y was in the dome.

2.2. Detection of the “Pyramid Power” (Non-Contact Effect)

In order to clarify the presence of the “pyramid power” in the PS, we verified the non-contact effect on the biosensors (cucumber fruit sections). In general, injuries to living bodies such as plants are known to cause biological protection and repair reactions [7 - 10]. Regarding these reactions, we noticed that there was a variable gas concentration from a gas generation reaction on the cut section (an injury) of the cucumbers and we analyzed the gas concentration to verify the existence of the “pyramid power” (non-contact effect). To prepare uniform biosensors, we used the simultaneous calibration technique (SCAT) (Figure 1(b)) [11]. Researchers at the International Research Institute (IRI) developed the non-contact effect measuring methods based on gas concentration. And using these measurement methods, we successfully detected the healer’s non-contact effect and a wave like bio-field around the healer [12 - 14].

The experimental samples GE1 and GE2 of Pair1 and Pair2 in Figure 1(b) were placed at the PS apex. The control samples GC1 and GC2 of Pair1 and Pair2 and experimental samples GE3, GE4, and control samples GC3 and GC4 of Pair3 and Pair4 were placed at the calibration control point 8 m away from the PS. The experimental and control samples were kept in their respective places for 30 minutes. GE and GC were the same cut section, but the direction of the cut section was different. The cut section of GE was in the same direction with respect to the growth axis of the cucumbers, but the cut section of GC was in the reverse direction. We had previously confirmed experimentally that a difference appeared in the released gas concentration due to the difference in the direction of the cut section, and the gas concentration was GE < GC [15 , 16].

While the samples were placed at the PS apex and calibration control point, they were electrostatically shielded by an electrically grounded Faraday cage. The Faraday cage was at a height of 180 cm from the floor. At the top of the PS, GE1, GE2, the Faraday cage and a circular copper mesh were put on the PS using insulated support legs (Figure 1(a), Figure 1(c)). Under the stacked samples (GE1 on the bottom, GE2 on the top) there was a circular copper mesh. The circular copper mesh was grounded. The center of the bottom of the Petri dish of GE1 and the extended center longitudinal line of the four aluminum pipes of the PS apex coincided (Figure 1(c) right). On the other hand, GC1 and GC2, GE3 and GE4, and GC3 and GC4 were stacked at the calibration control point in three groups. The larger numbered Petri dish was placed on top for each group. After 30 minutes, the lids of the paired Petri dishes were removed, and each Petri dish was placed in a separate sealed container with a volume of 2.2 liters; the pairs were stored side by side. The storage time was 24 h - 48 h. After storage, the gas concentrations released from the cucumber sections were measured. Gas detection tubes (Ethyl acetate detector tube 141L: Gastech, Japan) and a gas sampling pump (GV-100: Gastech, Japan) were used to measure the gas concentrations.

2.3. Calculation of the Psi Index (ψ) Representing the Magnitude of the Non-Contact Effect

In order to verify the existence of the “pyramid power” for the biosensors placed at the PS apex, in this paper, we introduced the psi index (Ψ), which is an index to quantify the magnitude of the “pyramid power” (non-contact effect). The effect of “pyramid power” can be buried within the noise of the data. The reason is that cucumbers as the biosensors are very sensitive to factors such as individual cucumber differences and environmental conditions. In order to minimize such variables, we adopted a paired sample method (Figure 1(b)) where GE and GC are paired and compared. The Ψ values are 100 times the natural logarithm of the ratio calculated for the gas concentrations of each pair. The relationship between the J value [17] we have used previously and Ψ was Ψ = 100J.

