Nickole Atkinson could. And giving out extraneous information, just being a lot more talkative than usual, is a classic symptom of lying. When he was being interrogated by the FBI, and during his polygraph, Watts was trying very hard to appear like a regular guy. Open, talkative, transparent, not himself. He was doing this to hide the fact that there was an awful lot he was hiding. And it took a while for his interrogators to latch on this.
Is affect important?
What is a factor?
How important is affect? Right here, we hear how forcefully Watts was confronted by both agents here, on his affect. And then, what happened after this? This confrontation took place about a minute before he asked to see his father. The ruse that he was hoping they were still alive was finally over. We can see how, in an interrogation scenario, telling a suspect how his affect is raising suspicion, is a clear way of riling him up, but also potentially shutting him down. He felt panic and wanted to fix his situation. So did Kessinger, and Nickole Atkinson [who went to work], as well as law enforcement.
While law enforcement bided their time on Monday night, Watts cleaned and vacuumed the crime scene. Why, because he had succeeded in infecting them with false hope. He likely felt a range of emotions, from reluctance, to resistance to relief, and even joy when it was over. So when Watts is confronted about his affect, he instinctively and immediately ratchets his affect up a notch. He sniffles. When he talks to his father his demeanor and his voice changes.
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This is why pretending to hope is a red flag. In the McCann case, as in the Watts case [early on] the question was always: is the pretense to hide what he did, or is it simply human weakness?
A year after we studied his body language, counted his tells, figured out his psychology, and became experts at lie spotting, the followers of this case are split into two camps. Children murdered first, at home; premeditated murder. And those who believe Watts. If Watts fully intended to get away with murder, and he did, he would never have taken the enormous risk to take his children — alive — to the well site and murder them there. The shadows on the driveway that some see as a child brought back to life, is the same hopefulness blinding us to the truth. I believe Watts is responsible for all their murders.
I think the answer to how it went down lies in the edited out recording from Feb Like Like. Like Liked by 1 person. It was one of the unexpected pieces of the planned murders. Horrifying, but possible. I believe that, as soon as the girls were knocked out, he would have wrapped plastic bags around their heads to make sure.
Funny you should mention your plastic bag theory, Ralph. I believe he wanted the murders to occur together in short succession, so estimated timing of deaths would line up closely with the tale he intended to tell later on in his plan. Just briefly, I need to entertain the possibility that one of the children was alive on the ride to Cervi and how that could possibly happen. Those plastic bags used to carry groceries from the store often end up with tiny holes or tears in the bottom from sharp items.
Table of contents
Nick had a fairly recent video explaining that the shadows that some thought were the girls were actually caused by the position of the sun, light sources, time of day and would make it appear that something small was moving toward CW. Hi Nick. Really enjoyed reading your assessment There is a movie coming up about Chris Watts.
Show all. Canuto Tabacco, Dept. Anita Tabacco, Dept.
Undergraduate Courses | Mathematical Institute Course Management
It provides a good coverage of the material, a very good choice of exercises, and an impeccable graphical presentation. The textbook is written for first-year students whose interest is not mainly in mathematics, yet mathematics plays an important role in their curricula. The authors attained their goal. Table of contents 11 chapters Table of contents 11 chapters Basic notions Pages Canuto, Claudio et al. Functions Pages Canuto, Claudio et al.
Limits and continuity I Pages Canuto, Claudio et al. Local comparison of functions.
Numerical sequences and series Pages Canuto, Claudio et al. Differential Calculus Pages Canuto, Claudio et al. Taylor expansions and applications Pages Canuto, Claudio et al. Data may be output at different resolutions by the different sensors but are usually aggregated to 10 Hz 0. Addi- tional variables, such as vehicle position relative to the curve, were calculated and reported at the same resolution. Changes in pedal position and speed were smoothed over 0.
An example of time series data was shown in Table 3. Speed was reported at 0. Pedal position was also usually available but in many cases was reported at less frequent intervals e. Consequently, only traces that had been reduced for the initial data request about that had both speed and pedal position reported at 0. Additionally, only curves with a minimum distance of m 1, Analyses in Phase 1 had suggested that drivers begin reacting to the curve within m ft , so provision of m 1, Data were extracted for each curve of interest for a distance of m 1, Sample size was limited by the constraints described above.
Curve radius varied from m to 7, m Three curves had chevrons, four had W signs, none had rumble strips, five had guard- rails, 21 had raised pavement markings, and 16 had curve advisory signs. Methodology for Defining Curve area of Influence The point at which significant pedal position changes occurred was obvious in some traces, as shown in Figure 6. In other cases, sufficient noise was present for pedal position and steer- ing wheel position, so it was more difficult to identify the point of reaction, as shown in Figure 6.
A change point model was used to determine where drivers were reacting to the curve. A separate model was fit to each curve for each event using time series data. Change point mod- els were fit using the statistical package R, which uses a regres- sion model based on Muggeo A change point model was selected because it could identify the point at which speed or pedal position changed significantly from upstream driving.
The third parameter of the model, b2, represents the strength of the reaction. If b2 is not significantly different from zero, this indicates that the driver did not react in a noticeable way to the curve. The identified reaction points are only meaningful if the strength of the reaction, the value of b2, is significantly different from zero. Models were developed independently for speed and pedal position for each curve, for travel in the direction inside of the curve and outside of the curve. Figure 6.
Change in pedal position for two drivers Florida Curve A model was developed for each trace for each curve. Model results are provided in Appendix C. Results are shown graphically in Figures 6. Traces for many curves have similar reaction points, as indicated by the slope of the line changing at about the same point, such as curves IN44Ain and IN44Jout. The average point at which drivers reacted for all curves was m Results were aver- aged by curve radius, as shown in Table 6.
Pedal Position Model Change point models were also developed using pedal posi- tion as an indicator of driver response. This variable has no units, but is a measure of how far the driver is pushing down on the gas pedal. If the value increases, the driver is increasing pressure on the pedal, and if the value decreases, the driver is decreasing pressure letting up on the pedal.
For the same traces across 36 curves in Indiana, New York, and North Carolina, the fitted change point models show pedal position as the dependent variable.
Model results are provided indi- vidually in Appendix C. Results are plotted graphically in Fig- ures 6. As noted, some of the curves have very similar reaction points for all events, which can be seen in curves IN13Aout and IN44Iout.
Others, however, have very separated reaction points e. The furthest reaction point was approximately m 1, Change in pedal position for one trace in which change is not obvious. Fitted speed models for Indiana curves. Fitted speed models for New York curves. The average point at which drivers reacted for all curves was m upstream of the curve, which was similar to the results for the speed models. Results were averaged by curve radius, as shown in Table 6. Results for individual models are shown provided in Appendix C.