Cryptographic and Physical Zero-Knowledge Proof Systems for Solutions of Sudoku Puzzles

We consider cryptographic and physical zero-knowledge proof schemes for Sudoku, a popular combinatorial puzzle. We discuss methods that allow one party, the prover, to convince another party, the verifier, that the prover has solved a Sudoku puzzle, without revealing the solution to the verifier. The question of interest is how a prover can show: (i) that there is a solution to the given puzzle, and (ii) that he knows the solution, while not giving away any information about the solution to the verifier. In this paper we consider several protocols that achieve these goals. Broadly speaking, the protocols are either cryptographic or physical. By a cryptographic protocol we mean one in the usual model found in the foundations of cryptography literature. In this model, two machines exchange messages, and the security of the protocol relies on computational hardness. By a physical protocol we mean one that is implementable by humans using common objects, and preferably without the aid of computers. In particular, our physical protocols utilize items such as scratch-off cards, similar to those used in lotteries, or even just simple playing cards. The cryptographic protocols are direct and efficient, and do not involve a reduction to other problems. The physical protocols are meant to be understood by “lay-people” and implementable without the use of computers. Research of R. Gradwohl was supported by US-Israel Binational Science Foundation Grant 2002246. Research of M. Naor was supported in part by a grant from the Israel Science Foundation. Research of B. Pinkas was supported in part by the Israel Science Foundation (grant number 860/06). Research of G.N. Rothblum was supported by NSF grant CNS-0430450 and NSF grant CFF-0635297.     

Molecular recognition in the sphingosine 1-phosphate receptor family

Computational modeling and its application in ligand screening and ligand receptor interaction studies play important roles in structure-based drug design. A series of sphingosine 1-phosphate (S1P) receptor ligands with varying potencies and receptor selectivities were docked into homology models of the S1P(1-5) receptors. These studies provided molecular insights into pharmacological trends both across the receptor family as well as at single receptors. This study identifies ligand recognition features that generalize across the S1P receptor family, features unique to the S1P(4) and S1P(5) receptors, and suggests significant structural differences of the S1P(2) receptor. Docking results reveal a previously unknown sulfur-aromatic interaction between the S1P(4) C5.44 sulfur atom and the phenyl ring of benzimidazole as well as pi-pi interaction between F3.33 of S1P(1,4,5) and aromatic ligands. The findings not only confirm the importance of a cation-pi interaction between W4.64 and the ammonium of S1P at S1P(4) but also predict the same interaction at S1P(5). S1P receptor models are validated for pharmacophore development including database mining and new ligand discovery and serve as tools for ligand optimization to improve potency and selectivity.     

Electrodeposition of rhenium-nickel alloys from aqueous solutions

Rhenium-nickel alloys were deposited on copper substrates in a small three-electrode cell, under galvanostatic conditions. The bath solution consisted of ammonium perrhenate, citric acid and nickel sulfamate. The effects of bath composition and deposition time were studied. The Faradaic efficiency (FE) and partial deposition current densities were calculated based on mass gain and elemental analysis using energy dispersive spectroscopy. The surface morphology was characterized by scanning electron microscopy. The thickness of the coating was measured on metallographic cross-sections. The results are discussed with emphasis on routes to increase the Faradaic efficiency and rhenium content in the coating. A plausible mechanism for the electrodeposition of rhenium-nickel alloys is presented.     

Sphingosine 1-phosphate pKa and binding constants: intramolecular and intermolecular influences

