### Table 1 Programming languages and their supported programming paradigms. Progr. language OO Functional Logic Static typing Dynamic typing

"... In PAGE 3: ... 1 The FCA algorithm takes as input a relation, or Boolean table, T between a (potentially large, but finite) set of elements and a set of properties of those elements. An example of such a table is given in Table1 , in which different programming languages and properties are related. A cross in a table cell means that the programming language in the corresponding row has the property of the corresponding column.... ..."

### Table 1 Programming languages and their supported programming paradigms. Progr. language OO Functional Logic Static typing Dynamic typing

"... In PAGE 3: ... 1 The FCA algorithm takes as input a relation, or Boolean table, T between a (potentially large, but finite) set of elements and a set of properties of those elements. An example of such a table is given in Table1 , in which different programming languages and properties are related. A mark in a table cell means that the programming language in the corresponding row has the property of the corresponding column.... ..."

### Table 5: Classi cations of male and female growth curves by the number of growth spurts, using the strict and soft decision rules.

"... In PAGE 13: ... For each male, we plot the estimates of the growth curves having b=1, 2, and 3 growth spurts, and we indicate the one we decided on by a solid curve. Table5 contains all of our classi cation results, with percents calculated based on the number classi ed. Insert Figure 4 and Table 5 about here.... In PAGE 13: ... Table 5 contains all of our classi cation results, with percents calculated based on the number classi ed. Insert Figure 4 and Table5 about here. Comparison of the female and male growth curves suggests that multi-bump curves are more prevalent for boys than for girls.... In PAGE 14: ...Table5 . But we can infer that they would classify 19 males (44.... ..."

### Table 5: Classi cations of male and female growth curves by the number of growth spurts, using the strict and soft decision rules.

"... In PAGE 13: ... For each male, we plot the estimates of the growth curves having b=1, 2, and 3 growth spurts, and we indicate the one we decided on by a solid curve. Table5 contains all of our classi cation results, with percents calculated based on the number classi ed. Insert Figure 4 and Table 5 about here.... In PAGE 13: ... Table 5 contains all of our classi cation results, with percents calculated based on the number classi ed. Insert Figure 4 and Table5 about here. Comparison of the female and male growth curves suggests that multi-bump curves are more prevalent for boys than for girls.... In PAGE 14: ...Table5 . But we can infer that they would classify 19 males (44.... ..."

### Table 1 Results of the inter-annotators agreements (in percent). Syntactic Strict Soft Conceptual

"... In PAGE 33: ... 4.2 Discussion of Results Table1 gives the results of the agreements among annotators (inter-annotator agreements) in terms of Precision, Recall and F-Measure as described in Sec- tion 4.1.... In PAGE 34: ...1. The rst interesting observation is that the values for the maximum evaluation are quite higher than the ones of the average evaluation, which again clearly shows that there was a considerable disagreement between annotators, as shown in Table1 , and thus the task, we are considering, is far from trivial. Obviously, people do interpret the same tables (same content) in various ways.... ..."

### Table 2: Function Types

"... In PAGE 2: ... Both a subset of the theor- ems presented in Chandy and Misra (Chandy amp; Misra 1988) and some additional simple logic rules were chosen as the propositional inference rules used to prove entail- ment. The subset and the simple rules combine to form the function set as shown in Table2 . Both the terminal and function set provide su cient functionality and rep- resentation to prove the entailment of sentences from the provided KB.... ..."

### Table A10. Relationship of Respondent Characteristics to Probability of Using USDA, Probit Model Results, for Sources Used for Regular Reading DEPENDENT

### Table A20. Relationship of Respondent Characteristics to Probability of Using USDA, Probit Model Results, for Sources Used for Market Analysis DEPENDENT

### Table A22. Relationship of Respondent Characteristics to Probability of Using USDA, Probit Model Results, for Sources Used for Market Analysis DEPENDENT

### Table 1. Full-Sample Estimates of Impact of IMF Programs on Market Access

2000

"... In PAGE 21: ... We are also interested in the differential effects of different types of conditionality. In column (1) of Table1 , we show the results of the probit relating the decision to... ..."