Ψ1 = 100ln (GE1/GC1),

Ψ2 = 100ln (GE2/GC2),

Ψ3 = 100ln (GE3/GC3),

Ψ4 = 100ln (GE4/GC4). (1)

In Equation (1), GE1 to GE4 and GC1 to GC4 were gas concentrations (ppm) measured from the samples as arranged in Figure 1(b). The Ψ1 to Ψ4 values were the psi index before calibration. From Ψ3 and Ψ4, we thought that the influence due to the difference in the direction of the cut sections of the cucumbers was detected. In addition, we thought that from Ψ1 and Ψ2, the result of two influences due to the difference in the direction of the cutting section and the difference in the placement (the PS apex and calibration control point) could be detected. Ψ1(E-CAL) and Ψ2(E-CAL) obtained by subtracting the average value of Ψ3 and Ψ4 from Ψ1 and Ψ2 are results of calibration of various external environment effects such as temperature, humidity, atmospheric pressure, and geomagnetism. Therefore, Ψ1(E-CAL) and Ψ2(E-CAL) were considered to reflect only the influence from the PS.

Ψ1(E-CAL) = Ψ1-(Ψ3 + Ψ4)/2,

Ψ2(E-CAL) = Ψ2-(Ψ3 + Ψ4)/2. (2)

Finally, the calibrated psi index at the PS apex was determined by

ΨE-CAL = (Ψ1(E-CAL) + Ψ2(E-CAL))/2. (3)

2.4. Analysis of the Experimental Data

From the results of the earlier experiments that “the PS and a human were related”, we found that the PS has a function to capture and convert two force types of a human. From this PS function, we saw two points. 1) A human unconsciousness (force type I) was detected from an experiment several hours before a human (the test subject) entered and meditated inside the PS [1 , 2]. 2) When a human (the test subject) entered the PS and meditated, the influence (force type II) was detected for more than ten days [4 - 6]. In the present paper, we have turned our attention to experimental verification of whether there is a potential power in the PS when “the PS and a human were not related”. Therefore, experimental data conducted without the influence of a human’s (the test subject’s) force type was necessary. We analyzed data obtained from experiments meeting the following three conditions. 1) The experiment was conducted without a human (the test subject) in the PS. 2) The experiment was conducted without a human in the PS for at least 20 days before conducting the experiment. 3) After the experiment, no human was kept inside the PS for at least 48 hours.

3. Results of the Experiment and Analysis

Figure 2(a) is the distribution of ΨE-CAL, which represents the magnitude of the non-contact effect calculated from the gas concentration. The vertical axis is ΨE-CAL, and the horizontal axis is the date. The dates are values from 1 to 366 obtained by starting at 1 and counting from January 1 of each year in which the experiment was conducted. The data analyzed in this paper were obtained from experiments between

Figure 2. The psi index (ΨE-CAL) in the case that “the PS and a human were not related”. (a) The vertical axis is ΨE-CAL, and the horizontal axis is the date. The dates are values from 1 to 366 obtained by starting at 1 and counting from January 1 of each year in which the experiment was conducted. The red circles are summer data (n = 252) and the blue triangles are winter data (n = 216). (b) the vertical axis is the ΨE-CAL and the horizontal axis shows the average of the data for three groups: all data (black square), summer data (red circle) and winter data (blue triangle). All error bars show 99% confidence interval.

July 2010 and September 2017. For experimental data of the same period, we previously published six papers [1 - 6] on the function of the PS in which we discovered that “the PS and a human were related” and two papers [15 , 16] on the characteristics of the biosensors. The red circles are summer data and the blue triangles are winter data. In Figure 2(a) summer data were the results obtained by experiments when the daytime was more than 12 hours. Summer was therefore from the day of the spring equinox to the day of the autumn equinox. The day of the spring equinox when not a leap year was March 20, and the value on the horizontal axis, 81. The day of the autumn equinox when not a leap year was September 23, and the value on the horizontal axis, 267. Analogously, winter data were the results obtained by experiments when the day length was less than 12 hours. The numbers of data were n = 252 for summer data and n = 216 for winter data.

