: A Computational Study.</em> Princeton University Press. 2007.</li> <li>Gregory Z. Gutin and Abraham P. Punnen, editors. <em>The Traveling Salesman Problem and its Variations.</em> Volume 12 of Combinatorial Optimization. Kluwer Academic Publishers. 2002. doi:<a href="https://dx.doi.org/10.1007/b101971">10.1007/b101971</a>.</li> </ol> </li> <li>Software: <ol> <li>The Metaheuristic Optimization in Python Package <a href="https://thomasweise.github.io/moptipy"><code>moptipy</code></a></li> </ol> </li> </ul> <p><strong>6. License</strong></p> <p>The files in this repository are under the <a href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</a>, with the exception of the files of <a href="http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/">TSPLIB</a> in directory <code>source/tsplib</code>, which are under copyright of their respective owner (we believe that they are in the public domain, as they are provided by many sources, included in many software packages under various open source licenses, and on many websites). The license is contained as file <code>LICENSE</code> in this archive.</p>
Defensive mutualists affect outcross pollen transfer and male fitness in their host plant
<p>Ant guards can increase plant fitness by deterring herbivores, but they may also reduce it by interfering with pollination. While ant impacts on herbivory have been well-studied, much less is known about their impacts on pollinators and associated consequences for plant pollination, particularly pollen transfer dynamics and outcrossing/selfing rates. We used field experiments to quantify the effect of ant guards on pollinator community composition, frequency and duration of flower visits, and cascading effects on outcrossing pollen transfer and pollen exports in Turnera velutina (Passifloraceae). Although ant patrolling did not affect pollinator community composition or visitation frequency, it decreased flower visit duration and the time pollinators spent foraging inside flowers. Such behavioural changes resulted in reduced pollen deposition on stigmas, decreased pollen exports (a proxy for male fitness) and significantly doubled outcross pollen transfer. This study contributes to our understanding of how nonpollinator mutualists can shape plant reproductive processes. We discuss the downstream effects that variation in biotic defences, such as rewards for guarding ants, can have on plant pollen transfer patterns and fitness. In conclusion, guarding ants influence pollen transfer patterns in Turnera velutina, increasing outcrossing in a self-compatible species at the cost of male fitness. We show how non-pollinators, such as defensive ant mutualists, can shape plant reproductive traits and discuss the consequences these interactions may have for plant mating systems.</p>
Active season body mass patterns of Little Brown Bats and Northern Myotis: Raw and fitted mass values, environmental conditions and inflection point estimates
<p><span>Animals are expected to adjust their behavioural patterns to improve fitness outcomes, such as fecundity or offspring survival. For long-lived hibernators, decisions made in each annual cycle may reflect considerations not just for concurrent survival and reproduction, but also the pressure to maximize overwinter survival and future reproductive success. We examined how these elements manifest themselves in the body mass variation patterns of North American northern latitude temperate bats, whose size and roosting habits present considerable monitoring challenges. We characterized and compared the summer and fall mass variation patterns of little brown myotis (<em>Myotis lucifugus</em>) and northern myotis (<em>M. septentrionalis</em></span><span>) from a historic dataset. In summer, the estimated date of parturition was strongly associated with spring foraging conditions (low wind, low precipitation, warm temperatures), and mass gain associated with female reproduction conferred considerable differentiation between the mass variation patterns of females and males. In fall, differences were most apparent among species, although adults exhibited a greater capacity for rapid mass gain than juveniles. These results demonstrate how reproductive constraints and interannual survival have important influences on the behaviour of temperate bats. Future work should seek to quantify the fitness benefits of patterns identified in this study, such as the rate of prehibernation mass gain.</span></p>
