### Table 4: Association of risk variables with total mortality in a multivariate analysis

### Table 2. Continuous intensive care unit (ICU) physiologic data acquisition systems and databases

2003

"... In PAGE 5: ...uration (~2 MB). Tsui et al. (8) initially reported the system for acquiring, mod- eling, and predicting intracranial pres- sure in the ICU from which our current system evolved. Other ICU data acquisi- tion systems and databases are listed in Table2 . To our knowledge, the Complex Systems Laboratory is the first system with the capability of remote data acqui- sition directly from multiple patient monitors simultaneously and the first continuous data acquisition system dedi- cated to critically ill children.... ..."

Cited by 5

### Table 2. Unadjusted and Adjusted Association of Heart Rate Variability Variables With All-Cause Mortality, Cardiac Mortality, Sudden Cardiac Mortality, Sudden Cardiac Autopsy-Verified Mortality, Sudden Cardiac Mortality for Both Genders, Nonsudden Cardiac Mortality and Nonsudden Cardiac Mortality With Cerebrovascular Mortality Unadjusted Association Association Adjusted for All Risk Variables Relative

"... In PAGE 4: ...mong men (RR 5.9, 95% CI, 2.8 to 12.5, p , 0.001). Results were similar among the subjects with autopsy- documented sudden cardiac death ( Table2 ). Short-term exponent also predicted nonsudden cardiac mortality but not cerebrovascular mortality (Table 2).... In PAGE 5: ... Multivariate predictors of mortality. Table2 shows the multivariate relative risks for HR variability measures ad- justed for other risk variables, such as age, gender, heart failure, angina pectoris, functional class, previous myocar- dial infarction, cardiac medication and ventricular prema- ture beats. Although the short-term exponent had weak associations to various clinical parameters (Table 3), it remained as a strong independent predictor of sudden cardiac death after adjustment for other variables in multi- variate analysis.... ..."

### Table 7: Regional Inequality in Illiteracy Rate and Infant Mortality Rate (IMR)

2003

"... In PAGE 10: ... Moreover, it appears that the gender gap has increased between 1990 and 1995. Table7 further displays the spread in the illiteracy rate across rural and urban areas, with the Gini and Generalized Entropy (GE) as inequality measures. The GE 2 The data in 1964, 1981 and 1990 are from the census, while the information in 1995 is from a one percent population survey.... In PAGE 11: ... Inequality is calculated using the population weighted values of illiteracy for spatial units at the highest level of disaggregation for which data is available. In the top panel of Table7 , the first two columns show that the Gini and the GE at the national level declined from 1964 to 1981 and then increased from 1981 to 1995. The same pattern holds true for inequalities across rural areas, as shown in the third column for the GE measure.... In PAGE 11: ... As is well known, the GE family of inequality measures can be decomposed into the sum of a within and a between group component, for any given partitioning of the population into mutually exclusive and exhaustive groups. The fifth and sixth columns of Table7 present the evolution of the within and the between group components of inequality. Both components rose in the post-reform period.... In PAGE 11: ...nequality. Both components rose in the post-reform period. Using the within-inequality and between-inequality, we can calculate the polarization index following the method outlined by Zhang and Kanbur (2001).4 As shown in the last column in Table7 , rural and urban areas became increasingly polarized from 1981 to 1995. The above inequality analysis, based on more disaggregated data, offers a snapshot for each of four years.... In PAGE 12: ...and district level as shown in Table7 . The rural regional income inequality, measured by the Gini coefficient, increased by from 13.... In PAGE 12: ... Using the data set, we can further examine the regional distribution of IMR. As shown in the lower panel of Table7 , overall regional inequality increased from 1981 to ... ..."

### Table 2. Potential Risk Factors of 1-Year Mortality Derived From Clinical and Statistical Criteria

1991

"... In PAGE 3: ... Descriptive statistics for age and length of stay for index hospital discharges are presented in Table 1. A list of the 37 diagnostic groups entered into multi- variable logistic regression is presented in Table2 along with the ICD-9 codes used to generate them. The fre- quency of each group was recorded during index hospi- tal admission, along with the number of inpatients who had the diagnosis and died within 1 year of the date of hospital discharge.... In PAGE 5: ... MODEL VALIDATION Bleeker et al28 suggested that both internal and external validations be used to ascertain performance of a new re- gression model. In our study, rather than using the split- half method, we used the entire data set to develop the model and performed bootstrapping as the measure of Table2 . Potential Risk Factors of 1-Year Mortality Derived From Clinical and Statistical Criteria (cont) Diagnostic Groups Descriptions (ICD-912 codes) No.... ..."

