A psychological tool for helping the public feel invested in climate change.

<p>A psychological tool for helping the public feel invested in climate change.</p><p>Talking to audiences about climate change in a way that helps them feel empowered is a challenge that many geoscientists feel ill-equipped to tackle. In this presentation, I demonstrate how using a blend of reverse psychology and cognitive dissonance can lead to an audience feeling highly activated and motivated. </p><p>I used data and presentation techniques to trick an audience into firmly believing that climate change is a hoax - and then revealed the hoax. I was able to use the initial anger and frustration to elicit highly positive states of mind and feelings of personal empowerment. Audiences report a  much higher degree of climate literacy and a greater sense of awareness of their role in the fight again climate change. This strategy also appears to effective in convincing 'climate sceptics' that they are mistaken.</p><p>Questionnaires collected after 24 of these presentations reveal 100% of participants left feeling 'invested' in climate change. 95% additionally felt 'motivated to learn more and take action'. When asking sceptical audiences, 85% said that the presentation had forced them to re-evaluate their pre-existing beliefs. 60% said they now felt anthropogenically driven climate change was likely a reality. 100% of sceptics wanted to learn more.</p><p>The neurophysiology of our brains explains this data. When paired with strong emotions - positive or negative - information is more likely stored in memory centres. Audiences that already understood climate change to be a threat switch from anxiety/anger /confusion to relief/happiness/wonder. Such a large jump in emotional state triggers a strong dopaminergic system response. By forcing the audience to consider why they were susceptible to the hoax in the first place, the positive mindset makes them feel empowered and eager to learn more.</p><p>In the case of climate sceptics; by mirroring their own arguments, I demonstrate empathy by appreciating their perspectives. Whilst the resulting cognitive dissonance of having the hoax 'unmasked' is deeply uncomfortable, I able to convert this strong negative emotion into a positive one. I do this by a) empathising with the discomfort b) showing solidarity with them c) being open about why I used the strategy I did.</p><p>In summary, by marrying geocommunication with brain science, we can look forward to exploring more innovative strategies that make members of the public feel more invested and activated.</p>

New Evidence of the Marginal Predictive Content of Small and Large Jumps in the Cross-Section

We investigate the marginal predictive content of small versus large jump variation, when forecasting one-week-ahead cross-sectional equity returns, building on Bollerslev et al. (2020). We find that sorting on signed small jump variation leads to greater value-weighted return differentials between stocks in our highest- and lowest-quintile portfolios (i.e., high–low spreads) than when either signed total jump or signed large jump variation is sorted on. It is shown that the benefit of signed small jump variation investing is driven by stock selection within an industry, rather than industry bets. Investors prefer stocks with a high probability of having positive jumps, but they also tend to overweight safer industries. Also, consistent with the findings in Scaillet et al. (2018), upside (downside) jump variation negatively (positively) predicts future returns. However, signed (large/small/total) jump variation has stronger predictive power than both upside and downside jump variation. One reason large and small (signed) jump variation have differing marginal predictive contents is that the predictive content of signed large jump variation is negligible when controlling for either signed total jump variation or realized skewness. By contrast, signed small jump variation has unique information for predicting future returns, even when controlling for these variables. By analyzing earnings announcement surprises, we find that large jumps are closely associated with “big” news. However, while such news-related information is embedded in large jump variation, the information is generally short-lived, and dissipates too quickly to provide marginal predictive content for subsequent weekly returns. Finally, we find that small jumps are more likely to be diversified away than large jumps and tend to be more closely associated with idiosyncratic risks. This indicates that small jumps are more likely to be driven by liquidity conditions and trading activity.

An Improved Artificial Bee Colony Algorithm Based on Elite Strategy and Dimension Learning

Artificial bee colony is a powerful optimization method, which has strong search abilities to solve many optimization problems. However, some studies proved that ABC has poor exploitation abilities in complex optimization problems. To overcome this issue, an improved ABC variant based on elite strategy and dimension learning (called ABC-ESDL) is proposed in this paper. The elite strategy selects better solutions to accelerate the search of ABC. The dimension learning uses the differences between two random dimensions to generate a large jump. In the experiments, a classical benchmark set and the 2013 IEEE Congress on Evolutionary (CEC 2013) benchmark set are tested. Computational results show the proposed ABC-ESDL achieves more accurate solutions than ABC and five other improved ABC variants.

Importance sampling of heavy-tailed iterated random functions

We consider the stationary solutionZof the Markov chain {Zn}n∈ℕdefined byZn+1=ψn+1(Zn), where {ψn}n∈ℕis a sequence of independent and identically distributed random Lipschitz functions. We estimate the probability of the event {Z>x} whenxis large, and develop a state-dependent importance sampling estimator under a set of assumptions on ψnsuch that, for largex, the event {Z>x} is governed by a single large jump. Under natural conditions, we show that our estimator is strongly efficient. Special attention is paid to a class of perpetuities with heavy tails.