Hybridization alters the shape of the genotypic fitness landscape, increasing access to novel fitness peaks during adaptive radiation
<p>Estimating the complex relationship between fitness and genotype or phenotype (i.e. the adaptive landscape) is one of the central goals of evolutionary biology. However, adaptive walks connecting genotypes to organismal fitness, speciation, and novel ecological niches are still poorly understood and processes for surmounting fitness valleys remain controversial. One outstanding system for addressing these connections is a recent adaptive radiation of ecologically and morphologically novel pupfishes (a generalist, molluscivore, and scale-eater) endemic to San Salvador Island, Bahamas. We leveraged whole-genome sequencing of 139 hybrids from two independent field fitness experiments to identify the genomic basis of fitness, estimate genotypic fitness networks, and measure the accessibility of adaptive walks on the fitness landscape. We identified 132 SNPs that were significantly associated with fitness in field enclosures. Six out of the 13 regions most strongly associated with fitness contained differentially expressed genes and fixed SNPs between trophic specialists; one gene (<em>mettl21e</em>) was also misexpressed in lab-reared hybrids, suggesting a potential intrinsic genetic incompatibility. We then constructed genotypic fitness networks from adaptive alleles and show that scale-eating specialists are the most isolated of the three species on these networks. Intriguingly, introgressed and<em> de novo</em> variants reduced fitness landscape ruggedness as compared to standing variation, increasing the accessibility of genotypic fitness paths from generalist to specialists. Our results suggest that adaptive introgression and <em>de novo</em> mutations alter the shape of the fitness landscape, providing key connections in adaptive walks circumventing fitness valleys and triggering the evolution of novelty during adaptive radiation.</p>
Spatz neutron reflectometer commissioning data and corresponding models to fits
<p>This is the data to the hot commissioning of the Spatz neutron reflectometer at the OPAL Research Reactor, ANSTO. The data also contains the Jupyter notebook to reduce the data to give complete reflectivity profile and contains the models used to fit the data within refnx using the GUI option. </p>
Fitness of gnotobiotic Rhodnius prolixus nymphs
<p>Kissing bugs (Hempitera: Reduviidae) are obligately and exclusively blood feeding insects. Vertebrate blood is thought to provide insufficient B vitamins to insects, which rely on obligate symbiotic relationships with bacteria that provision these nutrients. Kissing bugs harbor environmentally acquired bacteria in their gut lumen, without which they are unable to develop to adulthood. Early experiments identified a single bacterial species, <em>Rhodococcus rhodnii</em>, as a symbiont of <em>Rhodnius prolixus</em>, but modern studies of the kissing bug microbiome suggest that <em>R. rhodnii</em> is not always present or abundant in wild-caught individuals. We asked whether <em>R. rhodnii</em> or other bacteria alone could function as symbionts of <em>R. prolixus</em>. Bacteria-free (axenic) insects were produced whose microbiome could be experimentally manipulated to produce insects with known microbiomes (gnotobiotic). We found that gnotobiotic insects harboring <em>R. rhodnii</em> alone developed faster, had higher survival, and laid more eggs than gnotobiotic <em>R. prolixus </em>harboring other bacterial monocultures, including other described symbionts of kissing bugs and several related <em>Rhodococcus </em>species. <em>R. rhodnii</em> grew to high titer in the guts of <em>R. prolixus</em> while other tested species were found at much lower abundance. <em>Rhodococcus </em>species tested had nearly identical B vitamin biosynthesis genes, and dietary supplementation of B vitamins had a relatively minor effect on development and survival of gnotobiotic <em>R. prolixus</em>. Our results indicate that <em>R. prolixus</em> have a higher fitness when harboring <em>R. rhodnii</em> than other bacteria tested, and that symbiont B vitamin synthesis is likely a necessary but not sufficient function of gut bacteria in kissing bugs.</p>
Does perception of female cues modulate male short-term fitness components in Drosophila melanogaster?
