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168 results for “Complex systems”
Simulation systems for: "Pore formation in complex biological membranes: torn between evolutionary needs"
<p>Simulation systems for the publication:</p> <div> <div> <div> <p>Leonhard J. Starke, Christoph Allolio, and Jochen S. Hub, <em>Pore formation in complex biological membranes: torn between evolutionary needs</em>, BioRxiv (2024), doi: <a href="https://doi.org/10.1101/2024.05.06.592649">10.1101/2024.05.06.592649</a></p> <p>Required software:<br>GROMACS Chain Coordinate, a modified GROMACS variant for pore formation across membranes or stalk formation between membranes: <a href="https://gitlab.com/cbjh/gromacs-chain-coordinate">https://gitlab.com/cbjh/gromacs-chain-coordinate</a></p> <p>See README_small.sh and README_large.sh files for instructions on how to run pulling simulations for inducing pores in the provided complex membrane models.</p> </div> </div> </div>
Graphic Illustration of Kelly Speer's Keynote Talk: Hosts, parasites, and microbiomes: A system for studying natural complexity in a changing world
<p><a href="https://lib.ku.edu/people/courtney-foat" target="_blank" rel="noopener">Courtney Foat</a>, Advisor for Strategic Initiatives & Organizational Engagement at the University of Kansas, graphically recorded and synthesized the Keynote Talk by Kelly Speer at the Digital Data 2024 Conference in Lawrence, Kansas in May of 2024. We include this resource, with permission, because of its relevance to our NSF-supported Workshop: Digital Collections Data and Tracking Disease.</p>
Dataset for Algorithms and Complexity for Counting Configurations in Steiner Triple Systems
<p>This dataset contains the classification of full n-line configurations (for all n <= 13, filename: "full_line_config_<n>.txt.gz") and w_3 configurations (for all w <= 16, filename: "w_3_config_<w>.txt.gz") together with the sizes of minimum generating sets. Each file lists "m<s>" so that s is the size of the minimum generating set of the subsequent configuration, which is denoted by writing the points of each of its lines row-wise. For example</p> <p>m3<br> 0 1 4<br> 0 2 6<br> 0 3 5<br> 1 2 5<br> 1 3 6<br> 2 3 4<br> 4 5 6</p> <p>is the Fano plane and its minimum generating set has size 3.</p> <p>Additionally, the file "fulllineconjecture.txt.gz" contains the 623 Steiner triple systems of order 25 (i.e., all rows which contain curly brackets) used in Theorem 7 in the paper below, followed by a row starting with 1 and then describing the number of occurrences of all 179 full n-line configurations for n <= 8, i.e., first the number of occurrences of Pasch configurations, then mitre configurations, then the 5 full 6-line configurations, the 19 full 7-line configurations, and finally the 153 full 8-line configurations contained in the STS(25) in the preceding row. The ordering follows the ordering within the files "full_line_config_<n>.txt.gz". This file is built so that omitting all lines with curly brackets is a valid gap code and results in a prove of said theorem (i.e., zgrep -v "{" fulllineconjecture.txt.gz | gap yields 180).</p> <p><br> Further details can be found in the corresponding publication</p> <p>"Algorithms and Complexity for Counting Configurations in Steiner Triple Systems"</p> <p>by Daniel Heinlein and Patric R. J. Östergård.</p> <p>All files are compressed with gzip.</p>
Data from: First records of complete annual cycles in water rails Rallus aquaticus show evidence of itinerant breeding and a complex migration system
<p>In water rails <em>Rallus aquaticus</em>, northern and eastern populations are migratory while southern and western populations are sedentary. Few details are known about the annual cycle of this elusive species. We studied movements and breeding in water rails from southernmost Norway where the species occurs year-round. Colour-ringed wintering birds occurred only occasionally at the study site in summer, and vice versa. Geolocator tracks revealed that wintering birds (n = 10) migrated eastwards in spring to breed on both sides of the Baltic Sea, whereas a single breeding bird from the study site wintered in north Italy. Ambient light records of geolocator birds further indicated that all but one incubated 2–4 clutches per season. By combining information on incubation and movement, we found evidence for itinerant breeding in three individual birds: After a first breeding attempt (one did not incubate), all moved 129–721 km to breed again. This behaviour is rarely recorded in birds and was unexpected because the water rail is described as monogamous with both parents caring for eggs and chicks. The study greatly improves our knowledge about the annual cycle and reproduction in water rails. However, more studies are warranted to evaluate the generality of our findings and causes of breeding itinerancy.</p>
