ISEN 665 Human Machine Systems
Lab #01: Psychophysics
Dr. Y. Seong
September 25, 2022
Prepared By
Group #2
Mikaya Hamilton
Nowshin Sharmile
Jasmine Wiggins
Micah J Xavier
Department of Industrial and Systems Engineering
North Carolina Agricultural and Technical State University
ABSTRACT
Everyone has a unique way of perceiving stimuli. If an identical stimulus is shown to the observer
numerous times, they are likely to have a variety of perceptual responses. One way to measure
thresholds is to give observers a stimulus and record their responses.
The purpose of this study is to investigate, from a psychophysical standpoint, how observers
perceive line length vs actual line length. This is accomplished by providing the observer with a
series of paired stimuli and asking them to determine whether the test stimuli are shorter or longer
compared to the control stimuli.
It was expected that the participant's ability to determine whether the comparison stimuli line is
longer or shorter than the control stimuli line would be affected by the various conditions in the
experiment. This was demonstrated to be correct when it was found that the point of subjective
equality (PSE) for the reverse arrow condition was longer, but the PSE for the arrow condition
was shorter. DL and Weber's constant was found to be longer for arrow, but shorter for reverse
arrow, indicating participants were more sensitive to change when it comes to reverse arrow
conditions.
1
INTRODUCTION
This case study is in correspondence to the Human Machine Systems course given by North
Carolina A&T State University. The human machine system is a system in which the functions of
a human operator (or a group of operators) and a machine are integrated. This term can also be
used to emphasize the view of such a system as a single entity that interacts with the external
environment.
People are exposed to various stimuli, and their reactions to them are very different. Many factors
can affect the response such as environment, attention, interest, physical condition, etc. People
react to changes in sensory modalities differently as well. A threshold is a point where an observer
can notice a stimulus or notice the difference between two stimuli. (Gescheider et al. 1997) For
threshold measurement, there are three methods: the methods of constant stimuli, limits, and
adjustment. Each has its experimental procedure and own way of the mathematical treatment of
data. (Hsia and Drury 1986).
The objective of this study is to run a specific method in psychophysics named The Method of
Constants (Gescheider et al. 1986). This method is used to quantify how a line length is perceived
compared to the actual line length. The study also aims to examine the perceive and actual length
of the lines and find the “psychophysical function” that describes the people’s perception of line
length.
In the method of constants stimuli are not presented in the ordered series, they appear in a pseudorandom order. The participants were presented with two stimuli. One of them was a line of fixed
length i.e., constant stimulus, the other one was of varying length i.e., the comparison stimulus.
The line of varying length appeared out of order and sometimes it was greater than the constant
2
stimulus, sometimes it was smaller. Participants were asked to identify whether the comparison
stimulus was greater than or smaller than the constant stimulus.
The hypothesis is the participant's perception of the relative lengths of the stimuli. i.e., how the
participants perceive the line to be longer or shorter than the control stimuli line would be affected
by the various conditions of the experiment. The stimuli line for the three conditions (standard
line, arrow, and reverse arrow) are the independent variables. The point of subjective equality
(PSE) and the Difference Limen (DL) are the dependent variables.
In psychophysics, the point of subject equality (PSE) is any of the points along a stimulus
dimension at which an observer identifies the variable stimulus (in this case, line length) to be
equal to a standard stimulus. (Vidotto, Anselmi, and Robusto 2019). The difference threshold of
limen (DL) is the minimum intensity of some stimulus that a person can notice with their senses.
It is defined by Ernst Weber as the minimum or lowest intensity that a person will detect on at
least half the trials in a test of the senses. Calculation of PSE and DL will provide insight into the
participant’s perception of line length.
3
METHODOLOGY
The experiment was designed under 3 conditions, each condition must have an equal number of
participants. Each participant was assigned a condition by the instructor. They were:
1. Standard Line
2. Arrow
3. Reverse Arrow
>
<
The experiment consists of 300 trials of experiments. While participating, participants would see
a standard-length line i.e. constant stimulus of the assigned condition (standard line, arrow, reverse
arrow) that appeared at the bottom center of a screen; another one would be of varying length
which then would show up at a random location on the screen. Participants were asked whether
the line was shorter or longer than the standard-length line. Then the participants would provide
their judgment.