<p class="MsoNormal"><span>Phenotypic plasticity in reproductive behaviour can be a strong driver of individual fitness. In species with high intra-sexual competition, changes in socio-sexual context can trigger quick adaptive plastic responses in males. In particular, a recent study in the vinegar fly (<em>Drosophila melanogaster</em>) shows that males derive net fitness benefits from being shortly exposed to female cues ahead of access to mating (termed <em>sexual perception</em>), but the underlying mechanisms of this phenomenon remain unknown. Here, we investigated the short-term effects of female perception on male pre- and post-copulatory components of reproductive performance: a) mating success, b) mating latency and duration, c) sperm competitiveness, and d) ejaculate effects on female receptivity and oviposition rate. We found that brief sexual perception increased mating duration, but had no effect on the main pre- or post-copulatory fitness proxies recorded. This may suggest that male fitness benefits from responses to sexual perception do not play out in the short-term, but we discuss alternative explanations and future avenues of research. </span></p>
MARCI Mosaics from MY 29 to MY 35 with the ellipse of best fit drawn
<p>Videos showing the HSV ellipse fit tracking for MY 29 to MY 35 from early spring to late spring using MARCI mosacis </p>
The diverse effects of phenotypic dominance on hybrid fitness
<p>When divergent populations interbreed, their alleles are brought together in hybrids. In the initial F1 cross, most divergent loci are heterozygous. Therefore, F1 fitness can be influenced by dominance effects that could not have been selected to function well together. We present a systematic study of these F1 dominance effects by introducing variable phenotypic dominance into Fisher's geometric model. We show that dominance often reduces hybrid fitness, which can generate optimal outbreeding followed by a steady decline in F1 fitness, as is often observed. We also show that "lucky" beneficial effects sometimes arise by chance, which might be important when hybrids can access novel environments. We then show that dominance can lead to violations of Haldane's Rule (reduced fitness of the heterogametic F1) but strengthens Darwin's Corollary (F1 fitness differences between cross directions). Taken together, results show that the effects of dominance on hybrid fitness can be surprisingly difficult to isolate because they often resemble the effects of uniparental inheritance or expression. Nevertheless, we identify a pattern of environment-dependent heterosis that only dominance can explain, and for which there is some suggestive evidence. Our results also show how existing data set upper bounds on the size of dominance effects. These bounds could explain why additive models often provide good predictions for later-generation recombinant hybrids, even when dominance qualitatively changes outcomes for the F1.</p>
Diurnal variation in Uchikomi fitness test performance: Influence of warm-up protocols
<table> <tbody> <tr> <td>group</td> <td>time</td> <td>total scores</td> <td>uft(a+b)</td> <td>heart rate</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>31</td> <td>11</td> <td>183.83</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>178.17</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>27</td> <td>9</td> <td>175.17</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>179.33</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>179.67</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>15</td> <td>182.50</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>181.67</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>15</td> <td>182.50</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>178.17</td> </tr> <tr> <td>NWU</td> <td>morning</td> <td>42</td> <td>14</td> <td>179.67</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>46</td> <td>16</td> <td>185.17</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>43</td> <td>15</td> <td>186.67</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>49</td> <td>17</td> <td>177.33</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>41</td> <td>14</td> <td>182.67</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>49</td> <td>17</td> <td>179.17</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>48</td> <td>16</td> <td>187.00</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>41</td> <td>14</td> <td>158.50</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>48</td> <td>16</td> <td>187.00</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>43</td> <td>15</td> <td>186.67</td> </tr> <tr> <td>NWU</td> <td>evening</td> <td>49</td> <td>17</td> <td>179.17</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>38</td> <td>14</td> <td>183.83