cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.12573600
title: Data underpinning "Classical Chaos in Quantum Computers"

description: We provide the data used to produce the figures shown in our publication "Classical Chaos in Quantum Computer" and a Jupyter Notebook to reproduce all figures.

Abstract: 









The development of quantum computing hardware is facing the challenge that current-day quantum processors, comprising 50-100 qubits, already operate outside the range of quantum simulation on silicon computers. In this paper, we demonstrate that the simulation of classical limits can be a potent diagnostic tool potentially mitigating this problem. As a testbed for our approach, we consider the transmon qubit processor, a computing platform in which the coupling of large numbers of nonlinear quantum oscillators may trigger destabilizing chaotic resonances. We find that classical and quantum simulations lead to similar stability metrics (classical Lyapunov exponents vs. quantum wave function participation ratios) in systems with O(10) transmons. However, the big advantage of classical simulation is that it can be pushed to large systems comprising up to thousands of qubits. We exhibit the utility of this classical toolbox by simulating all current IBM transmon chips, including the recently announced 433-qubit processor of the Osprey generation, as well as future devices with 1,121 qubits (Condor generation). For realistic system parameters, we find a systematic increase of Lyapunov exponents in system size, suggesting that larger layouts require added efforts in information protection.
DOI: 10.5281/zenodo.3236068
title: RUEG Corpus

description: The Research Unit Emerging Grammars (RUEG) investigates the linguistic systems and linguistic resources of bilingual speakers from families with an immigrant history, “heritage speakers”, in both of their languages across different language pairs, registers, and age groups. We investigate speakers of Russian, Turkish, and Greek as heritage languages in Germany and the U.S., in addition to German as a heritage language in the U.S., as well as monolingual controls for majority and heritage languages. We study noncanonical phenomena as indicators of new grammatical options in bilingual systems. All projects contribute tothree “Joint Ventures” targeting (1) the development of new dialects vs. incomplete acquisition or erosion (“Language Change Hypothesis”), (2) the relevance of internal vs. external grammatical interfaces (“Interface Hypothesis”), and (3) the distinction of contact-induced change vs. language-internal developments and variation (“Internal Dynamics Hypothesis”). As a result of our collaborative research, we expect new insights into the special dynamics of language variation, language change and linguistic repertoires in contact situations and the modelling of noncanonical structures in the grammatical system, and new impulses for the investigation of heritage speakers and of speakers’ resources.

The projects are supported by two Mercator Fellows:

Shana Poplack, University of Ottawa

Maria Polinsky, University of Maryland

Jeanine Treffers-Daller, University of Reading

Cristina Flores, Universidade do Minho

The Research Unit is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project numbers: 39482131 & 313607803.

You can search this data online in ANNIS: https://korpling.german.hu-berlin.de/annis/
DOI: 10.5281/zenodo.7744053
title: A benchmark dataset of Solidity smart contracts

description: A benchmark dataset contains 4,364 real-world Solidity smart contracts, which are manually labeled with ten types of vulnerabilities. DC (DelegateCall). The <em>address.delegatecall() </em>function allows a smart contract to dynamically load external contracts from <em>address</em> at runtime. If the attacker can control the external contract and affect the current contract status, the contract is vulnerable to DC. IOU (Arithmetic/Integer Overflow and Underflow). An arithmetic overflow or underflow, often called Integer Overflow or Underflow (IOU), occurs when an arithmetic operation attempts to create a numeric variable value that is larger than the maximum value or smaller than the minimum value of the variable type. If the arithmetic operation may pass a variable type’s maximum or minimum value and is performed without using SafeMath, the contract is vulnerable to IOU. NC (Nested Call). The function containing the loop has a high risk of exceeding its gas limitation and causing an out-of-gas error. If the attacker can control the loop iteration and causes the out-of-gas error, the contract is vulnerable to NC, RE (Reentrancy). The contract vulnerable to RE uses the <em>call()</em> function to transfer ether to an external contract. The external contract can reenter the vulnerable contract by fallback function. If the state variable change is after the <em>call()</em> function, the reentrance will cause status inconsistency. TD (Timestamp Dependency). The contract uses the <em>timestamp</em> as the deciding factor for critical operations, e.g., sending ether. If the attacker can get ether from the contract by manipulating the timestamp or affecting the critical operations, the contract is vulnerable to TD. TO (TxOrigin). If the contract only uses <em>tx.origin</em> to verify the caller's identification for critical operations, it is vulnerable to TO. TOD (Transaction Order Dependency). The contract may send out ether differently according to different values of a global state variable or different balance values of the contract. If the attackers can get ether from the contract by manipulating the transaction sequences, the contract is vulnerable to TOD. UcC (Unchecked Call). The contract uses the function <em>call()</em> or <em>send()</em> without result checking. If the <em>send()</em> or <em>call() </em> function fails and leads to status inconsistency, the contract is vulnerable to UcC. Unprotected Suicide). If an attacker can self-destruct the contract by calling the <em>selfdestruct</em>(address) function, the contract is vulnerable to UpS. FE (Frozen Ether). If the contract can receive ether but cannot transfer it by itself, it is vulnerable to FE. <br> <strong>For the purpose of protection for smart contracts, the dataset can be available after request.</strong>
DOI: 10.5281/zenodo.8188948
title: Volumetric segmentation of biological cells and subcellular structures for optical diffraction tomography images - dataset

