dataesr/scientific-paragraphs-categorization huggingface dataset:
Analysis and synthesis In the third step, the research assistants used data extraction sheets independently from one another in order to analyse all articles identified. These data extraction sheets were implemented in Microsoft Access 2016 to allow a high degree of transparency and to minimize input data errors. The research assistants continually compared their results; in case of disagreement, the opinion of an additional reviewer was decisive. Each data extraction sheet consisted of the following elements: bibliographic data, research aim, method, type of collaboration, country, university, results, limitations and factors that influence the success of an IUC. The aim of the present study was to determine factors influencing the success of an IUC. In that regard, we faced a trade-off between imposing a homogeneous definition of success, which would improve comparability but potentially violate the 'fit' between the aim of the original study and its method (a key quality criterion of research identified, e.
Acknowledgements Open access funding provided by  University of Graz. Open Access This article is distributed under the terms of the Creative Commons Attribution 4. 0 International License (http://creat iveco mmons. org/licenses/by/4. 0/),which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
This data is then used to compute for each option the last acceptable date for selection regarding the delivery date and all other options able to be integrated in the same architecture. For instance, the process position feature indicates the first time when the related module of one option has to be considered in the production process. This is combined with the supplying capacities that indicate the possible delivery time after ordering a module from potential suppliers. The compatibility matrix is obtained by analyzing the interfacing capabilities between modules in different product architectures. The formal description of computation algorithms for the evaluation of module lead times and compatibility matrix building are out of scope of this work. However, the following short procedure shows how the configurator manages the configuration task based on a connection to the modular architecture in the back office data base.
Acknowledgments ;This research was funded in the framework of the European project  Interreg-SUDOE VINOVERT  funded by the  European Commission. The authors would like to thank  Jean-Louis Escudier ,  Jean-Michel Salmon  and  Alain Samson  from  INRA Pech Rouge  for their help in selecting the wines that were offered to the consumers in this experimental market. We would also like to thank  Isaac Rodriguez  and  Rafael Cela  from the  Instituto de Investigación y Análisis Alimentario (IIAA)  for their participation on the pesticide residue analyses. Anne-Sophie Masure (ISVV-GREThA ) helped with the material organization of the experimental market, for which we are most grateful.
, Segrate, Italy and Bio-Rad Laboratories Singapore Pte. Ltd. ) was used to run the gel at a constant voltage of 150 V until the bromophenol blue tracker dye reached the gel bottom. Wine samples were mixed with the 4x Laemmli buffer (v/v = 3:1) and 18 µL of the mixture was loaded in each well. Five-fold diluted standard proteins from 10 to 250 kDa (Precision Plus Protein TM Unstained Standards, Bio-Rad Laboratories, Inc. , Hercules, US State) were used as MW markers and 1 µL was loaded. The MWs of wine proteins were calculated from the linear regression equation of log MW versus mobility. After migration, gels were silver-stained according to the protocol described by Rabilloud  [52]. For each sample, the gels were carried out in triplicate. After silver nitrate coloration, the SDS-PAGE gels were scanned with a Bio-Rad Doc XR + scanner and analyzed using the Image Lab software.
Statistical Analysis The Pearson's correlation test was performed by using Microsoft Office Excel 2016 software. The correlation coefficients (r values, p < 0. 05) were obtained to reveal the relationships between oenological parameters such as pH, TA, MA, TartA, sugar content, PAC, grape berry MD, K + , Ca ++ , YAN, NH 4 + and α-NH 2 for grape juices and pH, TA, MA, TartA, K + , Ca ++ , α-NH 2 , total protein content (Bradford and SDS-PAGE quantifications) and foaming characteristic of base wines. The coefficients that give a significant positive or negative correlation between two parameters were marked in green (r > 0. 95) and in red (r < -0. 95) in Tables  3  and 4  (Results section). The coefficients showing a high positive or negative correlation are presented in pale green (0. 95 > r > 0.
8) and in pink (-0. 95 < r < -0. 8). Those correlation coefficients of oenological parameters (grape juice versus grape juice, grape juice versus base wine, and base wine versus base wine) were then counted. The PCA was carried out using Scilab software (version 6. 0. 0; Scilab Enterprises, Rungis, France) with the Fact toolbox (INRA Montpellier, France). Except for grape juice K + and Ca ++ (lack of data), all 20 oenological parameters of grape juice and corresponding base wines were analysed by PCA, to visualize to what extent the grape maturity and chemical components of grape juice and base wine could influence the wine foaming characteristic.
