dataesr/scientific-paragraphs-categorization huggingface dataset:
Figure1. Examples of moist processes that influence the water vapor isotopic composition of the trade-wind environment around Barbados (yellow landmass) and that can be studied using the EUREC 4 A-iso dataset collection. Black arrows indicate processes expected to increase water vapor isotope ratios, while white arrows indicate processes expected to lower them. The ships and aircraft in the schematic represent the six mobile EUREC 4 A-iso in situ sampling platforms.
Franziska Aemisegger and Leonie Villiger were funded by Swiss National Science Foundation (SNSF) grant no. 188731, Sebastian A. Los and Joseph Galewsky were supported by NSF ATM 1937583, Estefanía Quiñones Meléndez and Simon P. de Szoeke were supported by NOAA Climate Variability and Predictability Program Award NA19OAR4310375, Dariusz B. Baranowski was supported by Poland's National Science Centre grant no. UMO-2018/30/M/ST10/00674, Marina Dütsch was funded by NSF grant AGS-1938108, and Dean Henze and David Noone were supported by NSF Climate and Large-Scale Dynamics Award 1937780. In addition, this material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement 1852977.
For Derek Coffman and Patricia K. Quinn this is PMEL contribution number 5324. This work is also a contribution to the LEFE/IMAGO-GMMC project EUREC 4 A-OA, to the JPI-Climate and JPI Oceans project EUREC 4 A-OA, and to the TOSCA SMOS-Ocean and EUREC 4 A-OA projects supported by CNES (Centre National d'Études Spatiales). Support for these projects was also obtained from IFREMER, the French Research Fleet, the French Research Infrastructures AERIS and ODATIS, IPSL, the "Chaire Chanel" of the Geosciences Department at ENS, and the European Union's Horizon 2020 research and innovation program under grant agreement no. 817578 TRIAT-LAS. The NOAA Climate Program Office, under the Climate Variability and Predictability Program, supported ATOMIC and the deployment of the P-3 and Brown. European Research Council (ERC) grant no.
694768 (EUREC 4 A) funded the ATR operations. We also thank those programs that supported the satellite data processing. TROPOMI data processing was carried out on the Dutch national E-infrastructure with the support of the SURF Cooperative. The MUSICA IASI retrievals were initiated during the project MUSICA (funded by the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC Grant Agreement no. 256961). The MU-SICA IASI work received financial support through MOTIV and TEDDY (funded by the Deutsche Forschungsgemeinschaft under project IDs/Geschäftszeichen 290612604/GZ:SCHN1126/2-1 and 416767181/GZ:SCHN1126/5-1, respectively), and INMENSE (funded by the Ministerio de Economía y Competividad from Spain, CGL2016-80688-P). MUSICA IASI retrieval calculations were performed on the supercomputers ForHLR and HoreKa, funded by the Ministry of Science, Research and the Arts Baden-Württemberg and by the German Federal Ministry of Education and Research.
Cartes auto-adaptatives (SOM : Self-Organizing Maps) ou réseau de Kohonen Les SOMs sont une classe particulière d'ANN et sont largement utilisés comme outil de réduction de la dimensionnalité et de visualisation dans l'analyse exploratoire des données. L'objectif principal des SOMs est de transformer un espace d'entrée complexe de haute dimension en un espace de sortie de faible dimension (généralement bidimensionnel) plus simple (J. -M. Commenge, s. d. ). Une carte autoadaptative se compose de plusieurs neurones ou noeuds. Chaque noeud est caractérisé par un vecteur poids de la même dimension que le jeu de données. Plus de détails concernant la sélection de la taille de la carte, le nombre d'itérations se trouvent dans  Asan et Ercan (2012). Les cartes auto adaptatives ont été générées via le logiciel R et le package kohonen  (Wehrens et Kruisselbrink 2018).
Data Collection To assess the device with the targeted caregivers, the data were collected by inter viewing nurses on February, 2023, using a 20-item questionnaire covering 4 areas: (i) Clin ical assessment; (ii) Technical and ergonomic assessment; (iii) Nurse satisfaction; (iv) Im pact on fatigue. The candidates' eligibility for the study was assessed, and a date wa scheduled to train the candidate in the use of the exoskeleton. The questionnaire was give to each participant.
