### Table 9: Estimated Gender Differences in Quits

"... In PAGE 23: ... This applies both to quits to another job and quits out of the workforce. Table9 reports our estimates of gender differences in the hazard of quitting the current job post-promotion, after controlling for a large number of characteristics. The numbers in Table 9 are hazard ratios rather than coefficients.... In PAGE 23: ...en. This applies both to quits to another job and quits out of the workforce. Table 9 reports our estimates of gender differences in the hazard of quitting the current job post-promotion, after controlling for a large number of characteristics. The numbers in Table9 are hazard ratios rather than coefficients. Therefore a value of unity to... In PAGE 24: ...interpreted as a lower female than male quit rate, while a value greater than unity represents a higher female quit rate. As with the raw data, the results in Table9 reveal that there are positive but insignificantly higher quit rates for promoted women (compared to promoted men) to another job or out of the workforce, and higher quits of unpromoted women (compared to unpromoted men) out of the workforce. In contrast to the raw data, women who have never been promoted during the sample period are less likely to quit to another job than men.... ..."

### Table 1- The Function amp; Terminal Node Set for Evolving Discrete-Time Systems

### Table 1. Hardware components and their related performance metrics.

"... In PAGE 2: ... A virtualized system cannot deliver performance beyond what the physical hardware is capable of providing after subtracting the overhead required to manage the virtualization. Table1 contains a list of major components that may be either virtual or physical. The capacity or capability of each physical component may be specified by the hardware manufacturer or measured by some accepted methodology.... In PAGE 2: ... Studies have shown that the measurements taken at the logical component level may differ significantly from corresponding measurements at the Virtualization Manager level [BD]. In this paper, we assume that all measurements for the performance metrics defined in Table1 are collected at the Virtualization Manager level. Suppose a virtualized system has n partitions or guests, n G G G , , , 2 1 L , running on a physical system whose four hardware components are Processor P, Memory M, I/O subsystem D, and Network N.... ..."

### Table 2: Computational Power of Deterministic and Probabilistic Discrete-Time Analog Neural Networks with the Saturated-Linear Activation Function.

"... In PAGE 17: ...4 de- pends on the descriptive complexity of their weights. The respective results are summarized in Table2 as presented by Siegelmann (1994), including the comparison with the probabilistic recurrent networks discussed in sec- tion 2.... In PAGE 24: ..., 2000). This implies that the results on the computational power of deterministic asymmetric networks summarized in Table2 are still valid for Hopfield nets with an external oscillator of certain type. Especially for rational weights, these devices are Turing universal.... In PAGE 26: ...4 (Siegelmann, 1999b). The results are summarized and compared to the corresponding deterministic models in Table2 . Thus, for integer weights, the results co- incide with those for deterministic networks (see section 2.... In PAGE 39: ... Figure 2). Furthermore, Table2 , summarizing the results concerning the computational power of recurrent neural networks, shows that the only difference between deterministic and probabilistic mod- els is in polynomial time computations with rational weights, which are characterized by the corresponding Turing complexity classes P and BPP. This means that from the computational power point of view, stochasticity plays a similar role in neural networks as in conventional Turing computa- tions.... ..."

### Table 1. The Sylvester-type matrix equations considered in the RECSY library. CT and DT denote the continuous-time and discrete-time variants, respectively.

2004

"... In PAGE 4: ... RECSY com- prises a set of Fortran 90 routines, all equipped with Fortran 77 interfaces and LA- PACK/SLICOT wrappers, which solve 42 transpose and sign variants of eight common Sylvester-type matrix equations. Table1 lists the standard variants of these matrix equations. Table 1.... In PAGE 7: ...uture work includes extending the comparisons to other parallel platforms, e.g., the HPC2N IBM SP system which has much less compute power but provides a better \compute/communicate ratio quot;. Our aim is to construct a software package of ScaLAPACK-style algorithms for solving all matrix equations listed in Table1 . The implementations will build on standard node solvers from LAPACK and SLICOT [18, 20, 5], and recursive blocked solvers from RECSY.... ..."

Cited by 4

### Table 2: Parameters of the Discrete-Time Model

2003

### Table 1. Comparison of the number of deleted shell and solid elements in each model at four discrete time steps.

2005

"... In PAGE 13: ... The method chosen for this study was to estimate the area enclosed by the failed elements and those elements that appear to be close to failure, based on the contour plot data. The results of this analysis are documented in Table1 . It can be seen that the Model 2 and 3 panels sustained the greatest amount of damage, and the damaged areas were determined to be 39.... In PAGE 17: ...Table1 . The fact that the internal energy of the RCC for model 2 is considerably higher than the other models indicates that the strain energy in the panel is also much higher, resulting in more global deformation of the panel.... ..."

### Table 1: Rates for Ligand Binding and Conformational Transitions of nAChRa

"... In PAGE 3: ...mong all possible molecular species (except D state). (B) Passages scored as binding events. (C) Passages scored as ionic events. (D) Multiple transitions between conformational states. The simulations were conducted with the previously described program (8) applied to nonequivalent ligand-binding sites using the parameters in Table1 . All calculations were based on a ligand concentration of 2 10-5 M.... In PAGE 4: ... For muscle nAChR, two equivalent sites were used to model single channel measurements (7, 26, 44). Yet, in a number of other studies the data were interpreted on the basis of marked differences (up to 700-fold; see Table1 ) in the affinities of the two ligand-binding sites (45-47). Species differences and dependence on expression systems may be responsible in part for the lack of agreement on the characteristics of the two binding sites (7), but uncertainties remain concerning their intrinsic functional properties.... In PAGE 4: ... The dwell times are presented as the total events, corresponding to simulated experimental measurements (thick lines), along with the underlying contributions of the individual components (thin lines). The simulations are based on the values in Table1 and a ligand concentration of X ) 0.3 M in panels A and B and X ) 1.... In PAGE 5: ... In the latter case, binding of the first ligand to a receptor molecule is predicted to occur almost exclusively at the higher affinity site to generate B1(H). Since an off- rate 16-fold lower than in the case of equivalent sites was deduced ( Table1 ), the peak in the dwell time profile for binding events is predicted to lie at significantly longer times: 2 10-3 s for nonequivalent sites (Figure 3D) compared to 1.2 10-4 s for equivalent sites (Figure 3B).... ..."

### Table 2. Time delay of various components in terms of number of FO4 delays. Part Delay

2003

"... In PAGE 6: ... The model is validated through transistor simula- tion of different circuits. The different parts of the model are summarized in Table2 . Using units of FO4 delays makes the model independent of the technology scaling to a large degree since this elementary gate scales almost linearly with the technology [11].... ..."

Cited by 2

### Table 2. Time delay of various components in terms of number of FO4 delays. Part Delay

2003

"... In PAGE 6: ... The model is validated through transistor simula- tion of different circuits. The different parts of the model are summarized in Table2 . Using units of FO4 delays makes the model independent of the technology scaling to a large degree since this elementary gate scales almost linearly with the technology [11].... ..."

Cited by 2