dataesr/scientific-paragraphs-categorization huggingface dataset:
For the second research question, we employed a consistent system of deductive coding to identify and analyze theory-driven codes across the dataset  (Fereday and Muir-Cochrane 2006). We used the definitions established by  Adloff and Neckel (2019)  for the three SD imaginaries to guide our codebook, and the codification of textual phrases within the three trajectories: Modernization, Transformation, and Control. Each of the members of the research team conducted an initial coding process, and then a second stage of analysis focused on triangulation of the original coding among the three-member research team for this paper. During both of these phases of analysis, the researchers accepted participant comments at face value, although when the context or comment was unclear, elaborations were sometimes requested to clarify confusion that arose during coding and/or triangulation stages.
Results The following sections provide an overview of the study results, beginning with the characterization and descriptions of the actors and their interests, and the two categories and 12 sub-themes that arose from latent meaning analysis of the data associated with tensions and conflicts for the three development conflicts. Next, we present the results of the directed content analysis of the three SD trajectories: Modernization, Transformation, and Control. This section closes with a summary of the results with respect to the overlap and/or interaction of SD trajectories within the dataset.
Inductive coding of the latent meanings of participants' discussions of the conflicts and tensions around development processes for these three contexts helped to dig deeper into participants perceptions and values around the development process and governance. This analysis resulted in 12 themes that were grouped around two main categories: Trust (Fig. 10. 3) and Distrust (Fig. 10. 4). While technical and ideological differences were central to tensions and conflict in all three cases, these categorical perceptions of process and governance around development contexts in Aysén were expressed throughout the dataset, from actors in support and in opposition to the contexts. The Trust category (Fig. 10. 3) was comprised of six main themes, which defined participants' desires for regional development processes: a desire for greater proactivity around transparency, a binding participation process of governance, bottomup decision making, re-empowerment of local groups, decentralization, and The six themes grouped within the Distrust category (Fig.
Manifestations of Sustainable Development Futures Trajectories Directed content analysis revealed numerous manifestations of the three SD futures trajectories -Modernization; Transformation; Control-within the dataset. Manifestations of the SD futures trajectories were related to all three development contexts (Patagonia National Parks Network; HidroAysén; Río Cuervo). Figure  10. 5 illustrates the core concepts of the Modernization SD future trajectory, which worked from an adaptation imaginary, based on practical innovations, technology, and concepts of the green economy, that would push toward more sustainable practices. The sample excerpts from interviews and secondary sources in Fig. 10. 5 illustrate the range of ways in which this trajectory manifested within the interviews and secondary sources, including NBT, new financing mechanisms (i.
e. , Project Finance for Permanence [PFP]), the greening of Chile's image, a pro-business energy agenda based in non-conventional renewable energies, among others. Figure  10. 6 illustrates the core concepts of the Transformation SD future trajectory, which involved imaginaries that involved fundamental social transformation, along a new development model that involved non-consumptive values, buen vivir (living well, in English), utopias, and an overall alignment with the earth system. While the evidence was less prominent for this SD trajectory, several excerpts Although perhaps not to the degree described by  Adloff and Neckel (2019) , the Control SD futures trajectory also manifested within the dataset, as shown in the sample excerpts from interviews and secondary sources, provided in Fig.
Based on principles of Deep Ecology and Doug's vision of a "next economy" that would intimately intertwine economic sustainability and the restoration of natural systems  (Tompkins 2012) , the couple's initial approach to private conservation was centered on a Transformational SD futures trajectory  (Bourlon 2017). Along the trajectory of their work in Patagonia they experienced significant tensions with local and national stakeholders. Thus, as the following excerpt from our dataset reinforces, the Tompkins realized that the cost of a Transformation SD trajectory, might be the failure of achieving the large-scale change they sought:. the objective is not to develop the tourism offer, but to focus on the environment and protection. tourism may be involved, but it is not really the priority.