Data Collection To assess the device with the targeted caregivers, the data were collected by interviewing nurses on February, 2023, using a 20-item questionnaire covering 4 areas: (i) Clinical assessment; (ii) Technical and ergonomic assessment; (iii) Nurse satisfaction; (iv) Impact on fatigue. The candidates' eligibility for the study was assessed, and a date was scheduled to train the candidate in the use of the exoskeleton. The questionnaire was given to each participant.
Step 1: Literature Review and Model Constitution A literature review of red and yellow flags was conducted in order to gather the latest data available in the literature on this subject. The research was conducted using the following 4 databases: Medline, Cochrane Library, Embase and Google Scholar; the period studied was from 2015 until March 2021. The model was constituted following systematic bibliographic research. These search terms were extended with specific terminology and synonyms using Boolean operators, and the respective Medical Subject Headings are reported in Appendix A. Some specific filters or limits were used; for example, only English articles were included. The selected studies were then used to create a model that included triage and therapeutic options to manage patients with low back pain.
Study population Consecutive patients with benign or malignant thyroid disorders who underwent total thyroidectomy (in one-step) performed at a single tertiary center from January 2018 to December 2019 were enrolled in the study. Data were retrieved from a maintained institutional database, whose creation was approved by Institutional Research Ethics Committee (Ethic Committee of Paris region VI in Pitié Salpêtrière Hospital, registration number 20200115171338). According to the French law, retrospective studies built exclusively on data, do not need the approval of "committees for the protection of individuals". The main indications for surgery were multinodular compressive goiters, malignant or suspicious nodules on ne-needle aspiration biopsy, Grave's disease, and multinodular goiters with hyperthyroidism.
The exclusion criteria from the prospective database were previous neck surgery, concomitant parathyroid surgery, and inclusion in an auto uorescence study. The exclusion criteria after reviewing the operative and pathology reports were intentionally removed parathyroid glands (perioperative discovery of parathyroid adenoma). Cases of intrathyroidal IP were also excluded to keep the study focus on avoidable IP (Fig. 1 ). Most of the data were prospectively collected from our institutional database. Demographic characteristics included: age, sex, body mass index, and medical history. Operative characteristics included lymph node dissection (LND) and autotransplantation of parathyroid glands. Pathologic characteristics included the size and weight of the thyroid and the nal thyroid pathology.
Statistical analysis Our database was prospectively maintained. Statistical analyses were performed using R software. The normal distribution of quantitative variables was assessed using histograms. Proportions were compared using the chi-squares test or Fisher's exact test, as appropriate. Student's t-test or analysis of variance was used for quantitative variables. Logistic regression analysis was performed. Values are expressed as mean ± standard deviation. Statistical signi cance was set at p < 0. 05.
Clinical characteristics As seen on Fig. 1 , 1592 consecutive patients underwent one-step total thyroidectomy between January 2018 and December 2019. A total of 28 patients were excluded based on prospective database including 24 concomitant parathyroid surgery. Among the 1564 remaining eligible patients, 27 were exclude after medical chart review, including 25 for intrathyroidal parathyroid gland removal. A total of 1537 total thyroidectomies were included (1187 [77. 2%] women, median age : 51. 9 years (range: 11. 8-92. 7 years)). Concomitant CLND was performed in 472 cases (30. 7%). A total of 569 (37%) cases of thyroid malignancy were found in pathologic examination, including 497 papillary carcinoma (87. 3%), 32 follicular carcinoma (5. 6%), 24 medullary carcinoma (4. 2%), 8 papillary with follicular carcinoma (1.