Strategy of Maintenance over One-Year Duration and Financial Indicators An efficient maintenance strategy is measured by the reactivity of the team of maintenance, the capacity to control the costs of parts and the additional costs and profitability of the wind farm at the end of a period. In our approach, the final profitability of a wind farm, over a consequent period of operation, is expressed by a customized EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) indicator. This indicator is called "Function Cost": FC (  2 ) FC= Theoretical turnover -Production losses -O&M Costs (2) FC=ThT -PL -O&M Costs The theoretical production (3) of a wind turbine is equivalent to its production with an availability to 100% i. e. no downtime ago over the period. Over a chosen period, we can obtain a theoretical production of the wind turbine starting from the variables of entry which are the data of wind measured on the wind farm and the curve of real power.
Data of wind: they represent the speeds of wind measured by the anemometer-nacelle of the wind turbine. In the event of unavailability, they are recovered on the anemometer of the nearest wind turbine. If no data is provided on the wind turbines, it will take the data of the mast of measurement which is located near to the windfarm. The production loss is defined as a production which should have been realized for the period when the wind turbine was stopped; it's deduced in a theoretical way. The production loss represents a shortfall which is calculated by the same formula as the theoretical turnover but over the duration of production loss (PL). In this case, we use the same formula as in (3). The O&M Cost is related to all maintenance cost. (  4 ). It can be divided in two parts: spares et subcontract costs.
The agents present in the environment are in interaction with objects and other agents. Whether they are physical or abstract, they carry out actions to conform to the objectives which are predefined; the objects can interact with databases and provide answers at the requests of other agents. In our work, an agent has a goal which consists in modifying the object "Breakdown", to modify its state then to share its information with its dealings. The concepts identified in the descriptive ontology give us the objects which compose the field of the O&M. The concepts in the ontology can be at the same time physical or abstracted elements. The concept, when it is a physical entity can be translated in agent if it expresses behaviours, goals. Each agent must be able to express at least one objective to reach.
The platform establishes the scenarios with inputs from several data sources which come from several different applications (figure  6 ). These applications provide information's to PROMEEO database. Maintaining industrial equipment doesn't mean any more to keep it in a good condition; it means to achieve goals to maximize the profit which is to get more than a return on investment. It means also to preserve the wind turbines for a long time and at lower costs to amortize the expenses engaged for construction and the exploitation. O&M Budgets and subcontracts costs must be regularly revalued to guarantee efficiency in the wind farms management. To simulate the real costs of service of a wind farm means to know the cost of the reactivity of the maintenance subcontractor. Some questions remain.
Interview data were collected, along with a large volume of trade press and archival data (business plans, proposals, contracts and emails) -and not restricted to documents shared between suppliers and customers; files from both partner companies, reflecting their own private analyses were used as well. Semi-structured interviews (face-to-face and by phone) were conducted with CEO's, e-commerce, sales and marketing 547 executives, IT and support managers at both case companies. A total of 25 interviews were conducted-13 in the failed case, 12 in the successful case. All questions were targeted according to role in the company. This wide range of data sources contributes to enhancing qualitative research outcomes  (Eisenhardt & Graebner, 2007; Plé, 2013; Yin, 2003). In preparation for analysis, we transcribed and coded data into categories according to observed recurrence; Appendix 1 provides the list of codes and operational descriptions.
Relative supplier-customer characteristics, learning with customers and customerspecific investments were themes found in both Case 1 and Case 2, for instance, whereas dual value appropriation was only found in Case 1. A pattern-matching strategy  (Yin, 2003)  was then used to compare observations with the constructs, relationships and models from related studies. Analysis was assisted by MaxQDA2 software. Finally, the explanation-building technique for observed differences between symmetric and asymmetric alliances was applied  (Miles & Huberman, 1994; Yin, 2003). In the Results section we will delve deeper into these four elements and present our analysis, supported by Table  5. Jointly created value was the project goal. We analyze how complementary knowledge and skills may lead to new knowledge-which, in turn, drives the creation of valuable new solutions for the market (both products and services); an Internet-based infrastructure common to all medical areas at BSM, for instance (Case 1).
VALIDITY AND RELIABILITY In order to guarantee the validity and reliability of our findings, we followed guidelines proposed by various authors  (Gibbert et al. , 2008; Miles & Huberman, 1994; Yin, 2003). Different sources of evidence were proactively searched as a means of triangulating information and developing converging lines of inquiry, with a view to increasing construct validity; the creation of a chain of evidence; and the revision of the case study report by key informants. Moreover, to improve construct reliability, a database was created where reports and documentary evidence were stored. Finally, a research protocol was established to guide data collection, coding and analysis.