" And the final part of her excerpt returns to a Modernization SD trajectory, focused on incremental improvements, "In this sense, the creation of national parks has proven to be a successful instrument for the conservation of biodiversity and to contain, in part, this crisis. " While the Tompkins maintained their Transformation SD ideology throughout the trajectory of their work in Chilean Patagonia, our data suggests that they adapted their strategies to work within the political and social settings they encountered. Seemingly, they navigated between Modernization and Control SD imaginaries and tactics to maneuver between local and national actors, agendas, and decisionmaking processes. These tactics, which we have termed, SD agility, merit additional study, as they may represent an important capacity for SD futures trajectories.
Acknowledgements This work was supported by  Chile's National Research and Development Agency (ANID)  under  ANID's Regional Program   R17A10002 ; the  CIEP R20F0002  project;  ANID PAI79170138 ;  ANID FONDECYT Regular 1230020 , and the  CHIC-ANID PIA /BASAL PFB210018. We are grateful to  Aldo Farias Herrera ,  Universidad Austral de Chile , for his support with the elaboration of the cartography in Fig. 10. 1, and  Patricio Segura Ortiz , journalist and director of the private Corporation for the  Development of Aysén , for his permission to share the photographs in Fig. 10. 9.
2016; Cerqueira et al. 2002 ). An SSS ≥ 4 was considered abnormal  (Ziadi et al. 2011). For the quantitative part, left-ventricle (LV) rest myocardial blood flow (MBF), stress MBF, and myocardial flow reserve (MFR) were obtained by processing data with the fully automated FlowQuant software (Ottawa Heart Institute, Ottawa, Canada)  (Dunet et al. 2016; Klein et al. 2010). LV ejection fraction (LVEF) and transit ischemic dilation (TID) ratio was obtained by processing data with the Myometrix software (GE Healthcare, Waukesha, WI, USA). Quantitative analysis was assessed globally and for all 3 vascular territories derived from standard segmentation: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). A global LV MFR < 2 was considered abnormal, as previously documented  (Herzog et al.
All brain regions were automatically segmented from the 3D T1-MPRAGE sequences using the MorphoBox research application  (Schmitter et al. 2015) ; thus, absolute and relative volumes (in mL and % of the total intracranial volume [TIV], respectively) were provided for every cerebral parenchymal structures (total gray and white matter, central nuclei, hippocampus, brainstem, lobar gray and white matter, intracranial cerebrospinal fluid, ventricular system). The z-score of each structure was obtained by comparing each volume to the corresponding age-/sex-matched normative range built from healthy subjects (N = 303, 50. 8% males, min-max age = 19-90y, median age = 73. 25y) collected by the ADNI and studies following the ADNI guidelines  (Wyman et al. 2013). The software also estimates the volume of abnormal white matter (WMab) and the lesion load in the deep gray nuclei (GMab)  (Fang et al.
MR data Of 370 patients, 70 had non-lacunar stroke sequelae or sequelae from other disease on brain MRI (28 had only brain sequelae and 42 also had obstructive CAD) and were excluded from the MRI quantitative analysis. Of the 300 remaining patients with MRI, 114 were excluded due to obstructive CAD without brain sequelae. One hundred and twenty-three could not be segmented because the 3D T1-MPRAGE that did not follow  the ADNI guidelines (97 with normal myocardial perfusion and 26 with cardiac SVD). The 3D T1-MPRAGE was segmented in 63 subjects with normal myocardial perfusion or cardiac SVD (Fig. 1 ). Compared to patients with normal myocardial perfusion, patients with SVD had similar Fazekas score (P = 0. 45) but lower z-score for right and left frontal WM volumes (P = 0. 024 and P = 0. 021) and higher z-score for left and third ventricles (P = 0.
Numerical investigation 3. 1. Basilisk solver The Navier-Stokes equations for incompressible gas-liquid two-phase flow with variable density and surface tension are simulated using the Basilisk library. The Basilisk package, developed as the successor to the Gerris framework  (Popinet 2003 (Popinet , 2009)) , is an open-source program for solving various systems of partial differential equations on regular adaptive Cartesian meshes with second-order spatial and temporal accuracy. A quadtree-based adaptive mesh refinement scheme is used in 2-D calculations to improve computational efficiency by concentrating computational resources on important solution domains. The generic time loop is implemented in the numerical scheme and the time step is limited by the Courant-Friedrichs-Lewy condition.