The primary focus of this research was to find the difference threshold (DL) and the point of
subjective equality (PSE). PSE indicates whether the line of varying length is judged longer or
shorter than the constant stimulus. If the length is perceived as higher, it means that the PSE would
be high as well. The probability of being perceived longer can be transformed into z-values. Using
the z-values and the line length of the comparison stimulus, a least-squares regression line is fitted
to the psychophysical function. The PSE and DL can be calculated from the regression line.
Participants
The participants of the experiment were students taking the course ISEN 665 (Human Machine
Systems) for Fall 2022.
4
Apparatus
A program file was provided to the participants to experiment. A windows pc had to be used to
install the program needed.
Experimental design and Procedures
1.
The zip files provided in the blackboard were downloaded. After extracting, lab2.exe was run.
2. The name of the participant was provided on the first page and the appropriate condition
(standard line, arrow, reverse arrow) was selected from the drop-down menu, and the
experiment started.
3. Participants were provided with two options, Shorter or Longer as shown in Figure 2.1. Each
was selected by the participant based on the perceived length of the participant.
4. After finishing the experiment with 300 trials, the exit button was clicked
Figure 2.1: Experiment interface for condition 2
Data Collection
Once finished, the data is automatically collected into a txt file named the same as the input name.
This data was exported into MS Excel using the “comma delimited” option. The dataset for the
result contains the name, condition, line length, and participant’s response.
5
RESULTS
After completing the simulation and gathering the data, the data analysis was conducted. The
probability that the user said “Longer” based on line length was calculated and graphed in Figures
3.1, 3.2, and 3.3 shows the ogive plot for all three conditions (standard line, arrow, reverse arrow).
Figure 3.1: Ogive plot for standard line Figure 3.2 Ogive plot for Arrow (condition 2)
(condition 1)
Figure 3.3: Ogive plot for reverse arrow (condition 3)
For all three ogive plots, as the line length increased, the participant perceived the line to be longer
than the condition. Because the slope of the curve is very steep, it did not take much change in the
stimuli dimension for the participants to shift from deciding whether the line is shorter or longer.
However, the errors in people’s judgment can be normally distributed. So, the Excel function,
6
NORMSINV, was applied to the corresponding probabilities to calculate the Z-scores of each
decision based on line length. A plot of the z score and the line length is referred to as the
Gescheider et al.. In figures 3.4, 3.5, and 3.6, a normal probability plot for three different
conditions has been plotted.
Figure 3.4 Normal Probability plot for Figure 3.5 Normal Probability plot for arrow
standard line (condition 1)
(condition 2)
Figure 3.6 Normal Probability plot for standard line (condition 3)
Figure 3.4, 3.5, and 3.6 shows the probability that a line will be shorter or longer. The graphs show
whether a dataset is approximately normally distributed. Figure 3.4, 3.5, and 3.6 also displays the
trendline and regression equation. These equations are the psychophysical equation of each
condition. The slope was computed, and we know that the slope is inversely proportional to the
DL, the higher the slope, the more sensitive the participant is.
7
SUMMARY OUTPUT
Equation
PSE
DL
Regression Statistics
Multiple R
0.803894807
R Square
0.646246861
Adjusted R Square 0.633612821
Standard Error
266.434825
Observations
30
y = 125.1617x +1583.169
1583.168614
84.42030139
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
1
28
29
SS
MS
3631099.552 3631099.552
1987650.448 70987.51598
5618750
F
51.1512412
Significance F
8.77962E-08
Coefficients Standard Error
t Stat
P-value
1583.168614 52.53111886 30.1377288 6.9366E-23
125.1617261
17.50021788 7.152009592 8.77962E-08
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
1475.563495 1690.773733 1475.563495 1690.773733
89.31415485 161.0092974 89.31415485 161.0092974
Figure 3.7: Regression Analysis or condition 1 (Straight Line)
The psychophysical function can also be found by using Figure 3.7, the regression analysis. The
regression analysis is performed using line length as the y-axis, and probability as the x-axis. The
psychophysical function is y = 125.1617 x + 1583.1686. The equation of a straight line is y=ax+b.
