dataesr/scientific-paragraphs-categorization huggingface dataset:
Olive Waste and by-Products In the European countries, the total area covered with olive trees accounts for 4. 59 million ha, 55% of this area being in Spain, 23% in Italy, and 15% in Greece (https://appsso. eurostat. ec. europa. eu/nui/show. do?dataset=orch_olives3&lang=en, accessed on 06 January 2021). In 2018, the total production of olives for olive oil in the European Union was 12. 9 million tons. Spain accounted for 71. 9% of the European Union total harvested production of olives for olive oil (9. 3 million tons of olive oil produced in Spain), followed by Italy with 14. 7% and Greece with 7. 3%  [26]. Olive tree cultivation and the olive oil industry involve different processes, such as cutting branches and wood from pruning, and leave removal, olive washing, grinding, beating, and separation of the oil from extraction.
Methodology In the period going from 11/2019 to 02/2020, various data was collected by the authors via an extensive online search and review of company websites, presentations and reports, online articles, research project reports, specialized professional websites and newsletters (e. g. , Olive Oil Times). This online search was done via Google. In addition, experts (e. g. , from France Olive) and research colleagues were asked for existing initiatives that valorize olive waste and by-products. Academic articles reporting business case studies on olive waste and by-product valorization were searched on Web of Science, Scopus, and Google Scholar, but without results except from a very few examples  [32, 64, 65] , as literature in this domain is overwhelmingly focused on technological aspects of olive waste treatment.
For the 41 selected initiatives, the online data found was downloaded and saved in Portable Document Formats (PDFs). This data from the webpages was introduced into NVivo. NVivo is a software tool for qualitative analysis of textual and audio-visual data sources, that allows organizing and coding multiple data sources, assigning attributes to data for comparison, and querying and visualizing data  [66]. For classifying the initiatives, each one was coded regarding its type of business, geographical location (country), the priority of waste valorization (principal or side activity), business drivers, business model canvas elements, resources valorized, and outputs. The outline of the methodology is presented in the following Figure  3. The key data of each initiative was then synthesized and presented in a table according to the following main criteria (cf.
Electrophoresis on 2% agarose gels was performed to check for successful amplifications. Microsatellites raw data were analysed using The Genescan software (Applied Biosystems, version 3. 7). The different alleles corresponding to each isolate were computed to generate a similarity matrix (according to Dice coefficient), which was used to generate an aggregation of the isolates by the PHYLIP software (version 3. 6) [61] according to the neighbour-joining method.
Fermentation Results Analysis and Sensory Paired Comparison Test For technological and fermentation data, the Xlstat software (Addinsoft, version 1. 1. 1084) was used to perform descriptive statistics, analysis of variance, establish correlations (according to Pearson coefficient) and carry out principal component analysis (PCA). The experimental wines of two strains selected after results analysis were subjected to a paired comparison test by a wine expert who evaluated the following wine characters intensities: aromatic, undesirable flavours, tannins and body.
Method Data collection procedure and sample This study was conducted in an Italian military organization that was initiating different innovation programs aimed at introducing new organizational HRM practices and employee development activities. The data used in this research were collected over 2 years' time in three waves, each time marking precisely the progress of the projects. Further specification on the nature of the activities cannot be provided due to confidentiality. Participation was voluntary and employees were guaranteed full discretion of their responses. In addition, the methodology for the study was reviewed and approved on ethical matters by a joint board of research and military staff. At Time 1, employees were invited to fill an online anonymous questionnaire including demographic variables, organizational climate (reflexivity and tradition) and image outcome expectations (image risk and gain).