description: This dataset includes 4 files with segmentation results for 4 different ODT reconstructions of SH-SY5Y neuroblastoma cell. The segmentation results contain: 3D binary masks of biological cells obtained through Cellpose [1] and ODT-SAS; 3D binary masks of organelles: nucleoli and lipid structures (LS) obtained through slice-by-slice manual segmentation and ODT-SAS. All files are .*mat files. The files <em>REC_SH-SY5Y_1.mat, REC_SH-SY5Y_2.mat</em> and<em> REC_SH-SY5Y_3.mat</em> consist of 7 variables: RECON – tomographic reconstruction of SH-SY5Y neuroblastoma cell;<br> n_imm – refractive index of object immersion medium;<br> dx – object space sample size in XY [\(\mu m\)];<br> rayXY – xy-coordinates of illumination vectors; maskManual – table with manually determined 3D binary masks of organelles;<br> maskCellpose – 3D binary mask of biological cell obtained through Cellpose;<br> maskODTSAS – table with 3D binary masks of biological cell and their organelles obtained through ODT-SAS. File <em>REC_SH-SY5Y_4.mat</em> includes masks for the ODT-SAS and Cellpose segmentation of three closely packed cells and consists of 5 variables: RECON, n_imm, dx, maskCellpose and maskODTSAS.<br> <br> Access a particular 3D binary mask from 'maskManual' and 'maskODTSAS' tables, using the following names: 'Cell', 'Nucleoli', 'LS'.<br> For example: <pre><code>cellMask = maskODTSAS.Cell{1};</code></pre> <br> [1] Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation. Nature methods, 18(1), 100-106.
DOI: 10.5281/zenodo.8360397
title: Research data supporting article on implementation and validation of OpenMC cell-based R2S shutdown dose rate capabilities

description: This file contains an archive of all research data that supports the article on implementation and validation of a cell-based R2S shutdown dose rate workflow in OpenMC.
description: This work is supported by the U.S. Department of Energy Office of Fusion Energy Sciences under award number DE-SC0022033.
DOI: 10.6073/pasta/101ae920e5b5a97fadd3cb439440ac3f
title: North Temperate Lakes LTER: High Frequency Meteorological and Dissolved Oxygen Data - Sparkling Lake Raft 1989 - current

description: The instrumented raft on Sparkling Lake is equipped with a dissolved oxygen and CO2 sensors, a thermistor chain, and meteorological sensors that provide fundamental information on lake thermal structure, weather conditions, evaporation rates, and lake metabolism. Estimating the flux of solutes to and from lakes requires accurate water budgets. Evaporation rates are a critical component of the water budget of lakes. Data from the instrumented raft on Sparkling Lake includes micrometeorological parameters from which evaporation can be calculated. Raft measurements of relative humidity and air temperature (2 m height), wind velocity ( at 1, 2, and 3 m heights; but beginning in 2008, only at 2 m) ,and water temperatures (from thermistors placed throughout the water column at intervals varying from 0.5 to 3m) are combined with measurements of total long-wave and short-wave radiation data from a nearby shore station to determine evaporation by the energy budget technique. Comparable evaporation estimates from mass transfer techniques are calibrated against energy budget estimates to produce a lake-specific mass transfer coefficient for use in estimating evaporation rates. After correcting for flux to or from the atmosphere and vertical mixing within the water column, high frequency measurements of dissolved gases such as carbon dioxide and oxygen can be used to estimate gross primary productivity, respiration, and net ecosystem productivity, the basic components of whole lake metabolism. Other parameters measured include precipitation, wind direction (beginning in 2008), and barometric pressure (beginning in 2008). Sampling Frequency: one minute; averaged to hourly and daily values as well as higher resolution values such as 2 min and 10 min. Number of sites: 1
DOI: 10.6084/m9.figshare.23724705
title: Efficient inference of large prokaryotic pangenomes with PanTA