</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>53</td> <td>22</td> <td>187.00</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>33</td> <td>12</td> <td>175.17</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>52</td> <td>19</td> <td>188.67</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>41</td> <td>14</td> <td>173.00</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>68</td> <td>30</td> <td>176.67</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>49</td> <td>18</td> <td>166.67</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>68</td> <td>30</td> <td>176.67</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>53</td> <td>22</td> <td>187.00</td> </tr> <tr> <td>FWU</td> <td>morning</td> <td>41</td> <td>14</td> <td>173.00</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>44</td> <td>16</td> <td>183.83</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>55</td> <td>20</td> <td>188.50</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>51</td> <td>16</td> <td>172.50</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>62</td> <td>27</td> <td>185.17</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>63</td> <td>27</td> <td>173.83</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>68</td> <td>25</td> <td>185.83</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>52</td> <td>21</td> <td>156.83</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>68</td> <td>25</td> <td>185.83</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>55</td> <td>20</td> <td>188.50</td> </tr> <tr> <td>FWU</td> <td>evening</td> <td>63</td> <td>27</td> <td>173.83</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>55</td> <td>19</td> <td>169.50</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>62</td> <td>23</td> <td>173.50</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>55</td> <td>19</td> <td>169.50</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>56</td> <td>19</td> <td>179.33</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>57</td> <td>20</td> <td>168.33</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>68</td> <td>24</td> <td>176.33</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>50</td> <td>18</td> <td>158.67</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>68</td> <td>24</td> <td>176.33</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>62</td> <td>23</td> <td>173.50</td> </tr> <tr> <td>SWU</td> <td>morning</td> <td>57</td> <td>20</td> <td>168.33</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>61</td> <td>21</td> <td>171.67</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>66</td> <td>24</td> <td>174.50</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>60</td> <td>20</td> <td>171.00</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>61</td> <td>22</td> <td>180.33</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>57</td> <td>20</td> <td>167.83</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>68</td> <td>23</td> <td>176.33</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>54</td> <td>18</td> <td>160.83</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>70</td> <td>24</td> <td>177.00</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>62</td> <td>23</td> <td>173.50</td> </tr> <tr> <td>SWU</td> <td>evening</td> <td>57</td> <td>20</td> <td>168.33</td> </tr> </tbody> </table>
Flexibility solutions - making the power grid fit for the future
<p><b>Abstract</b></p><p class="dhik-abstract-content">The competence center Business Engineering presents different projects. QualyGridS: flexible hydrogen production, business ecosystem design; PACE: optimized operation of FC µCHPs, operations research, market analysis; - Multiple Benefits: valuation of MB of energy efficiency measures; smart services, CE, LCA</p><p></p><p><b>Weitere Beiträge aus dem DHIK-Forum 2022 auf Zenodo:</b></p><p class="dhik-session-list"></p><ul><li>Session #1: Viktor Sigrist: Internationalisierung - Partnerschaften für den Ausbau von Forschung und Entwicklung (DOI:<a href="https://zenodo.org/record/7123701">10.5281/zenodo.7123701</a>)</li><li>Session #2: Dieter Leonhard: DHIK- Strategien der internationalen Zusammenarbeit in Forschung und Lehre (DOI:<a href="https://zenodo.org/record/7123456">10.5281/zenodo.7123456</a>)</li><li>Session #3: Stephen Wittkopf: Wissens- und Innovationstransfer - Interdisziplinäre Zusammenarbeit mit Unternehmen und Institutionen (DOI:<a href="https://zenodo.org/record/7025707">10.5281/zenodo.7025707</a>)</li><li>Session #4: Xiao Feng: CDHAW - Chinesisch-Deutsche Hochschule für Angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123458">10.5281/zenodo.7123458</a>)</li><li>Session #5: Antonio Pita und Isabel Kreiner: Academy-Industry-Collaboration - Outreach Strategy (DOI:<a