Analytical strategy All research analyses were performed using R software with Lavaan package  (Rosseel, 2012). Anderson and Gerbing's (1988)  two-step approach was followed by testing, first, a measurement model (CFA) to establish the discriminant validity among study constructs, then a structural model to estimate the fit of the hypothesized model to the data. Hypotheses concerning direct and mediated effects were verified following  Iacobucci and colleagues' procedure (2007)  for mediation using structural equation modelling  (Judd and  Image expectations and innovative behavior  Kenny, 1981). First, a model comprising both direct and indirect effects was tested to measure each effect while controlling for the others. Then, the significance of indirect effects was calculated with the bootstrapping procedure recommended by  Preacher and Hayes (2008).
e. scanning the environment in search for ideas) and idea promotion (i. e. gaining support from others for the realization of new ideas)  (Carmeli and Spreitzer, 2009). Third, Third, control variables (age, tenure, and educational level) failed to significantly impact the results, future research should add effective control variables based on the theoretical ground to improve the validity of the research  (Bernerth and Aguinis, 2016). Lastly, data were collected from a single organization, which limits the cross-validation (i. e. generalizability) of our findings. Moreover, since the sample was drawn from military personnel the majority of the respondents were male, so results might not translate to the overall population. Therefore, to improve the generalizability of the results, future research should test the posited model in more diverse samples from different industry sectors and with a more balanced gender composition.
Paternity study Discovering SNP markers through data mining SNP data mining was performed using sequence data of 14 C. canephora genotypes which were deposited in the NCBI Sequence Read Archive (SRA) database. These SRA reads were downloaded from the database and mapped on the C. canephora reference genome  (Denoeud et al. 2014 ) using BWA program. The Genome Analysis Toolkit (GATK) package v 3. 520 was used for SNP calling using HaplotypeCaller with default parameter. Then the hard lters (parameters: QD < 2. 0 || FS > 60. 0 || MQ < 40. 0 || MQRankSum < -12. 5 || ReadPosRankSum < -8. 0) were applied to the lter low-quality alleles. To select high-quality SNPs for experimental validation, any SNPs that had other possible adjacent SNP sites 80 bp upstream or 80 bp downstream were eliminated.
Data analysis Paternity analysis CERVUS 3. 0. 6 software  (Marshall et al. 1998 , Kalinowski et al. 2007 ) was used to assign relatedness with SNPs genotype data. The method used is based on the maximum likelihood approach  (Thompson 1976 and Meagher 1986). For each descendant, a measure of the probability that each potential father is the actual father is calculated as a logarithmic score LOD (logarithm of odds). In CERVUS, the male parents of each offspring are determined using the "sex unknown" option. The list of candidate parents is composed of all genotypes in the trial. Paired parent analysis was applied to assign the two parents of each individual. The female parent serves as a control for the applied test. In CERVUS, the proportion of input errors is used as the error rate in the likelihood calculation during the simulation that precedes the parent pair assignment operation.
An error rate of 0. 2% was used for this analysis. The simulation was done with 10,000 cycles of replicates with discount assuming that 80% of the potential parents were listed. The critical likelihood value (LOD score) was considered with a percentage of 95% in the strict sense and 80% in the broad sense during the simulation, respectively. The contribution of a male progenitor or group of male progenitors to the pollination of a tree or group of trees in the plot is determined by the percentage of the number of paternal progenies observed for the tree or group of trees. The Mann-Whitney U test was used to compare the contribution values of Guinean and Congolese progeny. This test was performed using the XLSAT 2014 software.
The resulting ampli ed DNA was then diluted 1:5 in TE buffer in order to reduce the concentration of any remaining PCR by-products. Samples were then genotyped using the nano uidic 96. 96 Dynamic ArrayTM IFC(Integrated Fluidic  Circuit; Fluidigm Corp. ). The 96. 96 Dynamic Array IFC for SNP genotyping was described byWang et al. (2009). End-point uorescent images of the 96. 96IFC were acquired on an EP1TM imager(Fluidigm  Corp. ). The data was recorded with Fluidigm Genotyping Analysis Software(Fluidigm, San Francisco, CA). isolation and SNP genotyping SNP genotyping DNA was isolated from 3 discs of dry leave collected from each tree in the eld and each progeny seeding. SNP genotyping was performed at USDA-ARS, Sustainable Perennial Crops Lab, Beltsville, MD, USA, using the Fluidigm 96. 96 Dynamic ArrayTM (Fluidigm, San Francisco, CA).