The dissociation constant for an ionizable ligand binding to a receptor is dependent on its charge and therefore on its environmentally-influenced pKa value. The pKa values of sphingosine 1-phosphate (S1P) were studied computationally in the context of the wild type S1P1 receptor and the following mutants: E3.29Q, E3.29A, and K5.38A. Calculated pKa values indicate that S1P binds to S1P1 and its site mutants with a total charge of -1, including a +1 charge on the ammonium group and a -2 charge on the phosphate group. The dissociation constant of S1P binding to these receptors was studied as well. The models of wild type and mutant proteins originated from an active receptor model that was developed previously. We used ab initio RHF/6-31+G(d) to optimize our models in aqueous solution, where the solvation energy derivatives are represented by conductor-like polarizable continuum model (C-PCM) and integral equation formalism polarizable continuum model (IEF-PCM). Calculation of the dissociation constant for each mutant was determined by reference to the experimental dissociation constant of the wild type receptor. The computed dissociation constants of the E3.29Q and E3.29A mutants are three to five orders of magnitude higher than those for the wild type receptor and K5.38A mutant, indicating vital contacts between the S1P phosphate group and the carboxylate group of E3.29. Computational dissociation constants for K5.38A, E3.29A, and E3.29Q mutants were compared with experimentally determined binding and activation data. No measurable binding of S1P to the E3.29A and E3.29Q mutants was observed, supporting the critical contacts observed computationally. These results validate the quantitative accuracy of the model.     

Dynamic expression changes in vivo of adhesion and costimulatory molecules determine load and pattern of lymphoma liver metastasis

Although intradermal primary tumor growth and spontaneous liver metastasis of ESbL-lacZ lymphoma in syngeneic DBA/2 mice are progressive and malignant, they are characterized by a transient plateau period with a constant tumor diameter and a low number of metastasized cells in the liver. This period, which was shown to be immune dependent, was followed by a second expansion phase characterized by a preferential localization of tumor cells in the periportal areas of liver lobules (mosaic phenotype). To elucidate possible mechanisms leading to the plateau period as well as for the mosaic-like metastasis pattern, we investigated, using flow cytometry analysis, alterations in costimulatory and adhesion molecule expression in liver sinusoidal cells as well as in tumor cells isolated directly ex vivo throughout the kinetics of metastasis. In tumor and sinusoidal cells, we found up-regulation in the expression of MHC class II and B7 molecules during the plateau period. These molecules, which facilitate cell-mediated immune responses, were again down-regulated during the final exponential tumor growth and metastasis. In the final expansion phase, in which the mosaic phenotype of liver metastasis is seen, we detected a significant increase of leukocyte function-associated antigen-1/intercellular adhesion molecule-1 expression in both tumor and sinusoidal cells, suggesting tumor cell-sinusoidal cell interactions. vascular cell adhesion molecule-1/very late activated antigen-4 did not show any modification during the whole metastatic process. In vivo application of monoclonal antibodies directed to leukocyte function-associated antigen-1 and intercellular adhesion molecule-1 appeared to block the spread of metastasis, while no effect was seen with monoclonal antibodies directed to vascular cell adhesion molecule-1 and very late activated antigen-4. This study reveals in situ expression changes of cell surface molecules in tumor and host cells during metastasis. The changes seen during the plateau phase and during the second expansion phase differ, suggesting associations with mechanisms of immune control and tumor immune evasion, respectively.     

Efficient trace and revoke schemes

Our goal is to design encryption schemes for mass distribution of data , which enable to (1) deter users from leaking their personal keys, (2) trace the identities of users whose keys were used to construct illegal decryption devices, and (3) revoke these keys as to render the devices dysfunctional. We start by designing an efficient revocation scheme, based on secret sharing. It can remove up to t parties, is secure against coalitions of up to t users, and is more efficient than previous schemes with the same properties. We then show how to enhance the revocation scheme with traitor tracing and self-enforcement properties. More precisely, how to construct schemes such that (1) each user’s personal key contains some sensitive information of that user (e.g., the user’s credit card number), in order to make users reluctant to disclose their keys. (2) An illegal decryption device discloses the identity of users that contributed keys to construct the device. And, (3) it is possible to revoke the keys of corrupt users. For the last point, it is important to be able to do so without publicly disclosing the sensitive information.     