Strength and limitations The strengths of our study were that despite its retrospective nature, patient data were recorded consecutively and prospectively with great thoroughness. Calcium and parathormone blood levels were systematically collected and to ensure that all cases of transient and permanent hypocalcemia were recorded. The long-term follow-up allowed us to determine the long-term consequences of IP. However, the present study had some limitations. Most surgeons did not document the number of identi ed parathyroid glands or the macroscopic vascularization, precluding any correlation analysis between parathyroid identi cation and IP. We believe that parathyroid glands do not need to be routinely identi ed and assessed if they are not encountered during thyroidectomy  (33). We excluded patients whose pathology reports mentioned only "parathyroid tissue" to include only those who had 1 or several whole gland(s) incidentally removed.
Declarations Ethics approval and consent to participate Data were retrieved from a prospectively maintained institutional database, whose creation was approved by the Institutional Research Ethics Committee (Ethic Committee of Paris region VI in Pitié Salpêtrière Hospital, registration number 20200115171338). Informed consent was obtained from all subjects and/or their legal guardians. This being a retrospective study without new data collected, in accordance with the French recommendations, it does not require ethical committee approval. This monocentric retrospective cohort study was performed in accordance with the Declaration of Helsinki.
This study explored the use of YouTube children's educational videos to enhance early childhood English language proficiency. The study utilized a qualitative research design, and data were collected through semi-structured interviews with 10 parents of preschool-aged children. The findings of the study revealed that parents used a variety of YouTube children's educational videos to enhance their children's English language proficiency, including videos that taught basic English vocabulary, songs, nursery rhymes, grammar, and sentence structures. Participants also identified perceived benefits and drawbacks of using YouTube children's educational videos, such as improvements in vocabulary and grammar skills, exposure to the English language, and concerns about addiction to watching videos, exposure to inappropriate content, and quality and accuracy issues.
Data Sources and Keywords Definition In this review, the Scopus and Web of Science databases have been used as a data source with the keywords ("digital twin" OR "digital model" OR "digital shadow" OR "simulation model") AND ("post-harvest" OR "agri food" OR "agrifood" OR "agri-food"). Because many publications on this topic have been published without consistent use of terms, the search was carried out with considerable care, using a wide range of keyword combinations. When choosing keywords, several elements related to digitization in the agriculture and food supply chain were considered. Since this review aims to investigate how DTs have been used in recent years in the agri-food supply chain, the search includes published papers from 1 January 2019 to 20 August 2022. After eliminating duplicates, the authors evaluated each article to determine whether it met the inclusion criteria.
Screening and Eligibility Check Only works that have been peer-reviewed and published in journals, conferences, and book chapters were considered during the preliminary screening stage. All the articles collected from the two databases (Scopus and Web of Science) were checked for duplication using the reference management tool (Mendeley), followed by reading the abstracts and full texts of the selected articles. The final screening and eligibility assessment were done based on the following criteria. Screening Exclusion Criteria (SEC): • SEC1-Is it a peer-reviewed journal article, a book chapter, a review, or a conference paper? • SEC2-Does the document illustrate the use of DTs in the agri-food supply chain? Eligibility Exclusion Criteria (EEC): • EEC1-Is the full document available for reading? • EEC2-Does the paper discuss digital models, digital shadows, or DTs in the agri-food supply chain? • EEC3-Does the paper answer at least one of the research questions that have already been set?.
Additionally, the virtual entity needs to have access to cloud applications, data, and knowledge for it to work properly. In the supply chain DT development, experts are increasingly seeking real-time data such as demographic data collected from various supply chain participants or stakeholders that can be used to get information regarding the location of truck routes, fulfillment centers, retail outlets, consumers, etc. , to better understand logistics. These data can be directly entered into databases like the Enterprise Resource Planning (ERP) database and the production system to build a DT with a simulation tool  [59]. Furthermore, DTs can utilize data from transportation management systems (TMS) and customer relationship management systems (CMS)  [7]. It is also possible to combine internal data from the systems of the actors with external data sources (e.