So, here the y-intercept (b) is 1583.17, and the coefficient of x (a) is 125.1617. Therefore, PSE and
DL can be calculated using this equation.
For PSE, the probability must be 0.5. Z value at P(0.5)=0. So, x is substituted for 0.
So, PSE= 125.1617*0+1583.1686 =1583.1686
To calculate DL, DL1 represents the change required to move from 25% to 50% recognition, using
excel, the NORMSINV function was used to calculate the z-score value at P(0.25) which was then
substituted in the equation for x.
Z value at P(0.25) = −0.67449
Line length at P(0.25)= 125.1617 (-0.67449) +1583.1686 =1498.748.
The same procedure was used with 0.5 and zero was substituted for x, which resulted in the yintercept value of 1583.169.
Thus, DL(1)= 1583.169 - 1498.748 =84.4203
8
For DL2, the Z value for P(0.75) is needed, however, since the DL is being calculated from a
regression line, the DL(1) and DL(2) value is the same.
𝐷𝐿(1)+𝐷𝐿(2) 84.4203+84.4203
So, DL=
=
2
2
=84.4203
Using a similar approach, DL and PSE values are calculated for the other two conditions. Refer to
figure 3.8 to see the regression analysis for condition 2 (arrow) and 3.9 for condition 3 (reverse
arrow).
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.881511506
R Square
0.777062535
Adjusted R Square 0.769100483
Standard Error
211.5107125
Observations
30
Equation
PSE
DL
y = 85.367x+1636.249
1636.249713
57.5793387
Psychophysical function:
y=85.367x+1636.249
So, PSE=1636.249
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
1
28
29
DL=DL(1)= 1636.249 -
SS
MS
F
Significance F
4366120.118 4366120.118 97.5957584 1.25821E-10
1252629.882 44736.78149
5618750
Coefficients Standard Error
t Stat
P-value
Lower 95%
1636.249713 39.64760478 41.26982505 1.26225E-26 1555.035276
85.36725529 8.641235611 9.879056554 1.25821E-10 67.66648655
1578.67=57.58
Upper 95%
Lower 95.0% Upper 95.0%
1717.464149 1555.035276 1717.464149
103.068024 67.66648655 103.068024
Figure 3.8: Regression Analysis or condition 2 (Arrow)
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.893317011
R Square
0.798015283
Adjusted R Square 0.790801543
Standard Error
201.3261062
Observations
30
Equation
PSE
DL
y = 131.6818x+1844.629x
1844.628688
88.81800796
y=131.6818x+1844.629
So, PSE=1844.629
ANOVA
df
Regression
Residual
Total
Intercept
Z-Value
Psychophysical function:
1
28
29
SS
MS
F
Significance F
4483848.371 4483848.371 110.6243495 3.12135E-11
1134901.629 40532.20102
5618750
Coefficients Standard Error
t Stat
P-value
Lower 95%
1844.628688 38.47647734 47.94172481 2.01162E-28 1765.813197
131.6817756 12.51988412 10.51781106 3.12135E-11 106.0359556
DL=DL(1)= 1844.629 Upper 95%
Lower 95.0% Upper 95.0%
1923.444179 1765.813197 1923.444179
157.3275957 106.0359556 157.3275957
1755.81=88.82
Figure 3.9: Regression Analysis or condition 3 (Reverse Arrow)
9
Class Data
Each participant was assigned a condition. Table 3.1 shows the resulting PSE and DL calculation
for each participant, and the Mean and Standard deviation for DL and PSE for different conditions.
Table 3.1: Table of DL and PSE values for the class, organized by condition, with means and
standard deviations
Condition
1
2
PSE
DL
Standard
1791
77
line
1658
107
1774
95
1884
64.3
1562
76
1622
87.6
1607
82
Arrow
Mean
Mean
Standard
Standard
PSE
DL
Deviation of PSE
Deviation of DL
1776.75
85.83
92.76
18.92
1654.24
87.60
85.66
18.27
1792.50
75.45
114.58
13.23
1777.7 118.8
3
1702.5
73.6
Reverse
1636
57.6
Arrow
1903
80.2
1844
89
1787
75
Figures 3.10 and 3.11 show the plotting of the student’s PSE and DL values respectively.
