dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion In this case study, we calculated the impact of using a PMSthe equivalent of a monofunctional I-BIM for pavement maintenance planningon a high-traffic road life cycle carbon footprint, and showed that it must be beneficial to reduce the carbon footprint of road pavement management. Nevertheless, uncertainties occur at each stage of an LCA  (Huijbregts, 2001)  and the findings of this primary study must be confirmed by further studies encompassing geographic, technologic and temporal variabilities. PMS data collections, data management, and software usage, can vary widely from road manager to road manager around the world. Nevertheless, the PMS contribution to the pavement life cycle carbon footprint being negligible, SA on the PMS use case must not change the conclusions of this study.
Thus, I-BIM could be used to break free from established rules and optimize structures over time according to desired criteria, for example, carbon emissions minimization. Indeed, monitoring the condition of pavements in real-time through instrumentation and using these data in an I-BIM to simulate the structural evolution over time would greatly advance maintenance management compared to what current structural simulation software programs allow. The big data generated and stored on the condition of the pavements and their environment could seed the development of algorithms based on artificial intelligence (AI) allowing for better simulate the behavior of road structures. Indeed, road design methods have gone from an empirical approach to a combination of mechanical physics and empiricism ("ME" methods) in the face of the inability of empiricism to capture the unlimited heterogeneity of pavement behavior due to limited data.
NUMERICAL MODELLING The energy dissipated during the process of damage can be quantified by performing finite element impact simulations. Commercial finite element software, such as Abaqus  [44] , allows to compute the damage energy dissipated during collisions between objects. The computation is based on the 'erosion method', which requires a set of input parameters to define when the damage starts occurring and how the damage curve evolves. According to this approach, a finite element is removed from the system when its stiffness reduces to the point that its load-carrying capability becomes null. It is clear that a complete characterization of the stress-strain curve of the material is necessary to implement this method  [45]. However, our aim is to investigate the damage mechanisms of multiple-hit impacts rather than focusing on a specific material.
27 J. These conditions lead to the following system of equations 1 2 • 𝑚 𝑠 • 𝑉 𝑠𝑡𝑟𝑜𝑛𝑔 2 = 2 • 1 2 • 𝑚 𝑠 • 𝑉 𝑤𝑒𝑎𝑘 2 (6) 1 2 • 𝑚 𝑠 • ∑ 𝑉 𝑖 2 2,3 𝑖 = ℰ 𝑘 * (7) with 𝑚 𝑠 the mass of the projectile, 𝑉 𝑠𝑡𝑟𝑜𝑛𝑔 and 𝑉 𝑤𝑒𝑎𝑘 , respectively, the projectile's velocity for the strong and weak impacts. Different values of time delay between consecutive impacts, the parameter 𝛥𝑇 , are investigated: 0. 0 (the value tends to 0. 0), 0. 2, 0. 4, 0. 5, 0. 6, 0. 8 ms. The aim is to reproduce not only the mantis shrimp attack timing that, according to the experiments in  [26] , is 0. 5 ms, but also to explore different time delays having the same order of magnitude as the experimental data. Finally, our explicit dynamic simulations are developed in Abaqus 6. 13-3, a commercial finite element software allowing us to compute the damage energy dissipated during collisions J o u r n a l P r e -p r o o f between objects  [44].
ACKNOWLEDGMENTS NP is supported by the  EU   H2020 FET-Open  project  Boheme , grant agreement No. 863179 , and by the  PRIN-20177TTP3S  grant. FO is supported by the  EU   H2020 FET-Open  project  Boheme , grant agreement No. 863179. J o u r n a l P r e -p r o o f.
The Flystel Structure The performance metrics for AO algorithms differ substantially from the usual ones in symmetric cryptography. Neither the number of CPU cycles, nor the RAM consumption or the code size are the dominant factors. Pin-pointing exactly what is needed for the various protocols relying on arithmetization is a difficult task as each protocol has its own subtleties. For example, Plonk offers custom gates, which add complexity and a small overall overhead but can drastically decrease the cost of a particular operation, while other proof systems might not. On the other hand, additions are essentially free for R1CS or AIR, but not for Plonk. In addition, permutations of a sequence of elements are likely to incur cost in Plonk or AIR (via copy-constraints), but are free in R1CS. In this section, we present a family of non-linear components that provide both the cryptographic properties that we need to ensure the security of our primitives, and efficient implementations across proof systems, which we call open Flystel.
