dataesr/scientific-paragraphs-categorization huggingface dataset:
For this reason we also calibrate our reduced forms on an ALTER dataset, which is in fact a modified POLES dataset with increased curvatures and explicit absolute floors to the 3 energy intensities we work on. We refer to these floors as "technical asymptotes. " For the sake of argument, our year-2030 policy runs explore a wide range of carbon taxes in the simplified setting of perfect markets, including that of labor, and under the assumption of lump-sum recycling of the carbon tax proceeds to households. Besides the original IMACLIM-S model resorting to reduced forms according to Section Calibration of Reduced Forms of Bottom-up Behaviors, we implement a standard static CES model "CES Kfix" considering an exogenous stock of capital (following, e. g. , Böhringer, 1998) and a "CES Kvar" variant of this model, which (1) sorts out the various components of value-added net of labor costs and values its depreciation part as the composite good; (2) treats depreciation as an index of capital demand, which must be balanced by investment.
demand of households, and indeed the assumed trajectory of battery costs, which we apply to the electric equipment intensity of the electric car production. Despite the care taken to ground IMACLIM-S on hybrid economy/energy accounts following Section Building from IEA Energy Balances and Energy Price Data above, the data imports from TIMES into IMACLIM-S systematically take the form of trends developing from 2007 on, to be applied to IMACLIM-S variables, rather than of absolute values. The main reason for this is that TIMES PanEU is calibrated on 2005 data, and thus does not match the statistics of further years, including the 2007 data on which IMACLIM-S is calibrated. Another reason is that some non-energy variables, as vehicle sales or transport activities, are not described in IMACLIM-S with the same level of detail as they are in TIMES.
e. , to close to 50 economies with widely different economic and energy characteristics. As a consequence we have so far worked on aggregate 2-sector economies, although we might disaggregate the energy good in the 4-5 usual vectors in future work. We have also been careful to systematically resort to international datasets covering a large number of countries (at the World Bank, the IMF, the IEA, etc. ) to feed our modeling framework with parameters as recent statistical trajectories of GDP growth, labor supply, labor productivity, unemployment but also the trade balance and prevailing exchange rates. We calibrate our multiple IMACLIM-S country models at the 2007 base year on hybrid matrixes resulting from the combination of the extensive GTAP database (cf. footnote 38 above) with POLES data, following the synthetic method presented Section Building from BU Model Variables at Base Year above.
In this instance, shortcutting the alternate extensive method of Section Building from IEA Energy Balances and Energy Price Data appears particularly relevant, considering the daunting task of extending this method to several dozen countries, many of which suffering from poor statistical apparatus. As we already stressed this comes at the cost of some approximations, particularly in the split between households' and firms' transport fuel consumptions. Working on short term sovereign debt accumulation requires unusual alignment on available statistics. The Solow growth engine we mobilize, despite the path-dependency imposed by importing energy system constraints from POLES, but also statistics on investment, capital utilization and exchange rates, would "miss" the massive 2008 global economic crisis if it were to run on long-term trends of labor productivity improvements only.
The decision is then easier made to strip down auto-consumptions to genuine marketed inputs, or to identify, by comparing energy with national accounting data, putative commodity trade, which can then be given specific modeling. Hybridizing base year data by importing energy expenses and volumes from the coupled BU model offers less choice because of a lasting simplification of BU models: these rarely distinguish between crude oil and petroleum products, which forbids pinpointing the crude oil expenses of the refining industry-one major auto-consumption of the aggregate energy sector of hybrid accounts built on BU data. However, the refining data are readily available from even aggregated IEA balance sheets and could be exploited in future work. Our coupling methods also call for further developments.
According to the most recent official data, 127 timber CFM projects were submitted to environmental public agencies in the Amazon in 2010, 48 in Pará , 36 in Amazonas, 23 in Acre, 16 in Rondônia, and 4 in Amapa. However, most were not approved and only 53 plans were implemented in 2010  [19]. Public or/and private financial support has been provided for the submission of these CFM projects. In the states of Acre and Amazonas, the drafting and submission of CFM plans have been financially supported by public and NGO funds, including the World Wildlife Fund for Nature (WWF) and the International Union for Conservation of Nature (IUCN). In the state of Pará , many CFM plans in agricultural settlements have been submitted through partnerships between communities and private timber companies  [20].
Economic Assessment Methodology In Pará , the annual production costs supported by the communities, sales negotiations, and profits obtained were monitored in 2007, 2008, and 2009 as part of two research and development projects financed by international funds (European Fund and FFEM). In Acre, we used Cooperfloresta financial reports including annual costs and gross receipts since 2007, when this cooperative was put in charge of the forestry projects. Additional interviews were conducted with association leaders in 2010, 2011, and 2015 to enable a qualitative assessment of ongoing projects. The annual costs reported are only those that accrue to the communities. The costs paid by development projects and public funds are not included because (1) it was not possible to obtain reliable data for all the contributions from different sources at the different periods; and (2) in this paper, the focus is on estimating costs paid by members of the communities and additional income generated by CFM including such external supports-not to question the relevance of such supports.