10
Figure 3.10: Box plot of PSE values by condition
Figure 3.11: Box plot of DL values by condition
∆𝐼
Weber’s Law Weber’s Law is defined as 𝐼 =k where ∆I is the DL, I is the initial stimulus or in
this case mean length, and k is the constant. By using Weber’s Law, Table 3.2 displays the k
values for the class data.
Table 3.2 Summary of PSE, DL, I, and Weber’s constant k for the three conditions.
Condition
Average PSE
Average DL
I
k
1
1776.75
85.825
1725
.0498
2
1654.24
87.6
1725
.0508
3
1792.5
75.45
1725
.0437
11
DISCUSSION
The expectation for the ogive curve is to have a symmetrical ogive shape. A very steep slope for
an ogive curve would indicate that a small change in the stimuli length can make a noticeable
difference, and a less steep slope indicates it takes more of a change to make the shift. The normal
distribution plot was plotted in such a way that the points should form an approximate straight line.
Departure from a straight line indicates departures from normality. The data followed the
theoretical expectations for ogive and normal probability plots.
The PSE value for sample participants for this experiment was 1583.17 for line, 1636.2 for arrow,
and 1844.6 for the reverse arrow. The average value for participants for these conditions were
1776.75, 1654.24, and 1792.5 respectively. It seems that the sample participants’ PSE values are
lower for line and arrow conditions, but higher for the reverse arrow. The actual stimuli length is
1725, so, for condition 1 (line) the average PSE value is closer to the stimuli. It seems that the
participants for condition 1 were able to perceive the line length better than the other two.
The average PSE for condition 2 (arrow) was lower than the actual stimuli length, while the
average PSE for condition 3 (reverse arrow) was higher. So, it looks like the participants who had
condition 2 had a lower length perception than the standard line, while for condition 3, they had a
higher perception. It could be because as the control stimulus for condition 2 diverges, it looks
longer than the actual, and for condition 3 it converges thus making it look smaller.
The DL value for sample participants for this experiment was 84.42 for the line, 57.58 for the
arrow, and 88.82 for the reverse arrow. The average DL value for participants for these conditions
were 85.825, 87.6, and 75.45 respectively. It seems that the sample participants’ DL values are
12
lower for line and arrow conditions, but higher for the reverse arrow. The reverse arrow participant
is less sensitive to change than the average.
The differential threshold or difference limen (DL) represents the amount of change in a stimulus
required to produce a noticeable difference. The steepness of the psychometric function depends
on the observer’s differential sensitivity. Higher DL means an observer needs a higher chance to
observe a noticeable change. In the case study, it seems that the participants with the reverse arrow
required the lowest change, and the arrow condition required the highest change in line length to
see a noticeable difference. This is surprising, since the arrow has the lowest PSE, one would
assume that it would also have a lower DL as observers would notice a difference with smaller
change, but the results beg to differ. The result could mean that while the participants perceived
reverse arrow lines as longer, once their perception changed they identified the longer lines rather
quickly than the line or arrow condition.
The values do differ when DL is computed with probability data rather than the regression line.
For example, when calculated with probability, the PSE is 2150 for the sample participant for
condition 3. After interpolation from the graph, the p(0.25) is 1925 and p(0.75) is 2125, when
calculated, it gives a DL value of 125, which is different from 88.82 gained from regression. This
occurs because a regression takes account of all the data points and error values and from a normal
probability plot we only take account of the change in values.
The k value for line, arrow, and reverse arrow is 0.0498, and 0.0437 respectively. With the values
calculated, it can be found how much longer the test stimulus must be than the control stimuli to
just notice that it is longer. So, for the arrow condition, it needs to be smaller than the rest to be
detectable. No obvious outliers were not found while analyzing the data as well.