AIR Finally, we also study the performance of Anemoi in the Algebraic Intermediate Representation (AIR) arithmetization used in STARKs  [BBHR18]. Here, the relevant quantities are: the width of the computation state 𝑤, the number of computation steps 𝑇 , and the maximum degree of the constraints 𝑑 max. While there are several ways to estimate the cost of a given AIR program given the above quantities, we will consider the total cost to be expressed as 𝑤 • 𝑇 • 𝑑 max , following [AAB + 20]. For Rescue-Prime, Griffin and Anemoi, we have 𝑤 = 𝑡, 𝑇 = 𝑛 𝑟 and 𝑑 max = 𝛼. For Poseidon, we have 𝑤 = 𝑡, 𝑇 = RF + ⌈RP/𝑡⌉ and 𝑑 max = 𝛼. We then compare the total cost for these four schemes in Table  2. Anemoi and Griffin are quite similar, and close to Rescue-Prime.
Acknowledgements We thank the reviewers of CRYPTO 2023 for providing insightful comments which helped improve the clarity of this paper. In particular, we would like to thank the shepherd for their assistance in finalizing the paper. We are also grateful to  Markulf Kohlweiss ,  Antoine Rondelet  and  Duncan Tebbs  for proofreading an earlier draft of this paper, and for providing insightful comments and suggestions. Additionally, we extend our thanks to  Duncan Tebbs  for providing an independent estimation of the Flystel circuit cost in terms of R1CS constraints. The work of  Léo Perrin  is supported by the  European Research Council (ERC , grant agreement no. 101041545  " ReSCALE "). We thank  Tomer Ashur  for pointing out a mistake in Figure 1 in a previous version of the paper. We also thank  Miguel Ambrona  and  Raphaël Toledo  for the idea of the quadratic custom gate and their contribution to the Plonk implementation.
This study used the Theory of Planned Behavior as the theoretical foundation to investigate the motivating factors influencing Generation Z consumers' green purchasing behavior in Pakistan. Using a random sampling technique, the researchers gathered information from over 300 Gen Z consumers between the ages of 10 and 25 using a survey questionnaire. Utilizing a quantitative research approach, the study used Smart PLS 3. 0 software and Partial Least Square Structural Equation Modelling (PLS-SEM) to analyze the data. Green purchase intention, green buying behavior, green attitudes, perceived behavioral control, and green social norms were the variables examined. The results of the study indicate that there is a significant relationship between "green attitudes," "green social norms," and "green purchase intention" with green buying behavior, with a p-value of less than 0.
Research Design The purpose of the study is to analyze the factors that influence the green buying behavior of generation Z consumers. This study uses quantitative research approach. Quantitative research is the methodical collection and analysis of numerical data in order to draw statistical conclusions regarding a certain phenomenon  (Mohajan, 2020). In order to examine correlations and trends within a dataset, it needs acquiring structured, quantitative data  (Taherdoost, 2022). As such, it is a suitable method for scientifically measuring things like "green attitude", "green subjective norms", "green behavioral control". Moreover, deductive reasoning is used in quantitative research, which begins with a theory or hypothesis, gathers data, analyses it, and draws conclusions  (Haque, 2022)  It is a hypothesis-driven method that aims to support or reject preliminary assumptions, which makes it a good fit for addressing the study's research issues.
Target Population The study was carried out in Sukkur, Sindh, Pakistan, with a focus on Generation Z green consumers as the study participants. The age range of the participants spanned from 10 to 25 years, and they were persons who had received education and resided in metropolitan regions. Hocquette, Liu, Ellies-Oury, Chriki, and Hocquette (2022)  have posited that there exists a correlation between education level and environmental consciousness among customers residing in metropolitan areas, with educated individuals displaying a greater awareness and understanding of green products compared to their less educated counterparts in rural regions  (Hocquette et al. , 2022). Consequently, the researchers specifically recruited participants who were university-level students and professionals in order to ensure the acquisition of precise and reliable data for this study.
Sample Size The determination of the study's sample size followed the guideline of Hair Jr, Anderson, Tatham, and  Black (2006)  which suggests having 15 to 20 observations per item. The study employed a questionnaire consisting of five dimensions and a total of 24 items. Specifically, the questionnaire included six items pertaining to green buying behavior, three items related to green purchase intention, five items concerning green attitude, five items addressing green social norms, and five things exploring green behavioral control. The study aimed to have a sample size of 360 respondents, calculated by multiplying 24 items by 15 observations. In order to do so, 422 survey questionnaire were distributed, however, only 87% of total (367 out of 422) were returned. Prior to doing data analysis, the data obtained from our survey undertook a comprehensive data cleaning and screening procedure utilizing IBM SPSS.