In Figure 2(b), the vertical axis is the ΨE-CAL, and the horizontal axis shows the three groups of data: all data (black square), summer data (red circle) and winter data (blue triangle). All error bars show 99% confidence interval. The average value of the summer data had 1% significance and the ΨE-CAL was a positive value. However, the average value of all data and winter data became zero within the margin of error. This was the result of the experiments conducted when “the PS and a human were not related”. Thus, in the summer, the non-contact effect on the biosensors was significant, demonstrating the existence of a potential power of the PS (the “pyramid power”). As a result of analysis of variance (ANOVA), p = 6.0 × 10−3. The p value is a measure showing the possibility that the difference between the average value of the summer data and the winter data may occur by chance (Welch’s t-test, two-tails).

From the result of Figure 2(b), the presence of the potential power of the PS was demonstrated (1% significance).

Figure 3 shows the result of calculating the moving average of the ΨE-CAL. Figures 3(a)-(c) are the

Figure 3. Moving average of ΨE-CAL. The moving average of ΨE-CAL that is shown in Figure 2(a). The sizes of the moving average window are 60 days (a)), 120 days (b)) and 180 days (c)). The vertical axis is ΨE-CAL, and the horizontal axis is date as explained in the caption of Figure 2(a). (d) is the result of overlapping (a)-(c).

results of moving average when the window size of the ΨE-CAL shown in Figure 2(a) is 60 days, 120 days and 180 days, respectively. Figure 3(d) shows the results of overlapping Figures 3(a)-(c). From these results, it became clear that the non-contact effect due to the potential power of the PS was exhibiting a convex shape for the plotted ΨE-CAL values in summer. We also found that the potential power of the PS affected the biosensors throughout the year. However, it is difficult to determine if the potential power of the PS is changing continuously throughout the year or if discontinuous changes occur.

From the result of Figure 3, the following two results were demonstrated. 1) The potential power of the PS changed in value between summer and winter. 2) The potential power of the PS (non-contact effect on the biosensors) was larger in summer and smaller in winter.

Figure 4 shows the psi index before calibration. Figure 4(a) shows the moving average of (Ψ1 + Ψ2)/2, and Figure 4(b) shows the moving average of (Ψ3 + Ψ4)/2. The moving average window size is 180 days. (Ψ1 + Ψ2)/2 includes the results of the samples GE1 and GE2 placed at the PS apex. On the other hand, (Ψ3 + Ψ4)/2 includes only the results of the samples placed at the calibration control point. The convex shape seen for the plotted summer data in Figure 3(d) appeared prominently in Figure 4(a) but did not appear in Figure 4(b). Therefore, we found that the potential power of the PS detected as a non-contact effect mainly affected the biosensors placed at the PS apex. The correlation coefficient between Figure 4(a) and Figure 4(b) was not a strong correlation, being 0.296.

From the result of Figure 4, it was demonstrated that the potential power of the PS affected only the biosensors placed at the PS apex, and did not affect the biosensors placed at the calibration control point 8 m away from the PS.

Figure 4. The moving averages of the psi index (Ψ1 + Ψ2)/2 and (Ψ3 + Ψ4)/2 before calibration. (a) is the moving average of (Ψ1 + Ψ2)/2 and (b) is the moving average of (Ψ3 + Ψ4)/2. The horizontal axis is the date as explained in the caption of Figure 2(a). The moving average window size is 180 days. The correlation coefficient between (a) and (b) is 0.296.

4. DISCUSSION AND CONCLUSION

We conducted experiments to verify the non-contact effect of the PS on biosensors under the condition that “the PS and a human were not related”. From them we had three results. 1) The presence of the potential power of the PS was demonstrated with 1% significance (Figure 2(b)). 2) The potential power of the PS showed different characteristics in the summer and the winter. We found that the psi index (Ψ), which represents the magnitude of the non-contact effect, tended to increase in the summer and decrease in the winter (Figure 3). 3) The potential power of the PS affected only the biosensors placed at the PS apex, and not the biosensors placed at the calibration control point (Figure 4). From these results, we concluded that there was a potential power (the “pyramid power” that affected the biosensors) of the PS alone in the case that “the PS and a human were not related”. We also concluded that the potential power of the PS varied with the season. This paper is the first report in the world to show this type of effect by scientific measurements.