2013; Deike et al. 2015 Deike et al. , 2016;; Derakhti & Kirby 2016; De Vita et al. 2018; Mostert et al. 2022) , along with the shallow-water dataset from  Boswell et al. (2023)  and the present study. The breaking dissipation in this study falls between the previously established deep-water regimes and the shallow-water breaking waves documented by  Boswell et al. (2023) , and shows favourable consistency within the range of overlap between our data and Boswell's data. Furthermore, our data extend the left-hand boundary of this range by extending the nonlinearity parameter, specifically, H b /d from 0. 85 to 0. 75. This particular range displays a discernible diminishing trend in the breaking parameter b as the nonlinearity parameter F decreases. A similar trend can also be observed in Boswell's data.
However, there is a clear discontinuity between the deep-water and shallow-water regimes, rendering a single power-law scaling inadequate for capturing both datasets. As introduced by  Romero et al. (2012) , a heuristic examination of the breaking threshold was undertaken to fit the extensive experimental and numerical observations in deep-water scenarios, yielding a semiempirical formulation b = 0. 4(S -0. 08) 5/2 , where S ∼ F under deep-water conditions. Notably,  Boswell et al. (2023)  made a commendable effort to address the discontinuity across various depth regimes using the same concept of breaking threshold dependence, and a slope threshold F * = 0. 7 was determined in Boswell's shallow-water solitary wave cases. In our cases, the critical breaking threshold F * was determined to be 0.
65 through the best fit to our numerical data. The expression b = 0. 212(F -0. 65) 1. 5 collapses the DNS data presented in the present study favourably. However, the proposed semiempirical scaling fails to encompass the DNS data of shallow-water solitary breaking waves from  Boswell et al. (2023). Therefore, further endeavours should be made to develop a comprehensive breaking parametrization. Nevertheless, the available datasets summarized in figure  16  offer valuable insights into this unsolved problem. The data suggest the possibility of a varying breaking threshold, particularly in the context of transitioning between deep and shallow water conditions. A determination relation governing the breaking threshold could be proposed to accommodate the different depth regimes. This remains to be explored in future work.
Funding. This work is supported by a scholarship from the  China Scholarship Council (CSC)  under grant no. 201906090270. Declaration of interests. The authors report no conflict of interest. Author ORCIDs. Shuo Liu  https://orcid. org/0000-0002-8530-8359; Hui Wang https://orcid. org/0000-0001-9733-0150; Annie-Claude Bayeul-Lainé https://orcid. org/0000-0002-3799-0218; Cheng Li https://orcid. org/0000-0001-6045-6139; Joseph Katz https://orcid. org/0000 -0001-9067- 2473; Olivier Coutier-Delgosha https://orcid. org/ 0000-0002-4881-7058.
2018; Dirrichs et al. 2018; ) , and the effect of both short-term exercise  (Payne et al. 2018a ) and long-term training  (Avrillon et al. 2020; Miyamoto et al. 2019). To determine the correct interpretation of the SWE technique, it is still necessary to expand the understanding of normal tissue-specific variation between individuals from different athletic groups and according to their physical status. Therefore, the aim of this study was to acquire a large dataset of internal AT displacement and passive AT shear wave velocity and TS muscle shear modulus in athletes from different sports. Furthermore, we investigated whether (1) previous exercise, (2) history of lower limb injury, and (3) individual characteristics of sex and sport specialisation are factors that distinguished AT displacement or passive AT shear wave velocity and TS muscle shear modulus.
Data collection For the resting AT SWE examination, participants were lying prone with both feet fixed at 25° ankle plantarflexion. The SWE elasticity range was set from 0 to 800 kPa and the image depth was set to ~ 2. 5 cm. Using B-mode ultrasound, the proximal head of calcaneus was identified and marked on the skin. A second mark was placed three centimetres proximally. The SWE map of the AT was recorded longitudinally from three distal locations: first, with the proximal head of the calcaneus aligned in the centre of the image (ATdist), and then moving the transducer 18 mm (ATmid) and 48 mm (ATprox) proximally from the first location. The region of interest was set as wide as possible to cover the entire AT. The transducer was held still for ~ 5 s during each recording (Fig. 1a-d ). Triceps surae SWE imaging locations were determined using B-mode ultrasound and marked for longitudinal probe placement with the participants lying prone with both feet relaxed over the end of measurement table.