Initially, we detected and resolved the issue of missing values by the utilization of mean imputation technique. Following this procedure, a total of 58 observations, accounting for 15. 8% of the initial 367 observations, were eliminated. Furthermore, the identification of outliers was accomplished by employing descriptive statistics and box plots. Subsequently, any extreme values were eliminated from the dataset, resulting in a final sample size of 302 observations. The variables were normalized and converted where necessary, to ensure data satisfied the assumptions of statistical test. Consequently, 302 respondents were included in the final data set used for analysis. According to  Hair, Black, Babin, and Anderson (2010)  this sample size lies within the recommended range of 150-400 respondents for conducting structural equation modeling (SEM) analysis with SmartPLS3.
0. Procedure Self-administered questionnaires were used to gather data for this study, and they were delivered between January and March of 2023. The participants were informed in advance that they would be required to answer a brief survey about products that are environmentally friendly. In addition, participants received assurances that their answers would be treated with the utmost confidentiality. When the survey first began, it advised respondents to think about purchasing ecologically friendly goods. In addition, the participants received instructions to complete a 10-minute survey in which they were exposed to a series of statements. After that, participants were asked to indicate how much they agreed or disagreed with the statements that had been presented. Green buying behavior of Gen Z was the dependent variable in the study, whereas "green attitude", "green social norms", and "green behavioral control" were the independent factors.
Measurement Scale The researchers employed appropriate scales and measures derived from previous studies in order to investigate the study inquiries. This study uses pre-validated items to create questionnaire. Before collecting the data using the developed survey questionnaire, we performed pilot study on 68 consumers from the targeted sample of generation Z from Sukkur city to access the validity and reliability of questionnaire. The results for the pilot study suggests minor modifications to simplify the wording in few statements in order to reduce confusion and make it more clear for targeted participants. Following minor adjustments, the questionnaire was ultimately refined and employed as the primary instrument for data collection in this research endeavors. The participants employed a Likert-scale consisting of five points to assess their level of agreement with a set of statements.
Findings and Discussion This study's data was analyzed using IBM SPSS Statistics 26 and SmartPLS 4 software. The demographic data was analyzed using IBM SPSS Statistics 26 software, and the hypothesis was tested using Structural Equation Modelling (SEM) with the assistance of SmartPLS 4 software. This part covers the findings derived from the analysis of data, beginning with the presentation of demographic information. After, we conducted construct validity and reliability assessment to measurement model. Subsequently, the results of the structural modelling assessment are documented in order to evaluate the hypothesis.
In safety-critical industries, including the nuclear sector, ultrasonic testing (UT) of welded components is an area of continuous improvement. We have collaborated on developing advanced UT simulation tools to address challenges in monitoring and imaging defects near or within a weld bevel. These tools, integrated into the CIVA software platform, use hybrid approaches combining ray models and finite elements (FE) to accurately simulate wave propagation and diffraction phenomena in both 2D and 3D inspection configurations. While computation time is longer compared to ray-based approaches, the results serve as a reference for improving reliability and validating simulation tools. A comprehensive parameterization of the weld is proposed, utilizing knowledge on anisotropy, attenuation properties, and variations within the bevel, to achieve reliable UT results.
Integrated within the CIVA NDT simulation software platform, a particular effort has been made to obtain comprehensive parametric descriptions of the weld with relevant parameters. Taking advantage of the work already carried out on the CIVA asymptotic ray models applied to smoothly inhomogeneous weld properties  [7] -  [9] , we have developed a new hybrid FE solution which allows us to model the ultrasonic interactions within the component using only an FE calculation kernel. The objective here is to be able to provide a reference solution to the non-expert user to qualify or not other simulation results produced using models that are faster but subject to additional approximations that may lead to numerical artefacts. Such artefacts are sometimes non-negligible and difficult to apprehend a posteriori.
By combining high-order finite element basis functions with a lumped mass technique and an optimised mesh structure, we obtain an efficient FE solution with a small memory footprint compared with other standard finite element codes  [14] ,  [15]. Already implement in recent CIVA simulation modules (guided waves  [16] , coupling for local defect diffraction  [17] ), we have leveraged several enhancements to the calculation kernel, specifically addressing variable anisotropy and attenuation related to curved composite applications  [18]. These improvements have enabled us to adapt these FE techniques to weld part features and add a new hybrid technique coupling ray and FE models.
In the case of a UT simulation where we are trying to determine the ultrasound signal received by a probe, we simply need to capture the FE solution on the surface exposed to the receiver and applied the reciprocity principle as proposed in  [17]. When simulating a full matrix capture (FMC) acquisition, a FE computation is conducted for each emitted shot and subsequently, elementary A-scans are determined for all receiving elements. This process involves performing individual calculations for each element in the reception array. The elementary Ascans represent the response of each receiving element as a function of time, providing information on the detected echoes received by the array probe. This step allows for the reconstruction of the complete FMC dataset, which can then be further analyzed and processed for various inspection purposes like TFM.
