Effects of lying in practical Turing tests

Interpretation of utterances affects an interrogator’s determination of human from machine during live Turing tests. Here, we consider transcripts realised as a result of a series of practical Turing tests that were held on 23 June 2012 at Bletchley Park, England. The focus in this paper is to consider the effects of lying and truth-telling on the human judges by the hidden entities, whether human or a machine. Turing test transcripts provide a glimpse into short text communication, the type that occurs in emails: how does the reader determine truth from the content of a stranger’s textual message? Different types of lying in the conversations are explored, and the judge’s attribution of human or machine is investigated in each test.

Are sulfurous soil amendments (S0, Fe(II)SO4, Fe(III)SO4) an effective tool in the restoration of heathland and acidic grassland after four decades of rock phosphate Fertilization?

This paper deals with the complex issue of reversing long-term improvements of fertility in soils derived from heathlands and acidic grasslands using sulfur-based amendments. The experiment was conducted on a former heathland and acid grassland in the U.K. that was heavily fertilized and limed with rock phosphate, chalk, and marl. The experimental work had three aims. First, to determine whether sulfurous soil amendments are able to lower pH to a level suitable for heathland and acidic grassland re-creation (approximately 3 pH units). Second, to determine what effect the soil amendments have on the available pool of some basic cations and some potentially toxic acidic cations that may affect the plant community. Third, to determine whether the addition of Fe to the soil system would sequester PO4− ions that might be liberated from rock phosphate by the experimental treatments. The application of S0 and Fe(II)SO4− to the soil was able to reduce pH. However, only the highest S0 treatment (2,000 kg/ha S) lowered pH sufficiently for heathland restoration purposes but effectively so. Where pH was lowered, basic cations were lost from the exchangeable pool and replaced by acidic cations. Where Fe was added to the soil, there was no evidence of PO4− sequestration from soil test data (Olsen P), but sequestration was apparent because of lower foliar P in the grass sward. The ability of the forb Rumex acetosella to apparently detoxify Al3+, prevalent in acidified soils, appeared to give it a competitive advantage over other less tolerant species. We would anticipate further changes in plant community structure through time, driven by Al3+ toxicity, leading to the competitive exclusion of less tolerant species. This, we suggest, is a key abiotic driver in the restoration of biotic (acidic plant) communities.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Tests of sunspot number sequences: 1. Using ionosonde data

More than 70 years ago it was recognised that ionospheric F2-layer critical frequencies [foF2] had a strong relationship to sunspot number. Using historic datasets from the Slough and Washington ionosondes, we evaluate the best statistical fits of foF2 to sunspot numbers (at each Universal Time [UT] separately) in order to search for drifts and abrupt changes in the fit residuals over Solar Cycles 17-21. This test is carried out for the original composite of the Wolf/Zürich/International sunspot number [R], the new “backbone” group sunspot number [RBB] and the proposed “corrected sunspot number” [RC]. Polynomial fits are made both with and without allowance for the white-light facular area, which has been reported as being associated with cycle-to-cycle changes in the sunspot number - foF2 relationship. Over the interval studied here, R, RBB, and RC largely differ in their allowance for the “Waldmeier discontinuity” around 1945 (the correction factor for which for R, RBB and RC is, respectively, zero, effectively over 20 %, and explicitly 11.6 %). It is shown that for Solar Cycles 18-21, all three sunspot data sequences perform well, but that the fit residuals are lowest and most uniform for RBB. We here use foF2 for those UTs for which R, RBB, and RC all give correlations exceeding 0.99 for intervals both before and after the Waldmeier discontinuity. The error introduced by the Waldmeier discontinuity causes R to underestimate the fitted values based on the foF2 data for 1932-1945 but RBB overestimates them by almost the same factor, implying that the correction for the Waldmeier discontinuity inherent in RBB is too large by a factor of two. Fit residuals are smallest and most uniform for RC and the ionospheric data support the optimum discontinuity multiplicative correction factor derived from the independent Royal Greenwich Observatory (RGO) sunspot group data for the same interval.