Research data supporting: "Machine learning of microscopic structure-dynamics relationships in complex molecular systems"
<p>This repository contains the set of data and the code to reproduce the results shown in "Machine learning of microscopic structure-dynamics relationships in complex molecular systems" published on Machine Learning: Science and Technology (DOI: 10.1088/2632-2153/ad0fa5).</p>
Resilience assessment in complex natural systems
<p>Ecological resilience is the capability of an ecosystem to maintain the same structure and function and to avoid crossing catastrophic tipping points (i.e. irreversible regime shifts). While fundamental for management, concrete ways to estimate and interpret resilience in real ecosystems are still lacking. Here, we develop an empirical approach to estimate resilience based on the stochastic cusp model derived from catastrophe theory. The cusp model models tipping points derived from a cusp bifurcation. We extend cusp in order to identify the presence of stable and unstable states in complex natural systems. Our Cusp Resilience Assessment (CUSPRA) has three characteristics: i) it provides estimates on how likely a system is to cross a tipping point (in the form of a cusp bifurcation) characterized by hysteresis, ii) it assesses resilience in relation to multiple external drivers, and iii) it produces straightforward results for ecosystem-based management. We validate our approach using simulated data and demonstrate its application using empirical time-series of an Atlantic cod population and of marine ecosystems in the North Sea and the Mediterranean Sea. We show that CUSPRA is a powerful method to empirically estimate resilience in support of a sustainable management of our adapting ecosystems under global climate change.</p>
METHODS OF TRAINING AND ADAPTATION OF AI AGENTS IN COMPLEX PROCESS CONTROL SYSTEMS
<p>The article presents a study of modern methods of training and adaptation of artificial agents used in managing complex processes, which are characterized by a high level of uncertainty and the need for prompt response to changes. Key methodological approaches such as machine learning and neuroevolution are discussed. These approaches allow AI agents to accumulate knowledge about the behavior of systems continuously, analyze external changes, and adjust the management strategy depending on environmental conditions, which significantly increases their ability to predict and prevent possible failures in management.</p> <p>In the course of the study, models were considered that allow automating the execution of complex, multitasking processes, minimizing human intervention, and reducing the likelihood of errors. In addition, the presented methods provide high flexibility and scalability of systems, which is especially important in industrial and technological industries, where stability and reliability are critical. The results showed that AI agents with adaptive learning capabilities can increase operational efficiency while reducing costs and optimizing resource use. The conclusion highlights the prospects of using artificial intelligence to build highly autonomous control systems capable of responding to dynamic challenges, which opens up new horizons for automation and intellectual support in industrial production, logistics, and other key areas.</p> <p>Thus, the article makes a significant contribution to understanding the role of AI in management modernization, offering practical recommendations on the implementation of intelligent agents in real-world scenarios to increase productivity and sustainability.</p>
Project files provided as supporting information to the manuscript "Making sense of complex systems through resolution, relevance, and mapping entropy"