Literature Review A holistic literature review is conducted to identify major requirements for the economic assessment of PSS, with a particular focus on cost. The review was performed based on the databases of Google Scholar and Science Direct, primarily covering journal articles Research Clarification aims at identifying and refining "a research problem that is both academically and practically worthwhile and realistic"  [16]. In this study, the research objective is to support PSS industrialization by assessing the economic values generated from a PSS delivery. As previously explained, this is an academically worthwhile problem because the cost estimation of PSS offers remains a complex and under-studied issue, especially from a multi-actor perspective. It is also a realistic problem, since moving to PSS-based business models requires companies to be aware of the subsequent benefits and risks.
Literature Review A holistic literature review is conducted to identify major requirements for the economic assessment of PSS, with a particular focus on cost. The review was performed based on the databases of Google Scholar and Science Direct, primarily covering journal articles in the domains of industrial engineering and business management. In light of a relevant literature review about PSS assessment performed by  [18] , the searching timeframe was determined to be 2010-2020. A total of 25 articles were identified as relevant and analyzed in detail. Two complementary literature streams were considered: PSS multi-actor and life cycle dimensions, and PSS economic assessment with a focus on cost. For the first stream, a selection of keywords was used, including "PSS" OR "productservice system" AND "multi-actor" OR "multi-stakeholder" AND "value network" AND "assessment".
Since the proposed framework incorporates a multi-actor dimension, actors are a key element in the conceptual model. Through iterations among the above steps, a set of alternative scenarios of a PSS solution are built. A scenario specifies the role of each actor in delivering a PSS offer under the conditions defined by the contract, in particular, concerning services and products included in the offer as well as the contract duration. The roles are depicted through activities (related to product or service provision). Afterwards, data on resources and/or activities' unit costs are collected and stored in a database (structured according to the concepts of Figure  3 ) to prepare for the subsequent steps.
Their preference, regardless of the scenario, is to sell the battery directly to the solution provider. Typical datasets required for the assessment include the bill of materials, activities related to maintenance and cleaning services, the unit cost of different activities, the service frequency and the margin rate of product/service. Data related to cost and revenue were double-checked for accuracy and consistency throughout the project. Due to confidentiality, the technical data about the equipment and unit costs are not fully disclosed. The cost of the robot, that is, the product embedded in the PSS amounts to EUR 100,000. Several services are identified by the project consortium with the support of the authors. Table  2  shows the list of the selected services together with their unit cost estimates.
Simulation Setting and Economic Results The three scenarios shown in Table  1  were simulated upon modelling all required objects and entering cost data using the software platform. The assumption is that the demand will grow incrementally throughout the first year after launching the PSS. Then, it is expected to increase more rapidly in the following years, until the growth stagnates in the last year. Figure  9  shows the demand profile for the simulation, which applies equally to all three scenarios. installation fee is set to be EUR 4,000, which applies equally to both PSS. All services are executed at the same frequency regardless of th stochastic variables are introduced in the cost and revenue calculati tion run is required for each input dataset. It is worth noting that results lies in the comparative analysis.
Solution provider Battery provider Based on discussion with actors from the Solution provider and the Battery provider, the margin rates for manufacturing and service are set to be 0. 2 and 0. 3, respectively. The robot selling price in Product-PSS amounts approximately to EUR 117,000. The annual rent is about EUR 57,000 in the Use-PSS and EUR 179,000 in the Result-PSS. The fixed installation fee is set to be EUR 4000, which applies equally to both Use-PSS and Result-PSS. All services are executed at the same frequency regardless of the scenarios. Since no stochastic variables are introduced in the cost and revenue calculation, only one simulation run is required for each input dataset. It is worth noting that the relevance of the results lies in the comparative analysis. The monthly rent, selling price, and unit costs are determined based on the assumption that the fixed costs are the same across all three scenarios (Figure  10 ).