13
The result of the DL, PSE, and Weber’s constant for each condition is summarized below:
PSE arrow < PSE standard line < PSE reverse arrow
DL reverse arrow < DL standard line < DL arrow
k reverse arrow < k standard line < k arrow
14
CONCLUSION
The objective of this study was to implement a psychophysical experiment to see how a person
perceived a line length compared to the actual line length. In this study, the method of constants
was applied to see whether it would affect participants’ length perception. It was hypothesized that
the different conditions of the study i.e., line, arrow, the reverse arrow would affect the
participant’s judgment. Participants were randomly assigned a line condition, and the data was
collected from students of ISEN 665 using a computer program. After data collection, the mean
PSE, DL, and k were calculated.
It was found that the participants perceived arrow conditions as longer than the actual length and
reverse arrow conditions as shorter than the actual length. It could be because the diverging arrow
of the arrow caused the participants to perceive the line longer than it is, while the converging
reverse arrow caused the opposite. It was also found that the calculated DL from a normal
probability plot is different from that of the regression line. However, the DL painted another
picture, that the arrow condition had a higher value for difference threshold (DL) and k; while
revere arrow had the lowest, which means on average participants took longer to notice a difference
between the arrow condition, and for reverse arrow condition the difference needed to be smaller.
In short, even though perceived longer, participants noticed smaller changes in length for reverse
arrow quicker.
15
REFERENCES
Gescheider, G. A. (1986). Psychophysics. Hillsdale, NJ: Lawrence Erlbaum.
Gescheider, G. A., J. M. Thorpe, J. Goodarz, and S. J. Bolanowski. 1997. “The Effects of Skin
Temperature on the Detection and Discrimination of Tactile Stimulation.” Somatosensory
& Motor Research 14(3):181–88. doi: 10.1080/08990229771042.
Hsia, P. T., and C. G. Drury. 1986. “A Simple Method of Evaluating Handle Design.” Applied
Ergonomics 17(3):209–13. DOI: 10.1016/0003-6870(86)90008-6.
Vidotto, Giulio, Pasquale Anselmi, and Egidio Robusto. 2019. “New Perspectives in Computing
the Point of Subjective Equality Using Rasch Models.” Frontiers in Psychology 10:2793.
DOI: 10.3389/fpsyg.2019.02793.
16
APPENDIX
Calculation of PSE and DL from normal probability plot
Figure: PSE and DL Calculation from Normal Probability Plot
PSE
For PSE, the Probability must be 0.5. here 3 points correspond to 0.5. The highest value (2150)
was chosen. So, PSE=2150
DL
P(0.25) and P(0.75) were extrapolated from the graph.
P(0.3)corresponds to 1900. P(0.2)
corresponds to 1950. After extrapolating, P(0.25) corresponds to 1925. P(0.7) corresponds to 2100,
p(0.9) corresponds to 2200. After extrapolating, P(0.75) corresponds to 2125.
DL1= |2150-1925|=225 ;DL2=|2150-2125|=25
Thus, DL=(DL1+DL2)/2=(225+25)/2=125
17
Z- value for 3 conditions
(Line)
Line
Probability Z-Value
Length
1000
0.0001 -3.71902
1050
0.0001 -3.71902
1100
0.0001 -3.71902
1150
0.0001 -3.71902
1200
0.0001 -3.71902
1250
0.1 -1.28155
1300
0.9999 3.719016
1350
0.1 -1.28155
1400
0.9999 3.719016
1450
0.4 -0.25335
1500
0.5
0
1550
0.6 0.253347
1600
0.3
-0.5244
1650
0.5
0
1700
0.7 0.524401
1750
0.7 0.524401
1800
0.9999 3.719016
1850
0.9 1.281552
1900
0.9999 3.719016
1950
0.9999 3.719016
2000
0.9999 3.719016
2050
0.9999 3.719016
2100
0.9999 3.719016
2150
0.9999 3.719016
2200
0.9999 3.719016
2250
0.9999 3.719016
2300
0.9999 3.719016
2350
0.9 1.281552
2400
0.9999 3.719016
2450
0.9999 3.719016
18
Arrow
LONGER z-scores
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.90
0.89
1.00
0.80
0.30