LEARNING WITH LARGE CUSTOMERS Learning with large customers, the second element in Table  5 , represents both a condition for alliance success and a way of responding to previously identified asymmetries. Data from our case study shed light on the importance of having interdependent goals to fostering learningand the fundamental role strategic motivation and long-term vision play in the knowledge-building process. Our results also suggest that shared values towards collaboration facilitate social interaction and information exchange. Throughout our analysis of the cases, two distinct learning dimensions were observed: cognitive learning and behavioral learning. We will take a closer look at both dimensions in the next two subsections.
g. Miles & Huberman, 1994; Yin, 2003)  to guarantee validity, reliability and objectivity. In addition, we have used several sources of information and all data has been triangulated. Case protocols were also established and a complete database created. Preliminary findings and reports were discussed with key informants from both firms in each relationship, with a view to ensuring that our conclusions reflected the reality a closely as possible. Secondly, results are based on our analysis of the Spanish tech sector. As we have already commented, caution should be taken when extrapolating our conclusions to other contexts. This is, however, one of the classic limitations of case study research and one of the proposals we have made for future scholarly efforts. In our opinion, replicating this study in other industries and countries would enrich the body of literature on asymmetric alliances, as cultural dimensions may affect the dynamics of strategic alliance management.
The Global Initiative for Cancer Registry Development partnership, led by the International Agency for Research on Cancer (IARC), was established in response to an overwhelming need for high-quality cancer incidence data from lowincome and middle-income countries. The IARC Regional Hub for cancer registration in North Africa, Central and West Asia was founded in 2013 to support capacity building for cancer registration in each of the countries in this region. In this Series paper, we advocate the necessity for tailored approaches to cancer registration given the rapidly changing cancer landscape for this region, and the challenges faced at a national level in developing data systems to help support this process given present disparities in resources and health infrastructure. In addition, we provide an overview of the status of cancer surveillance and activities country-by-country, documenting tailored approaches that are informing local cancer-control policy, and potentially curbing the growing cancer burden across the region.
9  Several registries were established in north Africa;  10  registries from Tunisia (north), Libya (Benghazi), and Egypt (Gharbiah) comprising data from 2003-07 were considered of sufficient quality to be included (in addition to Setif) in CI5 volume X, but not in the subsequent volume XI. 9, 11  Registry developments and collaborative studies involving registries in high-resource settings (eg, the Benghazi registry, Libya, with the Modena registry, Italy) have been facilitated by technical support from IARC and WHO EMRO. 12 Other initiatives have contributed financial support for cancer registration, both regionally and nationally; the Gharbiah registry was initially supported by the Middle East Cancer Consortium via funding from the US National Cancer Institute, and the Lalla Salma Association in Morocco supported the establishment of Grand Casablanca regional registry during the mid-2000s.
9  Registration activities in Kyrgyzstan only recommenced in 2015 as a project of the country's Ministry of Health, in collaboration with WHO EURO. Kazakhstan has the longest population-based incidence series in the region, dating back to 2004, and currently has the most developed cancer surveillance system in central Asia. By contrast, Tajikistan still has no infrastructure for efficient cancer registration, Uzbekistan's cancer registration is hospital-based, and Turkmenistan has only just introduced software to commence cancer registration. Estimates of the cancer burden in central Asia are based on the mortality data available from the WHO mortality database for all five countries. 29 Although the estimated regional incidence in 2012 was comparatively low (168 per 100 000 men, 148 per 100 000 women), the estimated number of new cancer cases was over 80 000, which is projected to increase 60% by 2030 based on demographic changes.
31 he IARC Regional Hub's activities in the region have focused on establishing links with the cancer surveillance community, and provides training and materials in Russian. The first IARC cancer registration course in the Russian language was held in Astana in 2014, from which learning resources in Russian and recommendations for cancer registration in the former Soviet Union, the Astana Recommendations, 32 were developed. A further cancer registration course with WHO EURO was held in Bishkek, Kyrgyzstan, in 2016. At the national level, site visits were completed and recommendations provided to Uzbekistan, Kazakhstan, and Kyrgyzstan, which was the first country to implement the Russian version of the CanReg5 software developed by IARC. 33.