For the gastrocnemius, the area of greatest muscle bulk was used. Soleus was imaged laterally from the area where the muscle lies superficially, distal to LG muscle-tendon junction. Next, participants were seated on a custom-built ankle dynamometer with the hip in 60° flexion and the knee fully extended (Fig. 1e ). The foot was firmly attached to the dynamometer footplate and the knee was secured in extension with an inelastic strap. The axis of the dynamometer was aligned with the presumed centre of rotation of the ankle. The neutral ankle position (0°) was considered as the foot was perpendicular to the leg. Torque and ankle angle data were sampled at a frequency of 1 kHz using a 16-bit analogue-to-digital converter (Power 1401, Cambridge Electronic Design, Cambridge, UK) connected to a computer.
Torque and angle data were recorded using Spike2 software (v. 6. 17, Cambridge Electronic Design Limited, Cambridge, UK). Participants were instructed to remain as relaxed as possible, when the ankle joint was rotated at 2°/s from 40° plantarflexion to a maximum of 20° dorsiflexion. Each participant was familiarised with the movement prior to recording. If participants reported discomfort during the stretch towards dorsiflexion 1 3 or if the simultaneously observed torque level exceeded a set limit of 15 Nm, a lower range of motion of 15° dorsiflexion was used. This range could be further reduced to 10° if necessary. Elasticity range was set to a maximum of 0 to 600 kPa and image depth was adjusted according to the individual muscle thickness. For conditioning, participants performed repetitions of submaximal isometric contractions.
Data processing Shear wave elastography recordings were processed using a custom software developed for MATLAB (ElastoGUI, v. R2021b, MathWorks Inc, Natick, MA, USA) with semiautomatic processing. Each pixel of the SWE colour maps was converted to SWV and then to shear modulus based on the recorded colour scale. For each SWE recording, the area of analysis was adjusted to cover the largest possible area within the superficial and deep aponeurosis while avoiding artefacts. For AT, acceptable saturation and void levels of < 3% and < 0. 1% were used, and for TS muscles the limits were set to < 1%. In ATdist, SWV variation caused by the calcaneus was excluded (see Fig. 1a ). In TS muscle SWE processing, SWV variation due to reflection from the aponeurosis was excluded to ensure that the assessment was restricted to muscle tissue only (e.
g. Fig. 1j ). In results, AT SWE measurements are reported as mean SWV (m × s -1 ). TS muscle SWE measurements are given as mean peak shear modulus (kPa) to represent the elastic properties of the muscle under passive stretch loading. All SWE data are provided in kPa and as SWV values in the Supplementary Information (SI1) to facilitate global scientific data comparison. Absolute differences in passive shear modulus between TS muscles (MG-LG, MG-SOL, LG-SOL) were also calculated. Mean (SD) values of the analysed areas of the three muscles and the three AT SWE measurement locations were as follows: SOL 0. 8 cm 2 (0. 5); MG 2. 1 cm 2 (0. 7); LG 2. 0 cm 2 (0. 7); ATdist 0. 3 cm 2 (0. 1); ATmid 0. 9 cm 2 (0. 2); ATprox 0. 7 cm 2 (0. 2), respectively. Saturation was present in 124 analysed AT SWE recordings (average saturation % in different locations: ATdist 0.
7%; ATmid 0. 7%; ATprox 0. 6%). Changes in TS muscle shear modulus during passive ankle range of motion were determined to differentiate the muscle-specific relationship during passive stretch. In addition, we calculated the percentage contribution of each TS muscle from the total summed TS muscle shear modulus to describe the contribution of each muscle to resistance during the passive range of motion. Torque signal was filtered using a fourth order Butterworth low-pass filter with a cutoff frequency of 8 Hz. Internal AT displacement was assessed in MATLAB (v. R2021b, MathWorks Inc, Natick, MA, USA) using 2D speckle tracking  (Slane and Thelen 2014). The region of interest was manually positioned over the distal tendon with its size individually adjusted to ensure that only tendinous tissue was included.