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-5.19934
-5.19934
-5.19934
-5.19934
-5.19934
-5.19934
-5.19934
-5.19934
-1.28155
-1.22653
-5.19934
-0.84162
0.524401
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
4.753424
Line
Length
1000
1050
1100
1150
1200
1250
1300
1350
1400
1450
1500
1550
1600
1650
1700
1750
1800
1850
1900
1950
2000
2050
2100
2150
2200
2250
2300
2350
2400
2450
Reverse Arrow
Line
Length
Probability Z-Value
1000
0.00001
-4.264890794
1050
0.00001
-4.264890794
19
1100
1150
1200
1250
1300
1350
1400
1450
1500
1550
1600
1650
1700
1750
1800
1850
1900
1950
2000
2050
2100
2150
2200
2250
2300
2350
2400
2450
0.00001
0.1
0.00001
0.1
0.00001
0.00001
0.00001
0.00001
0.00001
0.00001
0.2
0.1
0.3
0.2
0.2
0.5
0.3
0.2
0.5
0.7
0.7
0.5
0.9
0.99999
0.99999
0.99999
0.99999
0.99999
-4.264890794
-1.281551566
-4.264890794
-1.281551566
-4.264890794
-4.264890794
-4.264890794
-4.264890794
-4.264890794
-4.264890794
-0.841621234
-1.281551566
-0.524400513
-0.841621234
-0.841621234
0
-0.524400513
-0.841621234
0
0.524400513
0.524400513
0
1.281551566
4.264890794
4.264890794
4.264890794
4.264890794
4.264890794
Dataset for All three Conditions
Standard Line
Condition Judgment
Line
Line
Line
Line
Line
Line
Line
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Line Length
Order of stimuli arrival
1000
1000
1000
1000
1000
1000
1000
10
79
86
103
119
131
188
20
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
1000
1000
1000
1050
1050
1050
1050
1050
1050
1050
1050
1050
1050
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1150
1150
1150
1150
1150
1150
1150
1150
1150
1150
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
220
237
256
2
74
76
94
112
137
166
225
238
268
9
16
22
26
77
105
159
200
232
242
21
45
53
80
155
178
234
265
270
295
75
84
110
115
139
147
156
258
271
274
21
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
1250
1250
1250
1250
1250
1250
1250
1250
1250
1250
1300
1300
1300
1300
1300
1300
1300
1300
1300
1300
1350
1350
1350
1350
1350
1350
1350
1350
1350
1350
1400
1400
1400
1400
1400
1400
1400
1400
1400
1400
1450
1450
1450
81
138
145
172
181
208
216
221
239
259
14
41
52
82
102
109
182
206
214
288
44
48
164
170
173
191
194
196
235
300
5
27
107
148
149
222
244
247
287
291
1
19
113
22
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Longer
Shorter
Longer
Shorter
Longer
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Shorter
Shorter
Longer
Longer
1450
1450
1450
1450
1450
1450
1450
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
1550
1550
1550
1550
1550
1550
1550
1550
1550
1550
1600
1600
1600
1600
1600
1600
1600
1600
1600
1600
1650
1650
1650
1650
1650
1650
114
199
201
231
254
263
282
18
106
122
141
151
184
211
213
272
275
23
97
116
153
163
202
218
227
264
277
33
38
146
175
177
217
248
251
253
276
24
28
32
40
83
154
23
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Shorter
Longer
Shorter
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Shorter
Shorter
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
1650
1650
1650
1650
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
1750
1750
1750
1750
1750
1750
1750
1750
1750
1750
1800
1800
1800
1800
1800
1800
1800
1800
1800
1800
1850
1850
1850
1850
1850
1850
1850
1850
1850
185
224
255
267
3
29
64
95
118
152
165
257
262
280
43
63
101
120
130
176
180
197
249
266
4
30
37
51
58
150
205
240
261
298
12
15
31
98
104
124
215
230
252
24
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
1850
1900
1900
1900
1900
1900
1900
1900
1900
1900
1900
1950
1950
1950
1950
1950
1950
1950
1950
1950
1950
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2050
2050
2050
2050
2050
2050
2050
2050
2050
2050
2100
2100
297
25
49
56
60
125
133
144
167
219
246
17
36
47
68
88
108
171
233
236
286
42
57
89
93
123
128
134
168
195
296
35
67
71
127
174
192
193
223
245
273
6
34
25