<p>README file to the project files provided as supporting information to the manuscript “Making sense of complex systems through resolution, relevance, and mapping entropy”</p> <p>Feb. 25, 2022</p> <p>Authors: Roi Holtzman, Marco Giulini and Raffaello Potestio</p> <p>==================================</p> <p>The dataset contains the following files:</p> <p>- A README file with the description of the pymap program for describing how different selections of *N* out of *n* degrees of freedom (mappings) affect the amount of information retained about a full data set.<br> - The pymap.py program<br> - The pymap.yml support file<br> - The data.tar tarball with the setup data<br> - The results.tar tarball with the output data<br> ===</p>
Code: The effects of model complexity on model output uncertainty in co-evolved coupled natural–human systems
<p>This is the code archive for the publication "The effects of model complexity on model output uncertainty in co-evolved coupled natural–human systems" in Earth's Future.</p> <p>Abstract:</p> <p>Studies have recently focused on using coupled natural–human systems (CNHS) to inform policymaking. However, model uncertainty can increase with model complexity and affect the variance of the model outcomes. Therefore, this study explores an uncertainty analysis of coupled hydrological and human decision models to better evaluate CNHS modeling properties. Five coupled models are proposed with different model complexities for human behavior settings (i.e., model structure and the number of calibrated parameters): one static, two adaptive, and two learning adaptive. Learning adaptive models (the most complex) have both a learning component (capturing long-term trends) and an adaptive component (capturing short-term variations), while adaptive models omit the learning component. The static model is the simplest, without learning or adaptive components. Applying the law of total variance, the model output uncertainty is decomposed into three sources: (1) climate change scenario uncertainty, (2) climate internal variability, and (3) different model configurations with parameter sets or model structures that are equally capable of producing similar outcomes. Our exploratory analysis demonstrated that model uncertainty would likely increase with model complexity given uncertain input data (e.g., climate forcing) and different model configurations; the inclusion of a learning mechanism in the human system can potentially offset the impact of the natural system on uncertainty through coupling natural and human systems. We also discuss other uncertainty sources, such as assumptions about model structure due to incomplete knowledge and metrics for calibration target selection for future studies.</p>
Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system
<p>This database includes the data used to produce the results for the following article:</p> <p>Bellos, V., Kossieris, P., Efstratiadis, A., Papakonstantis, I., Papanicolaou, P., Dimas, P., Makropoulos, C. 2022. Can we use hydraulic handbooks in blind trust? Two examples from a real-world complex hydraulic system. 7th IAHR Europe Congress, September 7th – 9th, 2022, Athens, Greece (accepted paper for oral presentation, in press).</p>
Figure 4: Complexity of geographical space with respect of emergent organizations-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS
<p>The applications we focus on in the models that we will propose in the<br> following, concerns specifically the multi-center (or multi-organizational) phenomona<br> inside urban development. As an artificial ecosystem, the city development<br> has to deal with many challenges, specifically for sustainable development,<br> mixing economical, social and environmental aspects. The decentralized<br> methodology proposed in the following allows to deal with multi-criteria problems,<br> leading to propose a decision making assistance, based on simulation<br> analysis.</p>
Figure 1: Complex spatial organizational model-MODELING SELF-ORGANIZING SYSTEMS WITH SOCIAL INSECTS ALGORITHMS
<p>On Figure 1, we describe a two-level model of spatial self-organizations with<br> interactions in both directions between these two levels: the emergence of organizations<br> from entities interactions but also the feed-back process describing<br> how organizations are regulating their own entities.</p>
Figure 4: Nyquist diagrams ² 00 (!¿¾) = f(² 0 (!¿¾))T 166-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>Fig.4. This behaviour denotes that the EDL is not an ideally<br> capacitor, but also is not a disipative region, depending both on the EDL<br> thickness and the frequency range of the applied ¯eld [7]. The composition<br> (by thickness) of the EDL determines essentially the dielectric response of the<br> interface system. Compared with experimental results, the dielectric pro¯le<br> of this higher length scales model, can provides a more complet description of<br> the solvent properties for a given electrode.</p>