Machine learning models can be trained in a variety of ways, including through supervised and unsupervised learning. The model training data could include horticultural-product storage conditions as well as the measured biological response of fresh horticulture products over time. Recent applications of DTs in the agri-food supply chain, mostly in the fruit supply chain, have emphasized physics-based DTs  [15, 16, 29, 30, 44, 45, 47, 48, 55, 60, 61]. Because of advancements in prediction accuracy and computational performance, the adoption of a physics-based DT is growing rapidly  [5]. Using mechanistic models (e. g. , heat and mass transfer) and kinetic models (quality deterioration), a DT can forecast when food will change its quality over time, including during storage and shipment. With such models, more emphasis has been placed on monitoring fresh fruits and vegetables, contributing to product loss, particularly during transcontinental shipments.
The connection needs to have enough broadband to deliver data as needed by the service. In addition, farmers need instruction in using basic computers and tablets, as well as knowledge of how the IoT works. In practice, mapping and obtaining a detailed real-time snapshot of the supply chain is challenging. The simultaneous validation of all model-output parameters is an additional barrier to the use of DTs in supply chain applications  [44]. Moreover, the stakeholders in the cold chain, such as retailers, require specific evidence to demonstrate the benefits in shelf life that may be obtained with certain digital solutions. Unfortunately, pilot studies to derive such validations are sometimes costly and time-consuming. Further implementation issues include a lack of detailed methodology and standards, a lack of clear data governance, and difficulties gathering and storing massive datasets  [20, [92] [93] [94].
The literature search was conducted using the Web of Science and Scopus databases, which are commonly used data sources for literature analysis. Despite their large citations, these databases have limitations in terms of document availability and coverage. Many reports regarding the progress of DT implementation by the companies are documented in white papers and other publications that are not included in both databases. Despite our best efforts to assure inclusiveness, our study is limited to publications that have undergone peer review. So, additional related work that has been published in other databases or languages other than English might be missed during our analysis. As a result, scholars interested in DT applications in the supply chain could consult additional sources. Researchers might also focus on evaluating the solution's effectiveness in terms of sustainability and feasibility, which will boost confidence in industries within the agri-food supply chain to incorporate this technology into their business processes.
G4SSA and CCMI-prescribed aerosol fields The complex contribution of aerosol microphysics, chemistry and dynamical changes in determining the overall stratospheric response has been highlighted in many of the general GeoMIP experiments  (Visioni et al. , 2021b) ). One way to constrain part of the response may be through prescribing an identical aerosol field in different models, in order to obtain a similar perturbation and understand how and why models differ in their projection of stratospheric heating and chemical changes to an identical perturbation; such an experiment can also overcome the lack of a detailed interactive aerosol treatment in some ESMs. Tilmes et al. (2015)  first proposed a similar experiment called G4 Specified Stratospheric Aerosols (G4SSA), offering the community a prescribed aerosol dataset determined using the ECHAM5-HAM microphysical model.
Patients and setting This is a retrospective study performed on data collected prospectively in a 24-bed ICU of a university hospital (CHU Rennes, Rennes, France). Patients were followed until day 60 after the diagnosis of ARDS. The study was approved by the hospital's ethics committee (number 20-39). We followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology; www. strobe-statement. org) recommendations for cohort studies. All consecutive patients aged over 18 years who were admitted between 1 October 2009 and 1 February 2022 for ARDS with arterial oxygen tension (P aO 2 )/inspiratory oxygen fraction (F IO 2 ) ⩽150 mmHg and a positive result on a real-time reverse transcriptase (RT)-PCR assay for influenza or COVID-19 on a respiratory specimen were included.
Data collection Day 1 was defined as the day the patient first met the criteria for moderate-to-severe ARDS. Demographic characteristics and the Simplified Acute Physiology Score (SAPS) II score  [24]  were recorded on admission to the ICU. Duration of symptoms suggestive of viral infection before admission to the ICU, treatment with high-flow nasal oxygen before intubation and prior treatment with angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker were recorded. The following data were also recorded: vaccination against influenza and complete vaccination against SARS-CoV-2, and comorbidities including arterial hypertension, obesity, diabetes mellitus, previous coronary artery and/or vascular disease with treatment, aplasia and/or recent chemotherapy for a solid tumour or haematological disease, and COPD.