As most of the data were collected in 2008, 2009, and 2010, we adjusted the 2008 and 2009 values with the observed IPC (Consumer Price Index) to 2010 (5. 9% between 2009 and 2010 and 10% between 2008 and 2010) to correct for inflation. For all the calculations, the following exchange rate was used: US$1/R$1. 72 in 2010.
In 2014, we were only able to obtain comparable data for production costs for the Porto Dias case study. The data show that the distribution of production costs was almost the same as in 2010 and that the total production cost per cubic meter had decreased slightly. One major cost, not included in Table  2 , was the cost of drafting and submitting the management plan. Initial costs were mainly funded by the Promanejo program (CANOR, Virola Jatobá , Porto Dias, Chico Mendes) or by an external funding agency such as ITTO, in Coomflona. It was very difficult to obtain data on the cost of this initial stage. However, we did get a general idea of the cost in our interviews and from the data we collected for two of our case studies. CANOR received US$265,116 from Promanejo in 2004 and about 50% of this amount (US$132,558) was used to pay for the delimitation and forest inventory of the 24 blocks (a prerequisite for preparation of a technical forest management plan) and the drawing up of the forest management plan and of the first operational plan by a forest engineer.
Coomflona and Porto Dias succeeded in negotiating prices of US$122/m 3 and US$145/m 3 (including transport costs), respectively, whereas the sales price negotiated by CANOR was US$74/m 3. Moreover, the Porto Dias and Chico Mendes settlements benefited from a significant additional subsidy from the state government of Acre. Coomflona benefits could have been even higher because they harvested 7843 m 3 but only succeeded in selling 5704 m 3 of round logs in 2008. We were able to collect more recent quantitative data for Porto Dias and Chico Mendes comparable with the data collected concerning 2009 and 2010. These data show that Cooperfloresta succeeded in guaranteeing an annual benefit for the families involved in the management plan that was almost the same as the amount they received in 2009 and 2010.
Data variables, source of data, definition of variables and data collection tool Data collected from TB registers and treatment cards for each patient by included: TB registration number, demographic characteristics (sex, age, place of residence), type of TB (new smear-positive and retreatment TB), HIVstatus (negative, positive, unknown), anti-tuberculosis treatment regimen and treatment outcomes. For those who missed one (or more) of their SA, additional information was collected from the tracing TB register that included: timing of the missed SA, reasons and results of the tracing activity. The tracing TB register was filled in by workers of the "service de relance". The information obtained was shared weekly and validated with nurses and the appropriate decisions were made for patients.
Secondly, in order to interact with other software tools (which is developed in our lab), the software should be able to deploy in ESB (Enterprise Service Bus). These lead that the software tool involved in the methodology should be a web service. SaaSs (Software as a Service) seems to be a good solution. In our lab, Vatcharaphun Rajsiri has created a knowledge-based system for collaborative process specification  [1]. This system deduces a BPMN (Business Process Modeling Notation) based collaborative process model automatically with the help of collaborative objective model and MIT process handbook  [2]. But this system has weaknesses. First, the system collects only the main goal of whole collaborative network. It leads to lack of partners' objectives and sub-network information. Designing a model, which models all above information, is necessary.
Implementation Nowadays, SaaS  [10]  is very widely used. It allows users to use application in a Web Client as rich application. No complex client site installation is required. According to  [11] , compared with the traditional way which software is purchased for and installed on personal computers, SaaS has advantages: e. g. , investment reduction, performance improvement, time saving, easier collaboration, global accessibility, etc. Considering our own needs, the software tool should be able to deploy on ESB  [12] , which means the software must be a web service. Because the software deals with a collaborative situation, all the partners may use the software in the same time or individually. This leads to a conclusion. SaaS is a quite good solution for our tool: Mediator Modeling 2ool.
We carefully construct a unique and detailed database of Belgian listed firms and the composition of their shareholdings for a period of sixteen years, from 1991 to 2006. The first quartile of share ownership of the leading shareholder is about 40 percent of voting rights, and the average shareholder holds about 54 percent. This very high concentration is rather uncommon and it is a unique Belgian feature. While Belgium is an example of the continental European tradition of ownership concentration, there are specific legal mechanisms, such as the recognition of voting blocks and the prevalence of business groups, that exacerbate this concentration. Voting blocks are formal agreements amongst shareholders that are explicitly allowed by law. In this regard, Belgium offers a unique laboratory to examine the impact of powerful controlling shareholders, grouped in voting coalitions, on firm performance.