Gulf countries Other than Yemen, each country has a high or very high HDI and is characterised by major immigration, particularly of men of working age. ] [36]  The oldest cancer registry in the Gulf is the Kuwaiti Cancer Registry, with data registered from 1979-2012 compiled in CI5 volumes V to XI. Other registries in the region developed in the 1990s, with national data from Oman published in CI5 volume IX, and data for Bahraini, Qatari, and Saudi (Riyadh) populations included in volumes X and XI. 9, 11 In 2011, a report on 10-year cancer incidence among nationals of the Gulf Cooperation Council states (1998-2007) was published by the Gulf Centre for Cancer Control and Prevention. 37 he inadequate availability or low quality of mortality data, partly due to rapid burial tradition, is shared by most Arabic countries, yet a particular challenge in the region is the registration and follow-up of non-nationals as they frequently return to their home countries for additional work-up and treatment.
The conference was followed by the development of a 10-year strategy (2010-20). 41 At the national level, most Gulf countries have cancer plans that include cancer surveillance. 22 n addition to the action plan with the WHO EMRO, training activities and research collaborations are planned in the Western Asia region. The IARC Regional Hub for cancer registration in North Africa, Central and West Asia also has an active role in supporting the registries in advocating legislation for cancer registration and obtaining access to death certificates and data sources from within the private sector. Many other countries in western Asia have ongoing conflicts, with large numbers of refugees and internally displaced people (table). A registry assessment workshop in Iraq, convened by WHO EMRO in Erbil in 2016, with participation of cancer registry professionals from all regions, provided a good model to support building cancer registry infrastructure in the near future.
Model Consistency Verification The model is checked in order to establish its consistency (see Section 3). Web Services Generation The model is used to generate an implementation of the web services that it represents. This process is generic: it can be implemented using different technologies. For example, we choose to specialize our implementation by adding two hypotheses: atomic components' implementations uses the PHP programming language (The PHP Group 2016) and the generated web services relies on the Laravel web framework  (Otwel 2016 ). This choice is made because PHP and Laravel are well known and used by our first end-users: Startup Palace's developers. To be able to conclude about consistency of web services generated from a consistent model (see Section 3), we need to assume or manually verify that atomic component implementations and their specifications in the model are compliant.
This is currently a limitation that will be removed in a future work by automating the compliance verification. The last step of our tool is the generation step. Many similar tools (see Section 6) take the approach to generate and output a standalone web application that includes everything necessary to operate it. We took another approach by generating code that should never be manually edited; the generated code does not override any existing files in a Laravel's architecture and can be easily hooked to an existing web application through configuration. Currently, developers still have to handle security aspects outside of the scope of our solution, for instance when writing atomic components, because they have control on implementation details.
To register, a user would use cURL to send a POST HTTP request to the endpoint /register/[name]/[email] where [name] is her name and [email] her email address. If this user is already registered, the service would return an error message with a 403 HTTP code. If the given email address is invalid, the service would return an error message with a 422 HTTP code. If both conditions are fulfilled, the registration would be persisted in a relational database along with the registration datetime, and the service would return the input information with a 200 HTTP code. To see registered people, an organizer would use cURL to send a GET HTTP request to the endpoint /attendees/[key] where [key] is a string that needs to be the same as the one hardcoded in the service in order to authenticate the request.
If the given key is invalid, the service would return an error message with a 401 HTTP code. If it is valid, it would fetch registrations from the database, serialize them and return them with a 200 HTTP code. Implementation. In the following examples, we use the concrete syntax introduced in Section 2. 3. We show a possible implementation of this informal specification into a model and explain the different steps to build it. First, we define our data model, that is the entities element of our model. We have only one entity: Registration. Then, we define two services that are linked to two composite component instances that we will define afterwards. These services will be the interfaces between our application and the outer world, as defined in the informal specification. Then, we define the two composite components linked to the services.
Finally, we setup other parts of the Laravel application to benefit from helper features such as external dependencies management, database schema migrations or end-to-end tests. Discussion. This case study is a first step to show that our meta-model is flexible enough to express minimalistic yet realistic web services. Components offer a first-class system to split computations into several smaller parts. Because assemblies of components are checked to ensure their consistency, developers can see them as black boxes which helps a lot when designing, implementing and testing these components. Implementing atomic components in the same language and environment as the generation target allows to have a fine control on what is generated without losing the advantages of building using high-level constructions.
Because generated code integrates easily in a Laravel application, the result can be deployed like any Laravel application thus benefiting from good practices such as those described in  (Wiggins 2012). Apart from generating code, our approach makes it easy to generate diagrams from models that allow easy visualization of how services are implemented or what are components dependencies, for example. This might be a game changer for new developers onboarding. Finally, MDE approach improves maintainability. For example, if we want to make an evolution and allow attendees to modify their registration information and status by adding a new service, it is easy to implement it while reusing existing components and still be confident about consistency, thanks to the verification step. Yet, we performed preliminary experiments with the approach; developers of Startup Palace have been involved in these experiments.