Statistical analysis Data are expressed as count and percentage for categorical variables. Continuous variables were initially assessed for normality and are presented as mean and standard deviation, and when not normally distributed as median and interquartile range. The Chi-squared test was used to compare categorical variables and the Mann-Whitney U-test was used to compare continuous variables. In a first step, we performed analyses on the whole population. We used a linear mixed model to analyse repeated values and assess longitudinal changes in respiratory parameters and SOFA scores from day 1 to day 5 of ARDS. COVID-19 and influenza were included as fixed effects and we used a random intercept to take into account the heterogeneity across subjects. We used Bonferroni's correction for post hoc analysis of repeated values.
In a second step, we performed an exploratory analysis to determine whether COVID-19 patients can be reliably distinguished from influenza patients based on respiratory parameters recorded on day 1 of ARDS. Principal component analysis (PCA) was performed using day 1 respiratory parameters. PCA is a dimensionality reduction method used to reduce the dimensionality of large datasets  [31]. Its goal is to extract the important information from the dataset. After transformation the number of variables is reduced and still contains most of the information of the initial dataset (the principal components, which are the linear combination of the original variables). Databases are then easier to explore and visualise. In a third step and in order to compare outcomes of patients, a propensity score near-neighbour with 0.
Objectives: To monitor the results of PIPAC directed therapy based on data from the International Society for the Study of the Pleura and Peritoneum (ISSPP) PIPAC database. Methods: Analysis of data from patients entered between June 15th, 2020, and February 28th, 2023. Results: Twelve centers reported 2,456 PIPAC procedures in 809 patients (median 2, range 1-18) with peritoneal metastasis (PM) from different primary tumors. Approximately 90 % had systemic chemotherapy prior to PIPAC. Twentyeight percent were treated in prospective protocols. Overall non-access rate was 3. 5 %. Concomitant surgical procedures were performed during PIPAC in 1. 6 % of the patients. Median length of stay was 2 days. A total of 95 surgical complications were recorded, but only 22 % of these were graded ≥3b. Seventeen-hundred-and-three adverse events were noted, and 8 % were classified ≥3.
The rate of complete or major histological response (peritoneal regression grade score, PRGS≤2) increased between the first and the third PIPAC in the group of patients who were evaluated by PRGS, and a PRGS ≤2 or a reduction of the mean PRGS of at least 1 between first and third PIPAC were observed in 80 %. Disease progression (50 %) or technical issues (19 %) were the most important reasons for stopping PIPAC treatment. Median overall survival from first PIPAC directed treatment varied from 10. 7 months (CI 8. 7-12. 5) in gastric cancer to 27. 1 months (16. 4-50. 5) in mesothelioma. Conclusions: The ISSPP PIPAC database provides substantial real-world data supporting the use of PIPAC directed therapy in patients with PM from different primary tumors.
Introduction Pressurized intraperitoneal aerosol chemotherapy (PIPAC) directed therapy has been used for the treatment of unresectable peritoneal metastasis since its first use in humans in 2011  [1]. Substantial research efforts on dose-finding, safety profile, response evaluation, and subsequent prospective phase II trials have provided insight into the oncological potential of this new treatment platform. However, PIPAC directed therapy has not yet reached its final maturity due to lack of randomized trials, and PIPAC is still considered experimental. Having reached stage 2b of the IDEAL recommendations  [2]  a prospective international PIPAC registry group and database were advocated by the International Society for the Study of the Pleura and Peritoneum (ISSPP) Executive Committee. An international PIPAC database was officially launched by ISSPP in June 2020.
Financial aspects The ISSPP PIPAC database is funded and hosted by Open Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark, in close collaboration with Odense PIPAC Center (OPC). Maintenance, inclusion of new centers, change of variables, reminders to including centers, and data analysis are performed by the ISSPP PIPAC Research Project Manager (CWF) supported by the ISSPP Registry Group chairman (MBM) and the ISSPP Registry Group. The work of the Research Project Manager was supported by an annual grant from the ISSPP until January 2022. Since then, the ISSPP PIPAC database has been solely funded by OPC and OPEN.