Sample selection Our sample consists of all Belgian listed firms except those in the financial sector, such as banks, insurance companies, common investment funds, companies active in or related to financial intermediation, as well as real estate firms. We also exclude some companies in coal mining and steel production that were involved in a long liquidation process but were still listed and had incomplete data. We limit ourselves to firms with available balance sheet data and a declaration of ownership to the Banking Commission, therefore, out of an initial total sample of 243 firms we end up with an unbalanced panel of 194 firms with 1676 firm year observations between 1991 and 2006.
Ownership data In Belgium, the disclosure law of 1989 makes notifications to the Banking Commission of share ownership in listed firms mandatory for all shareholdings of at least 5 percent of voting rights. This threshold could be as low as 3 percent if the firm writes this into its statutes, see Appendix A for more details. Hence, ownership information is public, and it is featured in a number of databases: (1) BDPart at the Documentation and Statistics Department of the Brussels Stock Exchange records the current ownership of listed firms, but unfortunately it does not keep historical data; (2) the "Centrale des Bilans" database at the National Bank of Belgium (NBB) provides ownership data, but it only keeps track of Belgian shareholders; (3) "Belfirst" from Bureau Van Dijk starts recording ownership positions of listed firms in 1997, but this data is not of sufficient quality and it requires what amounts to an almost manual cleanup.
Other data Following the literature on ownership and performance (see e. g. Morck, Shleifer, and Vishny 1988 , McConnell and Servaes 1990 , Short and Keasey 1999 , Davies, Hillier, and McColgan 2005) , we control for firm size, proxied by log of total assets, leverage, which we measure as short and long term debt, investment, proxied by capital expenditures, R&D as a proxy for investment opportunities, and investment in financial fixed assets, which is an important part of Belgian firms' investments. All these variables are weighted by total assets. Our dependent variable is firm performance, which we measure as market-to-book ratio (as a proxy for Tobin's q). All the accounting data we need to construct these variables come from two sources. For the 1991-1996 period we rely on the NBB's "Centrale des Bilans" database 4 and for the 1997-2006 period, we use the "Belfirst" database of Bureau Van Dijk 5.
In order to merge data from all these different source, we identify firms by their VAT code. 6  Finally, in order to compute market-to-book value, we collect year-end market capitalization of listed firms from the Brussels Stock Exchange. Table  1  defines our variables, while Table  2  shows descriptive statistics for the different variables we use in our analysis. On average, market-to-book value is about 1. 15 for the whole sample. Family firms have the highest average market-to-book value with 1. 41 against 1. 02 for non-family firms, with a statistically significant difference, while it is 1. 12 and 1. 16 for firms related to coordination centers and those without such a link, but the difference is not significant. There is no statistically significant difference between family, and nonfamily firms in terms of size, debts, investment in financial fixed assets, capital expenditures, or R&D.
Concluding Remarks In this paper we analyze levels of ownership concentration seldom considered before in the literature and we show how large controlling shareholders affect firm value. We use a unique detailed database on share ownership of Belgian listed firms which exhibit levels of ownership concentration ignored in the literature. The very high levels of ownership concentration via the practices of voting blocks and/or business groups make Belgian listed firms a real laboratory to examine issues of ownership structure and performance. Our data set also makes it possible to investigate differences between family and non-family firms, or firms with or without a link to a coordination center. We use kernel-based local linear semiparametric pooled, random and fixed effects models to study the effect of very large controlling shareholders on firm performance.
Expressiveness of GDT4MAS Through several articles, the expressiveness of GDT4MAS seems adapted to model most problems tackled by multi-agent systems. For instance, it has been shown in  (Mermet and Simon, 2011)  that agents mixing cognitive and reactive behaviours can be easily specified thanks to the holonic extension of GDT4MAS. The exception management is also a key issue in MAS  (Klein et al. , 2003) , But it is rarely handled by MAS models and languages  (Platon et al. , 2008)  like AgentSpeak for instance. However, once again, thanks to the holonic extension of GDT4MAS, this can be clearly specified with GDT4MAS, as explained in  (Mermet and Simon, 2011). Finally, many communication styles can ben specified with GDT4MAS. To our knowledge, this is the only formal model dedicated to MAS that manage this aspect of MAS.
Questionnaires and data collection The questionnaire for the face-to-face interview was adapted from UNAIDS documents used in behavioral surveillance studies and administered by trained and/or experienced interviewers who had not previously been involved in this specific outreach intervention. The standardized questionnaire was drawn up in French and translated into Darija, the colloquial Arabic dialect, to ensure that the studied population would understand its contents more comprehensively. It was pre-tested and validated on a sample of 20 truck drivers and used to collect data on the outcome (exposure to the intervention), sociodemographic data, and data on participant HIV at-risk behaviors during the 12 months prior to the survey: -Sociodemographic data included age, gender, marital situation, education level and health insurance.