Figure 1: EDL structure for p-Si-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>Figure 1: EDL structure for p-Si (SCL negative charged,²F < ²FR )/aqueous<br> solvent interface. The electrostatic potential and charged atoms in solvent<br> distributions vs the distance z from the wall.</p>
Figure 3: The dependencies ² 00 (log !¿¾). The values are normalized at ² 00 max-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>Fig.3. The conductivity relaxation occurs at<br> lowing frequencies. The form of the ²<br> 00<br> (!) = f(²<br> 0<br> (!)) diagrams changes from<br> a vertical line (a), to any deformate semicircles (b, c, d) having the angle to<br> real axe below ¼<br> 2 , Fig.4. This behaviour denotes that the EDL is not an ideally<br> capacitor, but also is not a disipative region, depending both on the EDL<br> thickness and the frequency range of the applied ¯eld [7]. The composition<br> (by thickness) of the EDL determines essentially the dielectric response of the<br> interface system. Compared with experimental results, the dielectric pro¯le<br> of this higher length scales model, can provides a more complet description of<br> the solvent properties for a given electrode.</p>
Figure 2: The dependencies ² 0 (log !¿¾). The values are normalized at ² 0 max-TOWARD THE PHYSICAL BASIS OF COMPLEX SYSTEMS: DIELECTRIC ANALYSIS OF POROUS SILICON NANOCHANNELS IN THE ELECTRICAL DOUBLE LAYER LENGTH RANGE
<p>The results of the model are shown that the frequency-dependences ²<br> 0<br> (log(!¿¾))<br> in Fig.2, ²<br> 00(log(!¿¾)) in Fig.3 and ²<br> 00<br> (²<br> 0<br> )T in Fig.4, where ²<br> 0<br> , ²<br> 00<br> are the real and<br> imaginary part, respectively, from (7), having the ¸D<br> ¸ ratio as parameter.</p>
Fig. 7 in Loss of complexity from larval towards adult nervous systems in Chaetopteridae (Chaetopteriformia, Annelida) unveils evolutionary patterns in Annelida
Fig. 7 The anterior adult nervous system of Phyllochaetopterus sp. revealed by immunohistochemistry. a, b confocal maximum projections of anti-5HT-staining. a: The brain (br) consists of a compact neuropil without prominent commissures. The palp nerves (pn1, pn2)
Fig. 8 in Loss of complexity from larval towards adult nervous systems in Chaetopteridae (Chaetopteriformia, Annelida) unveils evolutionary patterns in Annelida
Fig. 8 Representative larval and juvenile stages of Chaetopterus variopedatus. Light microscopic images. Stages are shown in hours (hpf) or days past fertilization (dpf). a: 48 hpf, the larvae are still spherical and possess a prominent apical tuft (at) at the anterior end. b: 13 dpf, the larvae exhibit an elongated body, with prominent apical eyespots (ey) and distinct chaetal bundles (ch). mo: mouth opening. c:> 50 dpf,
Fig. 4 in Loss of complexity from larval towards adult nervous systems in Chaetopteridae (Chaetopteriformia, Annelida) unveils evolutionary patterns in Annelida
Fig. 4 Adult ultrastructure of the nervous system. a: The brain is intraepidermal; i.e., the neurites (ne) are located dorsal to the basal lamina (bl). Intermediate filaments (if) are located inside radial glial cell processes (gcp) which cross the neuropil perpendicularly. mu: musculature. b: Somata (so) of neurons are located dorsal to the neurites (ne). Nuclei (nu) of neuronal somata are spherical. Somata of glial cells (sogc) are interspersed between the neuronal somata (so).
Fig. 2 in Loss of complexity from larval towards adult nervous systems in Chaetopteridae (Chaetopteriformia, Annelida) unveils evolutionary patterns in Annelida
Fig. 2 Adult histology of the cns. Azan, 5 µm, sections of anterior body region A (according to chaetopterid nomenclature). a, c, e: Spiochaetopterus costarum; b, d, f: Chaetopterus norvegicus. a: the brain (br) is located inside the epidermis (ep). It is composed of a neuropil (np) and dorsally located neuronal somata (so). Lateral of the brain, the lateral medullary cords (lmc) branch of. bl: basal lamina; eso: esophagus. b: The brain (br) is intraepidermal. The somata (so) layer is located dorsally to the neuropil (np). An esophageal plexus (epl) connects both medullary cords continuously. bl: basal lamina; ep: epidermis; eso: esophagus; c: somata (so) of the neuro-
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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.