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
2100
2100
2100
2100
2100
2100
2100
2100
2150
2150
2150
2150
2150
2150
2150
2150
2150
2150
2200
2200
2200
2200
2200
2200
2200
2200
2200
2200
2250
2250
2250
2250
2250
2250
2250
2250
2250
2250
2300
2300
2300
2300
2300
72
111
198
209
212
241
278
294
54
59
73
96
140
143
204
243
281
290
50
65
126
129
157
158
169
260
269
293
8
13
46
55
100
136
179
186
187
285
66
70
92
132
160
26
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Line
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
2300
2300
2300
2300
2300
2350
2350
2350
2350
2350
2350
2350
2350
2350
2350
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
2450
2450
2450
2450
2450
2450
2450
2450
2450
2450
161
210
229
250
284
7
11
62
69
78
91
99
207
226
292
61
87
121
142
183
189
203
228
279
283
20
39
85
90
117
135
162
190
289
299
Arrow
Condition
Arrow
Arrow
Judgment
Shorter
Shorter
Line Length
Order of stimuli arrival
1450
1
1050
2
27
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Longer
Longer
Shorter
Longer
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Shorter
Shorter
1700
1800
1400
2100
2350
2250
1100
1000
2350
1850
2250
1300
1850
1100
1950
1500
1450
2450
1150
1100
1550
1650
1900
1100
1400
1650
1700
1800
1850
1650
1600
2100
2050
1950
1800
1600
2450
1650
1300
2000
1750
1350
1150
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
28
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Longer
Shorter
Longer
Longer
2250
1950
1350
1900
2200
1800
1300
1150
2150
2250
1900
2000
1800
2150
1900
2400
2350
1750
1700
2200
2300
2050
1950
2350
2300
2050
2100
2150
1050
1200
1050
1100
2350
1000
1150
1250
1300
1650
1200
2450
1000
2400
1950
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
29
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Shorter
2000
2450
2350
2300
2000
1050
1700
2150
1550
1850
2350
2250
1750
1300
1000
1850
1100
1500
1400
1950
1300
1200
2100
1050
1450
1450
1200
1550
2450
1700
1000
1750
2400
1500
2000
1850
1900
2200
2050
2000
2200
1750
1000
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
30
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Longer
Longer
Longer
Shorter
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Longer
Shorter
Longer
Shorter
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Longer
Shorter
Shorter
Longer
2300
1900
2000
2450
2250
1050
1250
1200
2150
1500
2400
2150
1900
1250
1600
1200
1400
1400
1800
1500
1700
1550
1650
1150
1200
2200
2200
1100
2300
2300
2450
1550
1350
1700
1050
1900
2000
2200
1350
1950
1250
1350
2050
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
31
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Shorter
Longer
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Longer
Shorter
Longer
Shorter
Longer
Longer
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Longer
1600
1750
1600
1150
2250
1750
1250
1300
2400
1500
1650
2250
2250
1000
2400
2450
1350
2050
2050
1350
2000
1350
1750
2100
1450
1100
1450
1550
2400
2150
1800
1300
2350
1250
2100
2300
1500
2100
1500
1300
1850
1250
1600
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
32
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Shorter
Longer
Shorter
Shorter
Longer
1550
1900
1000
1250
1400
2050
1650
1050
2350
1550
2400
2300
1850
1450
1100
1950
1150
1350
1950
1000
1050
1250
1800
2100
1100
2150
1400
2050
1900
1400
1600
1750
2300
1600
1850
1600
1450
1650
1000
1700
1200
1250
2200
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
33
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Arrow
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Shorter
Shorter
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Shorter
1800
1700
1450
1550
1150
1750
1650
1050
2200
1150
1200
1500
2050
1200
1500
1600
1550
2100
2400
1700
2150
1450
2400
2300
2250
1950
1400
1300
2450
2150
1400
2350
2200