The capabilities of the new FE module were demonstrated through short examples of simulated TFM imaging results. Other representative applications of the PAUT inspection simulation can already be carried out to compare this reference solution with other approximate CIVA models, highlighting all the advantages of this new approach. Overall, the continued development and use of these advanced simulation tools offers great potential for improving inspection methods and gaining a better understanding of the phenomena induced by the presence of welds. The future challenges involve accelerating computations, especially in 3D, through innovative coupling techniques that accommodate variations in crack geometry and orientation.
8. Sequence taxonomy was inferred using the naïve Bayesian classifier method  (Wang et al. , 2007)  together with the SILVA database  (Quast et al. , 2012 ), v. 132, as implemented in DADA2 (Callahan et al. , 2016). Additionally, eukaryotic microorganisms were BLASTed  (Altschul et al. , 1990)  against the Protist Ribosomal Reference (PR2) database  (Guillou et al. , 2012) , v4. 10. 0. The PR2 classification was used when the taxonomic assignment from SILVA and PR2 disagreed. We removed ASVs that identified as Metazoa, Streptophyta, plastids, mitochondria, and Archaea since the 341F-primer was not optimal for recovering this domain  (McNichol et al. , 2020). The resulting table contained 2924 ASVs, Table  1A. Next, we removed rare ASVs, keeping ASVs with sequence abundance sums above 100 reads and prevalence above 15% of the samples, i.
Cyanobacteria Our dataset contained 19 cyanobacterial ASVs, which all appeared in the nano-, and nine in the picoplankton. This is against expectations, as Cyanobacteria are part of the pico-plankton. Yet, they have been observed in fractions above 3 µm at BBMO  (Mestre et al. , 2020). Recovering ASVs in the nanoplankton may be due to cell aggregation, particle attachment, clogging of filters or being prey to bigger microorganisms. We blasted the sequences against the Cyanorak database (Garczarek et al. , 2021), v. 2. We performed BLASTN matches against the nucleotide database containing all Synechococcus and Prochlorococcus RNAs with the option -evalue 1. 0e-5. We found 2812 sequences comprising 95 different ecotypes (considering name, clade and subclade), with 93. 84-100% identity. There were 63 sequences (34 different microorganisms) with a similarity of 100% for 11 ASVs.
Availability of data and material The BBMO microbial sequence abundances (ASV tables), taxonomic classifications, environmental data including nutrients will be publicly available after acceptance. The data are of course available to editors and reviewers upon request. Networks are already available. R-Markdowns for data analysis including commands to run eLSA and EnDED (environmentally-driven-edge-detection and computing Jaccard index) are publicly available: https://github. com/InaMariaDeutschmann/TemporalNetworkBBMO.
Competing interests The authors declare that they have no competing interests. Funding This project and IMD received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 675752 (ESR2, http://www. singek. eu) to RL. RL was supported by a Ramón y Cajal fellowship  (RYC-2013-12554, MINECO, Spain). This work was also supported by the projects INTERACTOMICS (CTM2015-69936-P, MINECO, Spain), MicroEcoSystems (240904, RCN, Norway) and MINIME (PID2019-105775RB-I00, AEI, Spain) to RL. FL was supported by the Spanish National  Program FPI 2016 (BES-2016-076317, MICINN, Spain). SC was supported by the CNRS MITI through the interdisciplinary program Modélisation du Vivant (GOBITMAP grant), and the H2020 project AtlantECO (award number 862923).
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Quadratic transfer functions Second-order hydrodynamic loads NEMOH is developed to solve potential flow problems using the boundary element method for computing wave loads on offshore structures. The solver solves the first-order problem in the frequency domain. An extended module enables computation of the second-order loads on a structure in bi-chromatic bidirectional waves. NEMOH is released as open-source, developed, and distributed under the terms of GNU General Public License (GPLv3). Along with the source code, a user manual is available which facilitates the compilation and execution of the source files. In this new release, NEMOH v3. 0 has new features; irregular frequencies removal method, new linear system solvers for enhancing computational efficiency, and a new module for computing the full quadratic transfer function (QTF) of drift forces.
linear system solvers are added for enhancing computational efficiency, and a new module is added for computing second-order wave loads. NEMOH v3. 0 has better accuracy than v2. 0 due to finer interpolation points of the free-surface Green function and a better integration method for constructing the influence coefficients. • For the free-surface piercing bodies problem, it is known that non-unique solutions exist in the boundary integral equation at certain frequencies. In NEMOH, the extended boundary integral equation is applied to remove the irregular frequencies by providing the lid panels on the body waterplane. The second-order loads require the computation of the free-surface forcing terms in the integral forms. These free-surface integrals are essential for the sum-frequency wave loads but may be negligible in the difference-frequency loads.