Since no stochastic variables are introduced in the cost and revenue calculation, only one simulation run is required for each input dataset. It is worth noting that the relevance of the results lies in the comparative analysis. The monthly rent, selling price, and unit costs are determined based on the assumption that the fixed costs are the same across all three scenarios (Figure  10 ). The results reported on in Figure  10  show the cumulative profits per actor and per PSS scenario in consideration of the demand profile over ten periods (Figure  9 ). It can be seen from Figure  10  that the net profit for the battery provider is the same over the three scenarios. The transformation towards PSS provides an opportunity for the Battery provider to gain steady revenue with mitigated risk. On the other hand, the profit for the Solution provider increases by almost 60% in Use-PSS compared to Product-PSS.
e. , just before the third lockdown in France) is analyzed both manually by the authors and using text mining and sentiment analysis tools to further discuss and illustrate their answers. In the present case, without any specific training dataset, the Google Natural Language API appeared to be the most accurate tool for sentiment analysis compared to other tools (e. g. , Textanalyzer, Free Sentiment Analyzer) when looking at the results (sentiment score) given by the API and our personal readings and interpretations of the answers.
Literature survey: contribution of circular economy for industrial resiliency in the COVID-19 context Additionally, the answers and insights provided by engineering students on these questions are positioned within the state-of-the-art post-COVID literature (i. e. , from the past 18 months) on this topic (sub-section 3. 3). To identify and select relevant articles, the Google Scholar database has been used with search queries combining the following keywords: ("COVID-19" OR "Coronavirus" OR "pandemic") AND ("circular economy" OR "closed loop") AND ("resilient" OR "resilience" OR "industrial" OR "value chain" OR "supply chain"). Note that the reading materials provided to the students are based on state-of-the-art publications (e. g. , released in the press a couple of days before the exam).
Specifically, several students mentioned the importance of the 3R (repair, reuse, recycle) principles to extend the lifespan of products and thus increase resource availability and supply chain resilience. Second, they had to give their opinions on whether or not the requests of several companies or industrial sectors to loosen environmental regulations are well justified by the economic and social issues raised by the COVID-19 crisis. A large majority of students agreed on rejecting these demands and pressures to suspend regulatory constraints regarding environment protection. The Google Natural Language API, AutoML Natural Language, has been used to automatically perform sentiment analysis on students' answers. AutoML Natural Language provides a breakdown of the sentiment per sentence, an overall score from 1.
Procedure We collected the content using a word association task, followed by two steps referring to hierarchical evocation and semantic contextualization [see  65, 60, 79, 80, 81]. Information such as social origins, consumption habits, and sociodemographic data were also requested. Participants wrote (04) words or phrases that came to mind  [82]  when we asked them about the four different inducing words. The inducing words in Brazil were: "vinho espumante" (sparkling wine), "espumante moscatel" (Moscatel sparkling wine), "sidra" (cider), and Champagne; in France: "vin mousseux," "vin pétillant," "vin crémant" -terms used to designate sparkling wine in French, and Champagne. These words were taken in referenced blogs and official content from wine associations, explaining the difference between those products, as well as how the product was misunderstood by the consumer [see 20].
Measurements and data collection The empirical data used for this study is part of a larger survey on eating practices. The survey was constructed based on a review of relevant scientific and policy literature and a qualitative pre-study (see  Biermann and Rau, 2020)  for details on the survey design). Thirteen closed-ended questions of the quantitative survey were used for this analysis. The main questions were (1) the components defining a sustainable diet, (2) the perceived healthiness of six diets/production methods, (3) the perceived environmental friendliness of these diets/ production methods, and (4) demographic data. For multiple-choice questions, the number of possible answers was limited to 3 out of 9. For opinion questions, responses were recorded using a 5-point Likert scale. The answer options of close-ended questions were rotated randomly, to prevent primacy-recency effects in the responses.