href="https://zenodo.org/record/7123460">10.5281/zenodo.7123460</a>)</li><li>Session #6: Martin Sternberg: Promotionsrecht – aktueller Stand an deutschen Hochschulen für angewandte Wissenschaften (DOI:<a href="https://zenodo.org/record/7123757">10.5281/zenodo.7123757</a>)</li><li>Session #7: Adrian Derungs: Duo mit Innovationskraft - Zusammenspiel von Forschung und Wirtschaft in der Zentralschweiz (DOI:<a href="https://zenodo.org/record/7123767">10.5281/zenodo.7123767</a>)</li><li>Session #8: Theres Paulsen: Transdisziplinäre Forschung - komplexe gesellschaftliche Herausforderungen erfordern diverse Ansätze (DOI:<a href="https://zenodo.org/record/7123769">10.5281/zenodo.7123769</a>)</li><li>Session #9: Jörg Schneider: International research collaboration - New funding opportunities for universities of applied sciences (DOI:<a href="https://zenodo.org/record/7123771">10.5281/zenodo.7123771</a>)</li><li>Session #10: Cornelia Spycher und Matthew Whellens: Horizon Europe - overview of funding opportunities for your research and innovation (DOI:<a href="https://zenodo.org/record/7123773">10.5281/zenodo.7123773</a>)</li><li>Session #11: Janique Siffert: Eureka Eurostars - erfolgreiche Förderung für internationale Innovationsprojekte (DOI:<a href="https://zenodo.org/record/7123777">10.5281/zenodo.7123777</a>)</li><li>Session #12: Ludger Fischer: Energy Lab - ein Netzwerk für innovative Lösungen im Energiebereich (DOI:<a href="https://zenodo.org/record/7123779">10.5281/zenodo.7123779</a>)</li><li>Session #13: Jörg Worlitschek: Thermal energy storage - heating the north, cooling the south (DOI:<a href="https://zenodo.org/record/7123781">10.5281/zenodo.7123781</a>)</li><li>Session #14: Jonas Mühlethaler: Neues DC Microgrid-Konzept – netzunabhängige Elektrifizierung in Entwicklungsländern (DOI:<a href="https://zenodo.org/record/7123783">10.5281/zenodo.7123783</a>)</li><li>Session #15: Tommy Claussen: Dekarbonisierung des Gebäudesektors - digitale Transformation in der Gebäudetechnik und im Gebäudemanagement (DOI:<a href="https://zenodo.org/record/7123785">10.5281/zenodo.7123785</a>)</li><li><b>Session #16: Christoph Imboden: Flexibility solutions - making the power grid fit for the future (<a href="#collapseTwo">Video</a>)</b></li><li>Session #17: Uwe Schulz: Spielerisches Sarnetz - Simulationen für die fossile Unabhängigkeit einer Ortschaft (DOI:<a href="https://zenodo.org/record/7123790">10.5281/zenodo.7123790</a>)</li><li>Session #18: Jana Koehler: Künstliche Intelligenz – Erfolg durch Erwünschtheit, Machbarkeit und Wirtschaftlichkeit (DOI:<a href="https://zenodo.org/record/7123792">10.5281/zenodo.7123792</a>)</li><li>Session #19: Rolf Kamps: KI in der Prävention - Befragungsmethoden und Schulungen trainieren, Krankheitserreger erkennen (DOI:<a href="https://zenodo.org/record/7123794">10.5281/zenodo.7123794</a>)</li><li>Session #20: Gwendolyne Pascua: Artificial Intelligence in Space - CIMON assisting astronauts on the International Space Station (DOI:<a href="https://zenodo.org/record/7123796">10.5281/zenodo.7123796</a>)</li><li>Session #21: Tobias Matter et.al.: Augmented Reality Soundscapes - mit maschinellem Lernen Klangkulissen von zukünftigen Bauvorhaben generieren (DOI:<a href="https://zenodo.org/record/7123798">10.5281/zenodo.7123798</a>)</li><li>Session #22: Angela Nicoara: Internet of Things - transforming businesses, people's lives and driving growth in the coming years (DOI:<a href="https://zenodo.org/record/7123800">10.5281/zenodo.7123800</a>)</li><li>Session #23: Adrian Koller: Feldrobotik - unermüdliche und zunehmend intelligentere Hilfe in der Landwirtschaft (DOI:<a href="https://zenodo.org/record/7123802">10.5281/zenodo.7123802</a>)</li><li>Session #24: Widar von Arx et.al.: Realisierung der Verkehrswende - Einfluss der Preispolitik in der Mobilität (DOI:<a href="https://zenodo.org/record/7124000">10.5281/zenodo.7124000</a>)</li><li>Session #25: Andreas Liebrich: Tourismusdateninfrastruktur - Was die Schweiz von Europa lernen kann (DOI:<a href="https://zenodo.org/record/7123806">10.5281/zenodo.7123806</a>)</li><li>Session #26: Frank Pöhlau und Stefan May: Find life on Mars - Schülerprojekte zur mobilien Robotik (DOI:<a href="https://zenodo.org/record/7123808">10.5281/zenodo.7123808</a>)</li><li>Session #27: Jiayun Shen: Open Innovation - Innovationsmanagement bei der Schweizerischen Post (DOI:<a href="https://zenodo.org/record/7123810">10.5281/zenodo.7123810</a>)</li><li>Session #28: Tobias Specker: Interkulturelles Management – innovative Konzepte zum Ausbau der China-Kompetenzen an Hochschulen (DOI:<a href="https://zenodo.org/record/7123812">10.5281/zenodo.7123812</a>)</li><li>Session #29: Elena Algorri: Swimming robots - exploring the unterwater from the surface (DOI:<a href="https://zenodo.org/record/7123814">10.5281/zenodo.7123814</a>)</li><li>Session #30: Sergio Camacho: Robotics and Digital Systems Engineering at the Tec de Monterrey (DOI:<a href="https://zenodo.org/record/7123816">10.5281/zenodo.7123816</a>)</li><li>Session #31: Thomas Dorn: Industrie 4.0 - Forschungskooperationen mit der CDHAW und der Tongji Universität Shanghai (DOI:<a href="https://zenodo.org/record/7123818">10.5281/zenodo.7123818</a>)</li><li>Session #32: Walter Reichert et.al.: Kollaboration und Unterstützung - Mobile Robotik und Exoskelette in der flexiblen Produktion (DOI:<a href="https://zenodo.org/record/7123820">10.5281/zenodo.7123820</a>)</li><li>Session #33: Louis Palmer: Solar Butterfly - climate pioneer world tour supported by HSLU (DOI:<a href="https://zenodo.org/record/7123822">10.5281/zenodo.7123822</a>)</li></ul><p></p>
Conservation implications of herbicides on seagrasses: sublethal glyphosate exposure decreases fitness in the endangered Zostera capensis
<p>Dataset containing morphological, biomass and chlorophyll responses of the seagrass, Zostera capensis, to sublethal glyphosate exposure over a 3 week exposure period.</p>
Fitness costs associated with a GABA receptor mutation conferring dieldrin resistance in Aedes albopictus
<p><span>Understanding the dynamics of insecticide resistance genes in mosquito populations is pivotal for a sustainable use of insecticides. Dieldrin resistance in <em>Aedes</em> <em>albopictus</em> is conferred by the alanine to serine substitution (A302S or <em>Rdl<sup>R</sup></em> allele) in the γ-aminobutyric acid (GABA) receptor encoded by the <em>Rdl</em> gene. On Reunion Island, dieldrin resistance was initially reported in natural <em>Ae</em>. <em>albopictus</em> populations sampled in 2008 despite the ban of dieldrin since 1994. To monitor insecticide resistance in <em>Ae</em>. <em>albopictus</em> on the island and to identify its drivers, we measured (i) the frequency of resistance alleles in 19 distinct natural populations collected between 2016 and 2017, (ii) fitness costs associated with dieldrin resistance in laboratory-controlled experiments, and (iii) the resistance conferred by </span><span><em>Rdl<sup>R</sup></em></span><span> to fipronil, an insecticide widely used on the island and reported to cross-react with </span><span><em>Rdl<sup>R</sup></em></span><span>. The results show a persistence of </span><span><em>Rdl<sup>R</sup></em></span><span> in <em>Ae</em>. <em>albopictus</em> natural populations at low frequencies. Among the measured life history traits, mortality in pre-imaginal stages, adults' survival as well as the proportion of egg-laying females were significantly affected in resistant mosquitoes. Finally, bioassays revealed resistance of </span><span><em>Rdl<sup>R</sup></em></span><span> mosquitoes to fipronil, suggesting that the use of fipronil <em>in</em> <em>natura</em> could select for the </span><span><em>Rdl<sup>R</sup></em></span><span> allele. This study shows that dieldrin resistance is persistent in natural mosquito populations likely as a result of combined effects between fitness costs associated with </span><span><em>Rdl<sup>R</sup></em></span><span> and selection exerted by cross-reacting environmental insecticides such as fipronil.</span></p>
Sib-mating enhances fitness in a haplodiploid beetle
<p>Inbreeding is generally avoided in animals due to the risk of inbreeding depression following an increase in homozygous deleterious alleles and loss of heterozygosity. Species that regularly inbreed challenge our understanding of the fitness effects of these risks. We investigated fitness consequences of extended inbreeding in the haplodiploid date-stone beetle, Coccotrypes dactyliperda. We hypothesized that continuous inbreeding could result in reduced fitness, while outbreeding would either increase fitness due to heterosis or lower fitness if co-adapted gene complexes are disrupted. We established three breeding treatments with beetles from two geographically separated populations: Sib-mating (inbreeding), and outbreeding within- and between-populations. Between-population outbreeding groups of both populations had lower fecundity and collapsed before the experiment ended, while sib-mated and within-population breeding groups persisted for ten generations. Sib-mated females had higher fecundity than within- and between-population outbreeding females. Inbreeding coefficients of sib-mated groups were higher than the other treatment groups, yet sib-mated beetles remained genetically polymorphic at the population level. Thus, there was no inbreeding depression, while crossing between distant populations led to outbreeding depression. Our findings are consistent with the life history of C. dactyliperda, in which sib-mating predominates within the date seed, but occasional within-population outbreeding may occur following local dispersal.</p>