description: Supporting data for paper "Efficient inference of large prokaryotic pangenomes with PanTA"
DOI: 10.6084/m9.figshare.25151096.v1
title: Frailty during one year after pandemic, Klangenan.xlsx

description: This study aimed to determine frailty status and identify factors associated with the suburban elderly population in Cirebon Regency, Indonesia, after one-year COVID-19 pandemic.
DOI: 10.6084/m9.figshare.25193651
title: Blender rendering of setup

description: Blender rendering of setup.
DOI: 10.6084/m9.figshare.25193663
title: CAD file of lens mounts

description: CAD file of lens mounts
DOI: 10.6084/m9.figshare.25193669
title: CAD file of objective lens mirror mount

description: CAD file of objective lens mirror mount
DOI: 10.6084/m9.figshare.25193675
title: CAD file of shutter mount

description: CAD file of shutter mount
DOI: 10.6084/m9.figshare.25347841
title: Supplementary Material for: Upregulated Genes in Atrial Fibrillation Blood and the Left Atrium

description: Introduction: Atrial fibrillation (AF) is a common arrhythmia associated with aging. Many known risk factors are associated with AF, but many senior individuals do not develop AF despite having multiple risk factors. This finding suggests that other factors may be involved in AF onset. This study aimed to identify upregulated genes in the peripheral blood and left atrium of patients with AF. These genes may serve as potential biomarkers to predict AF onset risk and its complications. Methods: Gene expression data was analyzed from blood (n = 3) and left atrial samples (n = 15) of patients with AF and sinus rhythm. We evaluated the significant genes identified using p-value analysis of weighted average difference to confirm their rankings. We created figures for the genes using GeneMANIA and performed a functional analysis using Cytoscape3.10.1. Hub and bottleneck genes were identified based on degree and betweenness centrality. We used RefEx to confirm the organs in which the extracted genes were expressed. Heatmaps and Gene ontology term evaluation were performed to further elucidate the biological functions of the genes. Results: We identified 12 upregulated genes (CAST, ASAH1, MAFB, VCAN, DDIT4, FTL, HEXB, PROS1, BNIP3L, PABPC1, YBX3, and S100A6) in both the blood and left atrium of patients with AF. We analyzed the gene functions using GeneMANIA and Cytoscape. The identified genes were involved in a variety of pathways, including lysosomal function and lipid and sphingolipid catabolism. Next, we investigated whether the 12 identified genes identified were systemically expressed or had high organ specificity. Finally, Reference expression (RefEx) was used to analyze the gene expression levels in various tissues. Four genes; FTL, ASAH1, S100A6, and PABPC1, were highly expressed in the normal heart tissue. Finally, we evaluated the expression levels of the 12 genes in the blood of patients with AF using a heatmap. Our findings suggest that the 12 genes identified in this study, especially the lysosome-related genes (FTL and ASAH1), may be involved in AF pathogenesis. Conclusion: Lysosome-related genes may be important to understand the AF pathophysiology and to develop AF-related future studies.
DOI: 10.6084/m9.figshare.25498645
title: Supplementary Material for: Neck circumference in polycystic ovary syndrome: a systematic review and bootstrapped meta-analysis with GRADE approach

