Two experiments tested the effect of co-occurrence of a target object with affective stimuli on automatic evaluation of the target when the relation between the target and the affective stimuli suggests that they have opposite valence. Participants learned about targets that ended an unpleasant noise or a pleasant music. The valence of such targets is opposite to the valence of the affective stimuli that co-occur with them. Participants reported preference for targets that ended noise over targets that ended music, but automatic evaluation measures revealed the opposite preference. This suggests that automatic evaluation is sensitive to co-occurrence between stimuli more than to the relation between the stimuli, and that relational information has a stronger influence on deliberate evaluation than on automatic evaluation. These conclusions support the Associative-Propositional Evaluation model (Gawronski & Bodenhausen, 2006), and add evidence regarding the sensitivity of the Evaluative-Conditioning effect to relational information.

Abstract. We present the first universally verifiable voting scheme that can be based on a general assumption (existence of a non-interactive commitment scheme). Our scheme is also the first receipt-free scheme to give "everlasting privacy" for votes: even a computationally unbounded party does not gain any information about individual votes (other than what can be inferred from the final tally).Our voting protocols are designed to be used in a "traditional" setting, in which voters cast their ballots in a private polling booth (which we model as an untappable channel between the voter and the tallying authority). Following in the footsteps of Chaum and Neff [7,16], our protocol ensures that the integrity of an election cannot be compromised even if the computers running it are all corrupt (although ballot secrecy may be violated in this case).We give a generic voting protocol which we prove to be secure in the Universal Composability model, given that the underlying commitment is universally composable. We also propose a concrete implementation, based on the hardness of discrete log, that is more efficient.

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We address one of the foundational problems in cryptography: the bias of coin-flipping protocols. Coin-flipping protocols allow mutually distrustful parties to generate a common unbiased random bit, guaranteeing that even if one of the parties is malicious, it cannot significantly bias the output of the honest party. A classical result by Cleve [STOC '86] showed that for any twoparty r-round coin-flipping protocol there exists an efficient adversary that can bias the output of the honest party by Ω(1/r). However, the best previously known protocol only guarantees O(1/ √ r) bias, and the question of whether Cleve's bound is tight has remained open for more than twenty years. In this paper we establish the optimal trade-off between the round complexity and the bias of two-party coin-flipping protocols. Under standard assumptions, we show that Cleve's lower bound is tight: we construct an r-round protocol with bias O(1/r).