Within the region of interest, a grid of six locations across the thickness of the tendon and 11 locations across the length of the tendon was generated (e. g. Fig. 1f, g ). Each tracking was visually monitored to ensure the quality of data processing. The mean displacement (mm) was calculated as the average displacement across the six tracked tendon locations. Mean displacement was further examined by dividing the tendon into anterior and posterior halves  (Franz et al. 2015). This was done to assess whether any adaptations were localised to different parts of the AT. Non-uniformity was calculated as maximum-minus-minimum displacement within the tracked locations across the tendon.
Statistical analysis All statistical analyses were performed with IBM SPSS Statistics for Windows (v. 28. 0, Armonk, NY) and visualised using JASP (JASP v. 0. 16. 4, Amsterdam, The Fig. 1  Measurement protocol for AT shear wave velocity, TS muscle shear modulus, and AT displacement. a-c SWE and B-mode images of AT at three different measurement sites; d representation of the SWE imaging sites of AT; e participant position on the ankle dynamometer when f-g internal AT displacement was assessed during submaximal isometric contraction, and when h-j SWE of the medial gastrocnemius, lateral gastrocnemius, and soleus muscle was measured during passive ankle dorsiflexion. Example in j shows that although the SWE region of interest was initially placed in the middle of the muscle, the changes in muscle position during dorsiflexion caused the region to overlap the aponeurosis, which shows higher shear modulus in the upper part of the image.
Sex differences We found no sex differences in the measured variables. In this study setting, the internal AT displacement measurement was performed with the same absolute, rather low torque of 50 Nm for all participants, which causes the torque to have differential percentage of the expected MVC between the sexes. However, at such a low torque level, the sex differences may not be as clear as at higher torques. Future studies should consider individualising the measurement by associating the data collection with the same relative torque level. Regarding SWE imaging, there is conflicting evidence of differences between sexes in the previous literature. Several previous publications have suggested that passive muscle and tendon stiffness does not differ according to sex (e. g. Chino and Takahashi 2016; Souron et al.
Limitations This study has some limitations. First, surface electromyography was not used to ensure that participants were relaxed during the SWE measurements. Participants were instructed to remain relaxed, and relaxation was observed from the real-time torque signal during the SWE recordings of the TS muscles. During data processing, both SWE and torque data were checked for possible muscle contractions to outline the possible influence on the results. Second, TS muscle SWE measurements were performed consecutively for each muscle belly. Thus, each muscle was successively subjected to a slow passive stretch to ankle dorsiflexion for a total period of approximately 35 s with approximately 1 min of rest periods between muscles. A recent study by  Umehara et al. (2021)  showed an acute decrease in shear modulus in response to a continuous 30 s muscle stretch.
In this paper, we are comparing HMMS with HTS. HTS is the most competitive of all the conventional methodologies because it only uses water as a solvent and it has a relatively low residence time, compared with the other processes. We validated the data from scientific and technical literature related to HMMS and HTS syntheses reactions with several experiments. The experiments for HMMS were developed by DEASYL SA (a spin-off company of EASYL SA) in their laboratories in Switzerland and the experiments for HTS were performed at the University of Málaga (UMA) in Spain. We compare these processes using the Life Cycle Assessment (LCA) methodology. LCA provides a comprehensive and holistic view of the environmental loads of the products or services understudy, covering a wide set of environmental impact categories  (Baumann and Tillman, 2004; Molander et al.
Hydro-thermal synthesis (HTS) According to the scientific literature  (Wang et al. , 2008) , this process consists of heating the stoichiometric mixture of calcium hydroxide (Ca(OH) 2 ) and zinc oxide (ZnO) at 75 °C for 24 h (12 h of reaction and 12 h of aging) with an excess of distilled water. CAZN crystals are retrieved by centrifugation, washed with demineralized water two times, and dried at 50 °C for 2 h in vacuum. Unlike in the HCS, the HTS does not require a strong alkali medium or other solvent than water. The reaction was replicated by DEASYL SA at the UMA for the purposes of our research. High conversion rates were achieved in only 10 h. In addition, the crystals were obtained at ambient temperature with no need of heating the mixture to 75 °C. To be in the safe side, the HTS inventory data used for the comparison with HMMS are the best ones: the primary data that were tested in UMA.