-Professional data included type of truck driver (national, international, assistant driver, mechanic), work location, length of service etc. -Having being tested for HIV in the 12 months prior to the survey. -Drug and alcohol use. -Sexual behaviors including sexual activity, sexual encounters with occasional partners and professional sex workers, non-systematic condom use with occasional partners or sex workers, and sexual encounters with male partners. -Knowledge of HIV and STI and the symptoms of HIV and STI. -Exposure (or not) to the specific prevention intervention. This information included the number of times the participant had contacted intervention stakeholders, the information obtained, whether condoms were obtained or not, etc. Inconsistent condom use was defined as the non-systematic use of condoms with sexual partners of unknown serostatus (occasional partners or sex workers).
Acknowledgments We would like to extend our sincere thanks to the  Global Fund  to fight Aids, Tuberculosis and Malaria which co-funded the project from the very beginning and continues to support it today. Our thanks also to the TOTAL Foundation which co-funded the project until 2011. We would especially like to thank  Catherine Ferrant , for her confidence and support. Our deep gratitude also to  Professor Françoise Barré-Sinoussi , 2008 Nobel Prize in Medicine, for her guidance and supervision. We also thank  Jude Sweeney  for his reviewing and editing of the English version of this manuscript. Finally, we wish to thank all the health care workers, peer-educators, volunteers and everyone else who contributed to the success of this project.
Data Collection We conducted a cross-industry survey of major European client firms from financial services, manufacturing, logistics, retail, utilities, telecom and other sectors. The data collection took place in late 2010. Senior managers at the client firms with extensive experience in outsourcing engagements for their firms were asked to respond to a survey regarding the quality of the relationships between their firm (unit of analysis) and their IT and business process outsourcing suppliers. This study applied a "key informant" methodology for data collection  (Kumar et al. 1993; Segars and Grover 1998; Goo et al. 2008 ). To ensure that respondents were involved in major decisions regarding outsourcing in their organizations, and in the governance of outsourcing arrangements, a set of screening questions were included as part of the survey.
This checking shows the strict control of consistency management on the choice of appropriate mechanisms according to actors' states. Absence of deadlock. Absence of deadlock or deadlock free system is when the system will never move up to a state where there is no possible progress. • A[] not deadlock: models are deadlock free. Interactive application execution is an unpredictable process caused by uncontrollable actors' actions. The conceived Uppaal models represent an abstract point of view of system's components logic and consistency management layer control. Moreover, thanks to Uppaal simulator and its query language, we can validate, step by step, system execution and verify several important properties concerning integrated misunderstanding handling. All previous properties are verified.
Interaction between Agents and Consistency Mechanisms. Fig. 11  summarizes the main interactions representing the communications between the agents above. To start exercise session, the teacher and all of the learners have to connect first. The first exercise will be calculated with a random difficulty level and a random deadline. This first decision will be validated or not by the teacher and then sent to the corresponding learner if accepted. Once the learner receives distributed exercise, he begins working and sends the rapport after finishing. This rapport will be analyzed by the Observer agent in charge, before redirecting it with observing data to ODL System. The observing data contain exercise finishing state, accuracy rate, learner knowledge level and estimated learner smart level.
The data are recorded and calculated for the average values from 10 simulations launching times in each measure. We compare these data between two cases: "With" and "Without" the consistency management. The results are summarized in Table  1. The total distributed exercises number N e is twice more in "Without" case  compared to the "With" case. The average number of not finished exercises in "Without" series is higher than in "With" series: 747. 4 vs 363. 4 also depicted in Fig. 12  (left). It is obvious that the session duration in "Without" case is almost 2 times longer than in "With" case. Fig. 12  (right) shows the number of learners that have finished their whole series during the situation execution in the "With" and "Without" consistency management cases. The lines shows that the learners work with more exercises and with longer duration T total in the "Without" case.
Many reports on Intellectual Capital have been published and numerous databases have been implemented  [26]. Reports provide static information that should be updated, it is the same for databases; the both are not adapted for smart managing of human resources, especially in the globalization context. Probably the first effort in applying the artificial intelligence techniques to managing skills in given situation was the application developed for French police  [3]. These principles and architecture were reused in larger system for managing security of the Winter Olympic Games  [4]. The techniques such as case-based reasoning can also be useful for matching demand and offer (looking for a job or a skill). Organizations such as OECD  [5]  have been involved in defining a general methodology for measuring intangible investment since 1989.