description: Introduction: Our aim was to perform a systematic review and meta-analysis for the association of neck circumference (NC) in polycystic ovary syndrome (PCOS) patients as compared to non-PCOS controls.
Methods: Primarily the PubMed/MEDLINE database, and others such as SCOPUS, Google Scholar, Cochrane Library, up to November 15, 2023 for observational studies comparing NC in PCOS versus non-PCOS women. The mean and SD values of NC and other covariates in PCOS and control groups were extracted by two independent reviewers, and the quality and risk of bias assessment was done using Newcastle–Ottawa Scale of the studies. The meta-analysis employed combined standardized mean differences (SMD) with 95% confidence intervals (CI) to compare NC between PCOS patients and controls. The heterogeneity and validity were addressed by sub-group, meta-regression, and sensitivity analyses. We conducted a Bootstrapped meta-analysis using 1000 and 10000 simulations to test the accuracy of the obtained results. The certainty of evidence was assessed by GRADE approach.
Results: Our meta-analysis included 9 observational studies. The PCOS patients showed a significantly higher NC values than the non-PCOS controls (SMD 0.66, 95% CI 0.41-0.91, p&lt;0.0001). In the bootstrap meta-analysis, the accuracy of the observed findings was proved (SMD=0.66, CI=0.42 to 0.91) for the NC outcome. No publication bias was detected in the funnel plot analysis using Begg’s and Egger’s tests. The 95% prediction interval of 0.036 to 1.28, suggest that the true outcomes of the studies are generally in the same direction as the estimated average outcome. The sensitivity analysis provided the robustness of the outcome, and no single study was overly influential on the pooled estimate. 
Conclusion: This meta-analysis provides accurate evidence for significantly higher NC in PCOS as compared to non-PCOS controls. There is no sufficient evidence on the diagnostic accuracy measures for NC in PCOS. Hence, further research on its diagnostic utility in PCOS is needed.
DOI: 10.6084/m9.figshare.26509780
title: Supplementary Material for: Assessment of Quality of Reporting in Randomized Controlled Trials of Moxibustion for Chronic Diseases using the CONSORT and STRICTOM statements

description: Background: Moxibustion is clinically used for treating various chronic diseases; however, the reporting quality of current published RCTs of moxibustion is unclear.
Objective: To assess the reporting quality of RCTs focusing on moxibustion as a treatment for chronic diseases.
Methods: Seven databases were searched to identify relevant RCTs. Criteria for evaluating the reporting quality of standard RCT elements and moxibustion intervention-related information were developed based on the CONSORT statement and its STRICTOM extension, respectively. Multivariate regression models were used to investigate factors impacting reporting quality.
Results: A total of 310 RCTs were included, with 41 (7.6%) published in English journals and 269 (92.4%) in Chinese journals. The median CONSORT and STRICTOM scores of these RCTs, with a maximum score of 100, were 41.2 and 62.9, respectively. RCTs with a later publication year and with protocol registration or ethical approval exhibited significantly higher CONSORT and STRICTOM scores. Higher CONSORT scores were also significantly associated with English-language publication, funding support, and inclusion of a safety evaluation, while higher STRICTOM scores were additionally associated with an active-control design.
Conclusion: The reporting quality of RCTs focusing on moxibustion treatment for chronic diseases is subpar, with gradual but limited improvement over the last 25 years. To enhance the reporting quality of moxibustion RCTs, researchers should develop a comprehensive study protocol and standardize result reporting based on CONSORT and STRICTOM statements. Registration platforms, ethical approval organizations, funders, and journals can also contribute to this improvement by bolstering structured information reporting in the review process.
DOI: 10.14469/hpc/12902
title: endo-TS1 replicating G03 lit calc( Lit: E = -823.545644624, G = -823.400723), sphere on 13, ==&gt; re-opt(readfc), E = -823.5462317, G = -823.399837, ΔΔG = +0.55, GN 0.000010283

description: Gaussian 16 (C01) calculation. No analytic 2nd derivatives available for G03 solvation model, so FC calculated using numerical 2nd derivatives and used to refine TS via the keyword opt(readfc,ts) in several cycles.

TS mode -281.5. Lit value -286.
DOI: 10.14469/hpc/13189
title: exo-TS1 replicating G03 lit calc( Lit: E = -823.546858207, G = -823.401398) Single point at lit geometry, sphere 14 =&gt; 2-ve, re-opt, =&gt; E = -823.546902530 , G = -823.40067, GN 0.000066369,

description: Gaussian 16 (C01) calculation. TS mode calc -271.52, Lit value -272 DG (exo-endo) = -823.400677 - -823.399837 = 0.52 kcal/mol.
DOI: 10.17882/77361
title: Coral fragments health and growth in the Reefscapers propagation project in the Maldives

description: The Reefscapers program is a coral restoration initiative to help reef recovery in the Maldives. It started in 2001, and is most active since the 2015-2016 mass bleaching event. We produced health and growth data for 77,574 transplanted colonies using machine learning algorithms to analyze monitoring pictures. It enables us to assess the ability of coral restoration to help reef recovery after mass bleaching events, on a large scale.
DOI: 10.18462/iir.rankine.2020.1168
title: Theoretical analysis of transcritical HTHP cycles with low gwp hfo refrigerants and hydrocarbons for process heat up to 200 °C.
DOI: 10.22000/txyuwrmdhbmgqmqr
title: ChauRS2024