Before the first question on the definition of a sustainable diet, a definition of the term (in accordance with the FAO guidelines) was provided to the respondents: A sustainable diet is a diet that should have the least possible impact on the environment, contribute to food security and enable a healthy life. The web-based survey was created and distributed using Unipark, an online survey software hosted in Germany. Data was collected between January and April 2019. The study protocol followed the International Sociological Association's code of ethics and participants gave informed consent before taking part in the survey study. The survey was distributed online through diverse channels and carried out in German. It was thereby accessible to German-speakers, with 94% of respondents also citizens of and residing in Germany.
Data analysis Data analysis focused on the meanings associated with sustainable nutrition. Gender differences in the beliefs around sustainable diets were also analyzed. Statistical analyses were carried out using R. For the first multiple choice question on components of a sustainable diet, a market basket analysis was conducted using the APRIORI algorithm in R. For the opinion questions, the 1-5 rating scale was reversed for better interpretability. Thus 5 represents the most positive answer and 1 the most negative answer. For the multiple-choice questions, a Cochran's Q test was performed as well as pairwise McNemar's tests with Bonferroni adjustments to determine the statistically different pairs. Additionally, Fisher's tests were used to determine if gender differences were significant.
Citation Analysis to Identify the Intellectual Core Since citation counts are considered important measures of intellectual influence, their analysis can lay out underlying patterns in the theoretical structure of a stream of literature  (Di Stefano et al. 2010). We conduct citation analysis by mapping the citation counts of articles in our sample that were listed on the ISI Web of Science database (a final set of 77 articles). Among these studies, the average number of citations was 52. 05. A subtotal of 20 articles had more than that average number of citations, constituting 78. 99% of the total (Table  1 ).
Historical Citation Analysis of Field Development We subsequently conducted historical citation analysis to understand the evolution of the research stream. We use a historiographic approach and develop a chronological network map of the most relevant direct citations using data of direct in-group citations (Fig. 4 ). The historical citation analysis in Fig. 4  identifies three important phases that characterize the different stages of development of the literature. Stage I (2002 Stage I ( -2006 ) entails a clear business-centric focus on market access, and consists in several articles addressing specific elements of BoP business models. London and Hart (2004) , for example, pioneered the view that MNEs need to adopt different strategies for entering low-income economies. During the second stage  (2006) (2007) (2008) , several key articles built on  London and Hart (2004)  by emphasizing the importance of new capabilities for BoP businesses-such as technological capabilities  (Chesbrough et al.
Historical climate and phenology data for Napa and Bordeaux Historical climate data were curated from the United States National Oceanic and Atmospheric Administration database for Napa, CA USA and the Meteo France database for Bordeaux, France. The growing degree days were calculated using 10 °C as the base temperature in each year with no upper limit. The growing season was defined as the period from the 1st of April to through 30th of October. Heat spike days were defined as those days with a maximum temperature greater than 34 °C. Phenology intervals between veraison and harvest were calculated for the years available using data from the Napa Valley Vintners (https://napavintners. com) Harvest Reports and  Chevet et al. (2011)  for Bordeaux, France.
Sugar concentrations at harvest and wine quality ratings The harvest sugar concentrations were acquired from the California Grape Crush Report database (www. cdfa. com) for Napa, CA, USA, and from an average of Pauillac 1 & 2 from  Soyer and Chevet (2007)  for Bordeaux, France. The Napa, CA, USA, wine quality ratings were acquired from compiling Wine Spectator (www. winespectator. com) ratings for "Cabernet-Sauvignon" and "Merlot" wines from California from over 1900 wines and taking the mean rating per year. For Bordeaux, France wine quality ratings were acquired by taking the mean of three different vintage quality sources: Tastet & Lawton (presented in  Soyer and Chevet, 2007) , Le Guide Hachette des Vins 2020 ("Bordeaux rouge" category), and Cellar Insider (www. thewinecellarinsider. com).