### Table 3 Panel Trend Regression:

"... In PAGE 13: ...b] is that these trends are common (i.e.: identical) across the cross-section. Table3 presents the results from a panel estimation of a linear deterministic trend. These results strongly reject the equality restrictions of assumption [b] imposed on the coefficients across the cross-section.... ..."

### Table 1: Physiological Features

"... In PAGE 2: ...eart rate variability (electrodes glued over the left side of the thorax), a sensor to measure skin conductance (a.k.a. galvanic skin response (GSR), or electrodermal response) attached with Velcro strips to two toes of the left foot, and a flexible chest belt for measuring chest cavity expansion with a Hall effect sensor. From the raw signals, we derive 12 features through Matlab post-processing software ( Table1 ). We also recorded a subjective workload rating (feature 13) indicated by the driver on a scale from 1 (very low) to 8 (very high), in real time.... ..."

### Table 2. Potential Risk Factors of 1-Year Mortality Derived From Clinical and Statistical Criteria (cont)

1991

"... In PAGE 3: ... Descriptive statistics for age and length of stay for index hospital discharges are presented in Table 1. A list of the 37 diagnostic groups entered into multi- variable logistic regression is presented in Table2 along with the ICD-9 codes used to generate them. The fre- quency of each group was recorded during index hospi- tal admission, along with the number of inpatients who had the diagnosis and died within 1 year of the date of hospital discharge.... In PAGE 4: ...Table2 . Potential Risk Factors of 1-Year Mortality Derived From Clinical and Statistical Criteria Diagnostic Groups Descriptions (ICD-912 codes) No.... ..."

### Table 4. Comparison between increment and mortality groups Mortality group Increment

1990

"... In PAGE 8: ... Table 3. Mortality pattern and size at maturity Number of species classified by size at maturity (Stocker 1983) Mortality group Small ( lt;40 cm dbh) Intermediate (40-100 cm dbh) Large ( gt;100 cm dbh) Total number of species 1 5 24 4 33 5 19 15 0 34 10 2 8 7 17 Others 11 15 0 26 Total species 37 62 11 110* * based on specific name, not common name, for species classified by Stocker (Appendix) Table4 illustrates the correspondence between the increment groups (Vanclay 1991) and the mortality groups. The 100 species employed in the preceeding analysis belong to 41 different increment groups, and were grouped into ten mortality groups.... In PAGE 8: ... The 100 species employed in the preceeding analysis belong to 41 different increment groups, and were grouped into ten mortality groups. If increment group provided a perfect indication of mortality pattern, Table4 would have only 41 entries. Conversely, the worst case would exhibit 100 entries, and random allocation would result in 83 entries (Table 5).... In PAGE 8: ... In fact, it contains 84 entries which suggests that increment pattern provides no indication of the appropriate mortality group. The standard v2 test cannot be applied to sparse data such as Table4 , but a comparison of the the observed and expected frequency of numbers of species per cell indicates that the difference is not significant and that the diameter increment group provides no guide to the relevant mortality group ... In PAGE 10: ... So the possibility of some correspondence will be further investigated. The mortality group indicated by the diameter increment pattern is given in Table4 , and has been calculated as the mortality group most frequently represented within each increment group. Since all species from increment groups 1, 2, 18 and 32 were found to quot;belong quot; to mortality group 1, it is reasonable to argue that any other species in these increment groups may also be best assigned to mortality group 1.... ..."

### Table 1. Summary of Physiological Signal Measurements

"... In PAGE 4: ...Table1 . Over the period, data points of the signal amplitude against the measurement tie are recorded.... In PAGE 4: ... This works as a way of counting how jitery the signal is from the player: the beter the points fit a linear regresion, the more stable the signal is, indicating that the player is more focused. For the tonic measures, the same sample rates are used, but with a longer measurement period (se Table1 ). The sample amplitudes are fed into a Kalan filter, to smooth the points [Welch amp; Bishop, 2001].... ..."