In order to understand why the non-contact effect due to the potential power of the PS varied with the season, we proposed a hypothesis. First, we discussed the relationship between the potential power of the PS and the gas generation reaction of cucumbers. For this purpose, we considered the change of the psi index before calibration in Figure 4. The result of (Ψ3 + Ψ4)/2, which was not affected by the PS, was considered to be almost constant at negative values throughout the year (Figure 4(b)) [16]. On the other hand, (Ψ1 + Ψ2)/2, which included the results of the samples placed at the PS apex, was larger in summer and smaller in winter than (Ψ3 + Ψ4)/2 (Figure 4(a)). To understand these features, we assumed the following three things. 1) There were two types of potential power (potential power 1 (P1) and potential power 2 (P2)) near the PS apex (Figure 5(a)). 2) There were at least two types of gas generation reactions

Figure 5. The schematic diagram to consider the seasonal change of potential power of the PS. (a) We hypothesized that two kinds of potential power (P1, P2) existed near the PS apex. Samples GE1 and GE2 placed at the PS apex were affected by P1 and P2. (b) We hypothesized two kinds of gas generation reactions of the cucumbers (α reaction, β reaction). αE, βE: Average gas concentration generated from experimental samples by α and β reactions. αC, βC: Average gas concentration generated from control samples by α and β reactions. From the axial characteristics of the cucumber sections, αE < αC, βE < βC. Here, we assumed that αE = βE and αC = βC. The α reaction was suppressed by P1 in the winter, and αE of GE1 & GE2 became αE(winter). The β reaction was promoted throughout the year by P2, and βE of GE1 & GE2 became βE(year).

of the cucumbers: reaction α and reaction β (Figure 5(b)). 3) The samples GE1 and GE2 placed at the PS apex were affected by the two potential powers P1 and P2 of the PS. The αE and βE in Figure 5(b) were the average gas concentrations generated from the experimental samples by the α reaction and β reaction. Similarly, αC and βC were average gas concentrations generated from the control samples. The reason why αE < αC and βE < βC in Figure 5(b) came from the characteristic that the concentration of released gas differed depending on the difference in the axial direction of the cucumber cut section [15 , 16].

Here, in order to facilitate understanding, we assumed αE = βE, αC = βC. At this time, if the following relationship between the potential power of the PS and the gas generation reaction exists, it is possible to understand the results of Figure 4: “The α reaction suppresses gas generation in winter by the potential power P1 of the PS. As a result, αE of GE1 and GE2 becomes αE(winter). The β reaction promotes gas generation throughout the year by the potential power P2 of the PS. As a result, βE of GE1 and GE2 becomes βE(year).” If the results of Figure 4(a) and Figure 4(b) can be derived from the relationship between the potential power of the PS and the gas generation reaction, it can be understood that the change of non-contact effect (ΨE-CAL) in Figure 3 is caused by the potential power of the PS.

We experimentally demonstrated the existence of the potential power of the PS and some of its properties. This opens up the possibility that the so-called “pyramid power”, which has often been recognized as having no scientific basis, may become a new field of science. The issues to be further investigated are changing the experimental variables such as the structural parameters of the PS (e.g., size, material and the fractal patterns). So many issues remain to be studied. In the future, we may expect to see developments in many fields applying the “pyramid power”.

A part of this research was done under the Sakamoto Hyper-tech Project (SHyP, October 2007 to September 2017) as a joint activity between Aquavision Academy Co., Ltd. (President: Masamichi Sakamoto) and the International Research Institute (IRI, Chairman of the Board of Directors: Mikio Yamamoto).

Cite this paper
Takagi, O. , Sakamoto, M. , Yoichi, H. , Kawano, K. and Yamamoto, M. (2019) Potential Power of the Pyramidal Structure. Natural Science, 11, 257-266. doi: 10.4236/ns.2019.118026.
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