Differential activation of protein kinase C delta and epsilon gene expression by gonadotropin-releasing hormone in alphaT3-1 cells. Autoregulation by protein kinase C

The effect of gonadotropin-releasing hormone (GnRH) upon protein kinase C (PKC) delta and PKCepsilon gene expression was investigated in the gonadotroph-derived alphaT3-1 cell line. Stimulation of the cells with a stable analog [D-Trp6]GnRH (GnRH-A) resulted in a rapid elevation of PKCepsilon mRNA levels (1 h), while PKCdelta mRNA levels were elevated only after 24 h of incubation. The rapid elevation of PKCepsilon mRNA by GnRH-A was blocked by pretreatment with a GnRH antagonist or actinomycin D. The PKC activator 12-O-tetradecanoylphorbol-13-acetate (TPA), but not the Ca2+ ionophore ionomycin, mimicked the rapid effect of GnRH-A upon PKCepsilon mRNA elevation. Additionally, the rapid stimulatory effect of GnRH-A was blocked by the selective PKC inhibitor GF109203X, by TPA-mediated down-regulation of endogenous PKC, or by Ca2+ removal. Interestingly, serum-starvation (24 h) advanced the stimulation of PKCdelta mRNA levels by GnRH-A and the effect could be detected at 1 h of incubation. The rapid effect of GnRH-A upon PKCdelta mRNA levels in serum-starved cells was mimicked by TPA, but not by ionomycin, and was abolished by down-regulation of PKC or by Ca2+ removal. Preactivation of alphaT3-1 cells with GnRH-A for 1 h followed by removal of ligand and serum resulted in elevation of PKCdelta mRNA levels after 24 h of incubation. Western blot analysis revealed that GnRH-A and TPA stimulated (within 5 min) the activation and some degradation of PKCdelta and PKCepsilon. We conclude that Ca2+ and PKC are involved in GnRH-A elevation of PKCdelta and PKCepsilon mRNA levels, with Ca2+ being necessary but not sufficient, while PKC is both necessary and sufficient to mediate the GnRH-A response. A serum factor masks PKCdelta but not PKCepsilon mRNA elevation by GnRH-A, and its removal exposes preactivation of PKCdelta mRNA by GnRH-A which can be memorized for 24 h. PKCdelta and PKCepsilon gene expression evoked by GnRH-A is autoregulated by PKC, and both isotypes might participate in the neurohormone action.     

An efficient parallel algorithm for computing a large independent set in a planar graph

Let α(G) denote the independence number of a graphG, that is the maximum number of pairwise independent vertices inG. We present a parallel algorithm that computes in a planar graphG = (V, E), an independent set \(I \subseteq V\) such that ¦I¦≥ α (G)/2. The algorithm runs in timeOlog² n) and requires a linear number of processors. This is achieved by denning a new set of reductions that can be executed “locally” and simultaneously; furthermore, it is shown that a constant fraction of the vertices in the graph are reducible. This is the best known approximation scheme when the number of processors available is linear; parallel implementation of known sequential algorithms requires many more processors.     

Parametric optimization of sequence alignment

Theoptimal alignment or theweighted minimum edit distance between two DNA or amino acid sequences for a given set of weights is computed by classical dynamic programming techniques, and is widely used in molecular biology. However, in DNA and amino acid sequences there is considerable disagreement about how to weight matches, mismatches, insertions/deletions (indels or spaces), and gaps.Parametric sequence alignment is the problem of computing the optimal-valued alignment between two sequences as afunction of variable weights for matches, mismatches, spaces, and gaps. The goal is to partition the parameter space into regions (which are necessarily convex) such that in each region one alignment is optimal throughout and such that the regions are maximal for this property. In this paper we are primarily concerned with the structure of this convex decomposition, and secondarily with the complexity of computing the decomposition. The most striking results are the following: For the special case where only matches, mismatches, and spaces are counted, and where spaces are counted throughout the alignment, we show that the decomposition is surprisingly simple: all regions are infinite; there are at most n^2/3 regions; the lines that bound the regions are all of the form =c + (c + 0.5); and the entire decomposition can be found inO(knm) time, wherek is the actual number of regions, andn相似文献