2100
1150
2000
1850
1800
2450
1350
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
34
Reverse Arrow
Arrow Type
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Dec
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Line Length
Attempt
1000
1000
1000
1000
1000
1000
1000
1000
1000
1000
1050
1050
1050
1050
1050
1050
1050
1050
1050
1050
1100
1100
1100
1100
1100
1100
1100
1100
1100
1100
1150
1150
1150
1150
1150
1150
1150
1150
1150
10
79
86
103
119
131
188
220
237
256
2
74
76
94
112
137
166
225
238
268
9
16
22
26
77
105
159
200
232
242
21
45
53
80
155
178
234
265
270
35
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
1150
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1250
1250
1250
1250
1250
1250
1250
1250
1250
1250
1300
1300
1300
1300
1300
1300
1300
1300
1300
1300
1350
1350
1350
1350
1350
1350
1350
1350
1350
1350
1400
1400
295
75
84
110
115
139
147
156
258
271
274
81
138
145
172
181
208
216
221
239
259
14
41
52
82
102
109
182
206
214
288
44
48
164
170
173
191
194
196
235
300
5
27
36
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
1400
1400
1400
1400
1400
1400
1400
1400
1450
1450
1450
1450
1450
1450
1450
1450
1450
1450
1500
1500
1500
1500
1500
1500
1500
1500
1500
1500
1550
1550
1550
1550
1550
1550
1550
1550
1550
1550
1600
1600
1600
1600
1600
107
148
149
222
244
247
287
291
1
19
113
114
199
201
231
254
263
282
18
106
122
141
151
184
211
213
272
275
23
97
116
153
163
202
218
227
264
277
33
38
146
175
177
37
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
1600
1600
1600
1600
1600
1650
1650
1650
1650
1650
1650
1650
1650
1650
1650
1700
1700
1700
1700
1700
1700
1700
1700
1700
1700
1750
1750
1750
1750
1750
1750
1750
1750
1750
1750
1800
1800
1800
1800
1800
1800
1800
1800
217
248
251
253
276
24
28
32
40
83
154
185
224
255
267
3
29
64
95
118
152
165
257
262
280
43
63
101
120
130
176
180
197
249
266
4
30
37
51
58
150
205
240
38
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Shorter
Longer
Longer
Longer
Longer
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Longer
Longer
Shorter
Shorter
Shorter
Shorter
Shorter
Longer
Shorter
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
Longer
Shorter
Shorter
Shorter
Longer
Longer
Shorter
Longer
1800
1800
1850
1850
1850
1850
1850
1850
1850
1850
1850
1850
1900
1900
1900
1900
1900
1900
1900
1900
1900
1900
1950
1950
1950
1950
1950
1950
1950
1950
1950
1950
2000
2000
2000
2000
2000
2000
2000
2000
2000
2000
2050
261
298
12
15
31
98
104
124
215
230
252
297
25
49
56
60
125
133
144
167
219
246
17
36
47
68
88
108
171
233
236
286
42
57
89
93
123
128
134
168
195
296
35
39
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Longer
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Shorter
Shorter
Shorter
Longer
Shorter
Longer
Longer
Longer
Longer
Shorter
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
2050
2050
2050
2050
2050
2050
2050
2050
2050
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
2150
2150
2150
2150
2150
2150
2150
2150
2150
2150
2200
2200
2200
2200
2200
2200
2200
2200
2200
2200
2250
2250
2250
2250
67
71
127
174
192
193
223
245
273
6
34
72
111
198
209
212
241
278
294
54
59
73
96
140
143
204
243
281
290
50
65
126
129
157
158
169
260
269
293
8
13
46
55
40
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Reverse Arrow
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
Longer
2250
2250
2250
2250
2250
2250
2300
2300
2300
2300
2300
2300
2300
2300
2300
2300
2350
2350
2350
2350
2350
2350
2350
2350
2350
2350
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
2450
2450
2450
2450
2450
2450
2450
100
136
179
186
187
285
66
70
92
132
160
161
210
229
250
284
7
11
62
69
78
91
99
207
226
292
61
87
121
142
183
189
203
228
279
283
20
39
85
90
117
135
162
41
Reverse Arrow
Reverse Arrow
Reverse Arrow
Longer
Longer
Longer
2450
2450
2450
190
289
299
42