Wmid-c506d4 - furniture fitting or attachment
An incomplete lead alloy probable decorative furniture fitting or attachment of probable Post Medieval dating (AD 1700 to AD 1900). The artefact is sub rectangular in shape, with both short ends being incomplete. The long edges are rounded. One short end has the remains of a circular perforation in the centre, with an internal diameter of 1.7 mm. The other short end is gradually tapering in width. In the centre is a recessed panel with raised floral decoration. An eighted petalled flower is either side of a smaller six petalled flower. The reverse of the artefact has been recessed in places. A large rectangular recessed panel is behind the tapering short end and a short vertical slot is present more in the middle of the artefact. For more information, please visit the online database record available at: https://finds.org.uk/database/artefacts/record/id/1071106 Source: Objaverse 1.0 / Sketchfab
Wmid-3a538c - Harness fitting
A copper alloy probable harness fitting dating to the Late Iron Age/Early Roman period circa 100 BC to 100 AD. The object has a slight curvature in profile. The upper face is slightly convex and the reverse is flat. It consists of a circular perforated loop at one end. This projects at 90 degrees from a larger broadly oval shaped loop. Below the oval loop is a triangular loop that then extends to a circular loop. Extending from the circular loop appears to be a further now incomplete triangular loop. This could suggest that originally the circular loop was once in the centre and the remaining triangular and oval loops were mirrored on the other side. The object has a well developed dark brown coloured smooth patina that has also developed over the broken terminal. For more details, please visit the database record available at: https://finds.org.uk/database/artefacts/record/id/1053202 Source: Objaverse 1.0 / Sketchfab
Iron fittings of a bucket from Zakrzówek
ID no.: MAK/K/514/15 Archaeological Museum in Kraków https://muzea.malopolska.pl/en/objects-list/1555 Digitalisation: RDW MIC, Virtual Małopolska project Source: Objaverse 1.0 / Sketchfab
068 Schwertgurtbeschlag / Sword belt fitting
# Fundort / Site Bergkamen, Kreis Unna (Germany) # Fundumstände / Circumstances of discovery Grab / Grave 2011 # Objekt / Object Eisen, Buntmetall, Silber / Iron, non-ferrous metal, silver Schwertgurtbeschlag Typ Civezzano / Sword belt fitting type Civezzano # Datierung / Dating 650–700 Frühmittelalter / Early Middle Ages Merowinger / Merovingians # Import Herstellungsort / Place of production: Süddeutschland / Southern Germany Herstellungszeit / Time of production: 650–700 # Fundverbleib / Repository Zentrales Fundarchiv der LWL-Archäologie für Westfalen, Münster (nicht öffentlich zugänglich) # 3-D-Modell / 3D model Fotokamera / Photo camera: Nikon D850 Modellberechnung / Model processing: Reality Capture Modell / Model: LWL-Archäologie für Westfalen/Florian Westphal Source: Objaverse 1.0 / Sketchfab
Variation and plasticity in life-history traits and fitness of wild Arabidopsis thaliana populations are not related to their genotypic and ecological diversity
<p>Despite its implications for population dynamics and evolution, the relationship between genetic and phenotypic variation in wild populations remains unclear. Here, we estimated variation and plasticity in life-history traits and fitness of the annual plant <em>Arabidopsis thaliana</em> in two common garden experiments that differed in environmental conditions. We used up to 306 maternal inbred lines from six Iberian populations characterized by low and high genotypic (based on whole-genome sequences) and ecological (vegetation type) diversity. Low and high genotypic and ecological diversity was found in edge and core Iberian environments, respectively. Given that selection is expected to be stronger in edge environments and that ecological diversity may enhance both phenotypic variation and plasticity, we expected genotypic diversity to be positively associated with phenotypic variation and plasticity. However, maternal lines, irrespective of the genotypic and ecological diversity of their population of origin, exhibited a substantial amount of phenotypic variation and plasticity for all traits. Furthermore, all populations harbored maternal lines with canalization (robustness) or sensitivity in response to harsher environmental conditions in one of the two experiments. Overall, we conclude that the environmental attributes of each population probably determine their genotypic diversity, but all populations maintain substantial phenotypic variation and plasticity for all traits, which represents an asset to endure in changing environments.</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.