description: Data to reproduce the figures in publication.
DOI: 10.34863/0k5x-w691
title: Dataset: Real-space visualization of a defect-mediated charge density wave transition
DOI: 10.5258/soton/d2613
title: Dataset supporting the publication "Bi-doped fiber amplifiers in the E+S- band with high gain per unit length"

description: This Dataset is supporting the publication "Bi-doped Fiber Amplifiers in the E+S- band with High Gain per Unit Length". The data is an excel file that contains data of the Bi-doped fibre amplifier (BDFA) in terms of Gain and Noise Figure (NF) across 80nm from 1400 to 1480nm. The amplifier is also studied under different temperatures. The temperature-dependent gain (TDG) is presented. All this data supports the figures in the article. Published in Optics Letters
DOI: 10.5281/zenodo.7075871
title: Full-waveform pulsed LiDAR dataset

description: A dataset comprised of full-waveform (periodically sampled) pulses emulating LiDAR signals is provided. The waveforms were captured at a sampling rate of 20 Gsample/s and over a dynamic range of 45 dB. A simple Python notebook is also given, showing how to properly load the waveforms and capture parameters from the stored .mat file. The dataset was used to demonstrate a new time-frequency estimation method for pulsed LiDAR systems [1]. The dataset was also used to build efficient machine learning (ML) models capable of accurate and precise time-of-flight estimations [2]. For full details, please check the Experimental Setup in [1]. Please contact Daniel Bastos (d.bastos@ua.pt) for any further questions. References: [1] – D. Bastos, A. Brandão, A. Lorences-Riesgo, P. P. Monteiro, A. S. R. Oliveira, D. Pereira, H. Z. Olyaei and M. V. Drummond, , "Time-Frequency Range Estimation Method for Pulsed LiDAR," in <em>IEEE Transactions on Vehicular Technology</em>, vol. 72, no. 2, pp. 1429-1437, Feb. 2023, doi: 10.1109/TVT.2022.3207588. [2] – Daniel Bastos, Bruno Faria, Paulo P. Monteiro, Arnaldo S. R. Oliveira, and Miguel V. Drummond, "Machine learning-aided LiDAR range estimation," Opt. Lett. <strong>48</strong>, 1962-1965 (2023), doi: 10.1364/OL.487000.
DOI: 10.5281/zenodo.8318495
title: Questionnaire data for assessing what determines urban residents' engagement in activities for the protection of urban green spaces (UGS)

description: This dataset contains the core data used to investigate what determines Munich’s residents’ engagement in activities for the protection of urban green spaces (UGS). We conducted an exploratory factor analysis and a structural equation modelling based on the data from an online and in-person questionnaire. <strong>List of data and content</strong> Questionnaire_English: The content of the questionnaire in English (*.pdf) Questionnaire_RawData_ Munchen_German: Core data from the questionnaire in German (*.xlsx) InputEFA1: Core data for the first exploratory factor analysis with the input for analysis in Mplus (*.xlsx) InputEFA2: Core data for the second exploratory factor analysis with the input for analysis in Mplus (*.xlsx) InputSEM: Core data for the structural equation modelling with the input for analysis in Mplus (*.xlsx) ResultsSEM: Results of the structural equation modelling (*.xlsx) InputCFA1: Core data for the first confirmatory factor analysis with the input for analysis in Mplus (*.xlsx) ResultsCFA1: Results of the confirmatory factor analysis (*.xlsx) InputCFA2: Core data for the second confirmatory factor analysis with the input for analysis in Mplus (*.xlsx) ResultsCFA2: Results of the confirmatory factor analysis (*.xlsx) Acronyms_Shortings: Acronyms and shortings used in the uploaded files (*.pdf) <strong>Data processing</strong> The software for performing the exploratory factor analysis and structural equation modelling was Mplus 8.8 (Muthén and Muthén, 1998). The details on the methodological steps are available in the published publication. To quickly understand the EFA, CFA and SEM model and settings the details are provided in the hyperlinks. <strong>Acknowledgments</strong> The authors thank to all participants for their participation in the online and in-person questionnaires. Data processing and analysis would not have been possible without the help of Tomomi Saito. This work was supported by a grant from the Alexander von Humboldt Foundation and by the Leibniz Best Minds Competition, Leibniz-Junior Research Group, Grant J76/2019.