Kinetic and Electromyographic Subphase Characteristics With Relation to Countermovement Vertical Jump Performance

This study sought to identify kinetic and electromyographic subphase characteristics distinguishing good from poor jumpers during countermovement vertical jumps (CMVJs), as defined by the reactive strength index (RSI, CMVJ displacement divided by jump time; cutoff = 0.46 m·s−1). A total of 15 men (1.8 [0.6] m, 84.5 [8.5] kg, 24 [2] y) were stratified by RSI into good (n = 6; RSI = 0.57 [0.07] m·s−1) and poor (n = 9; RSI = 0.39 [0.06] m·s−1) performance groups. The following variables were compared between groups using independentttests (α = .05) and Cohen’sdeffect sizes (d ≥ 0.8, large): jump height, propulsive impulse, eccentric rate of force development, and jump time, unloading, eccentric, and concentric subphase times, and average electromyographic amplitudes of 8 lower extremity muscles. Compared with the poor RSI group, the good RSI group exhibited a greater, though not statistically different CMVJ displacement (d = 1.07,P = .06). In addition, the good RSI group exhibited a significantly greater propulsive impulse (P = .04,d = 1.27) and a significantly more rapid unloading subphase (P = .04,d = 1.08). No other significant or noteworthy differences were detected. Enhanced RSI appears related to a quicker unloading phase, allowing a greater portion of the total jumping phase to be utilized generating positive net force. Poor jumpers should aim to use unloading strategies that emphasize quickness to enhance RSI during CMVJ.

Income Volatility and the PSID: Past Research and New Results

The PSID has major advantages for studying income volatility and, because of this, research using it has been responsible for major improvements in the methodology of studying income volatility. Its research on calendar trends finds a reasonably consistent pattern for phased but rising male earnings volatility since 1970. Female earnings volatility has declined and household income volatility has risen. Some other datasets find similar patterns but others do not, suggesting the need for more research. A new earnings volatility model is estimated on PSID men through 2014, showing similar patterns but with a large jump during the Great Recession.

Restricted Additive Schwarz Preconditioner for Elliptic Equations with Jump Coefficients

This paper provides a proof of robustness of the restricted additive Schwarz preconditioner with harmonic overlap (RASHO) for the second order elliptic problems with jump coefficients. By analyzing the eigenvalue distribution of the RASHO preconditioner, we prove that the convergence rate of preconditioned conjugate gradient method with RASHO preconditioner is uniform with respect to the large jump and meshsize.

Planetary period oscillations in Saturn's magnetosphere: comments on the relation between post-equinox periods determined from magnetic field and SKR emission data

We discuss the properties of Saturn planetary period oscillations (PPOs) deduced from analysis of Saturn kilometric radiation (SKR) modulations by Fischer et al. (2014), and from prior analysis of magnetic field oscillations data by Andrews et al. (2012) and Provan et al. (2013), with emphasis on the post-equinox interval from early 2010 to early 2013. Fischer et al. (2014) characterize this interval as showing single phase-locked periods in the northern and southern SKR modulations observed in polarization-separated data, while the magnetic data generally show the presence of separated dual periods, northern remaining shorter than southern. We show that the single SKR period corresponds to the southern magnetic period early in 2010, segues into the northern period in late 2010, and returns to the southern period in mid-2012, approximately in line with changes in the dominant magnetic oscillation. An exception occurs in mid-February to late August 2011 when two periods are again discerned in SKR data, in good agreement with the ongoing dual periods in the magnetic data. Fischer et al. (2014) discuss this change in terms of a large jump in the southern SKR period related to the Great White Spot storm, which the magnetic data show is primarily due instead to a reappearance in the SKR data of the ongoing southern modulation in a transitory interval of resumed southern dominance. In the earlier interval from early April 2010 to mid-February 2011 when Fischer et al. (2014) deduce single phase-locked periods, we show unequivocal evidence in the magnetic data for the presence of separated dual oscillations of approximately equal amplitude. We suggest that the apparent single SKR periods result from a previously reported phenomenon in which modulations associated with one hemisphere appear in polarization-separated data associated with the other. In the following interval, mid-August 2011 to early April 2012, when Fischer et al. (2014) again report phase-locked northern and southern oscillations, no ongoing southern oscillation of separate period is discerned in the magnetic data. However, the magnetic amplitude data show that if a phase-locked southern oscillation is indeed present, its amplitude must be less than ~ 5–10 % of the northern oscillation.