The backtracking survey propagation algorithm for solving random K-SAT problems

Discrete combinatorial optimization has a central role in many scientific disciplines, however, for hard problems we lack linear time algorithms that would allow us to solve very large instances. Moreover, it is still unclear what are the key features that make a discrete combinatorial optimization problem hard to solve. Here we study random K-satisfiability problems with $K=3,4$, which are known to be very hard close to the SAT-UNSAT threshold, where problems stop having solutions. We show that the backtracking survey propagation algorithm, in a time practically linear in the problem size, is able to find solutions very close to the threshold, in a region unreachable by any other algorithm. All solutions found have no frozen variables, thus supporting the conjecture that only unfrozen solutions can be found in linear time, and that a problem becomes impossible to solve in linear time when all solutions contain frozen variables.Comment: 11 pages, 10 figures. v2: data largely improved and manuscript rewritte

Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays

Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an essential task in sonar, radar, acoustics, biomedical and multimedia applications. Many state of the art wide-band DOA estimators coherently process frequency binned array outputs by approximate Maximum Likelihood, Weighted Subspace Fitting or focusing techniques. This paper shows that bin signals obtained by filter-bank approaches do not obey the finite rank narrow-band array model, because spectral leakage and the change of the array response with frequency within the bin create \emph{ghost sources} dependent on the particular realization of the source process. Therefore, existing DOA estimators based on binning cannot claim consistency even with the perfect knowledge of the array response. In this work, a more realistic array model with a finite length of the sensor impulse responses is assumed, which still has finite rank under a space-time formulation. It is shown that signal subspaces at arbitrary frequencies can be consistently recovered under mild conditions by applying MUSIC-type (ST-MUSIC) estimators to the dominant eigenvectors of the wide-band space-time sensor cross-correlation matrix. A novel Maximum Likelihood based ST-MUSIC subspace estimate is developed in order to recover consistency. The number of sources active at each frequency are estimated by Information Theoretic Criteria. The sample ST-MUSIC subspaces can be fed to any subspace fitting DOA estimator at single or multiple frequencies. Simulations confirm that the new technique clearly outperforms binning approaches at sufficiently high signal to noise ratio, when model mismatches exceed the noise floor.Comment: 15 pages, 10 figures. Accepted in a revised form by the IEEE Trans. on Signal Processing on 12 February 1918. @IEEE201

Duplication of modules facilitates the evolution of functional specialization

The evolution of simulated robots with three different architectures is studied. We compared a non-modular feed forward network, a hardwired modular and a duplication-based modular motor control network. We conclude that both modular architectures outperform the non-modular architecture, both in terms of rate of adaptation as well as the level of adaptation achieved. The main difference between the hardwired and duplication-based modular architectures is that in the latter the modules reached a much higher degree of functional specialization of their motor control units with regard to high level behavioral functions. The hardwired architectures reach the same level of performance, but have a more distributed assignment of functional tasks to the motor control units. We conclude that the mechanism through which functional specialization is achieved is similar to the mechanism proposed for the evolution of duplicated genes. It is found that the duplication of multifunctional modules first leads to a change in the regulation of the module, leading to a differentiation of the functional context in which the module is used. Then the module adapts to the new functional context. After this second step the system is locked into a functionally specialized state. We suggest that functional specialization may be an evolutionary absorption state

What does it take to evolve behaviorally complex organisms?

What genotypic features explain the evolvability of organisms that have to accomplish many different tasks? The genotype of behaviorally complex organisms may be more likely to encode modular neural architectures because neural modules dedicated to distinct tasks avoid neural interference, i.e., the arrival of conflicting messages for changing the value of connection weights during learning. However, if the connection weights for the various modules are genetically inherited, this raises the problem of genetic linkage: favorable mutations may fall on one portion of the genotype encoding one neural module and unfavorable mutations on another portion encoding another module. We show that this can prevent the genotype from reaching an adaptive optimum. This effect is different from other linkage effects described in the literature and we argue that it represents a new class of genetic constraints. Using simulations we show that sexual reproduction can alleviate the problem of genetic linkage by recombining separate modules all of which incorporate either favorable or unfavorable mutations. We speculate that this effect may contribute to the taxonomic prevalence of sexual reproduction among higher organisms. In addition to sexual recombination, the problem of genetic linkage for behaviorally complex organisms may be mitigated by entrusting evolution with the task of finding appropriate modular architectures and learning with the task of finding the appropriate connection weights for these architectures

Profit Shifting by Debt Financing in Europe

This article aims at analyzing the link between subsidiaries’ capital structure and taxation in Europe. First we introduce a trade-off model, which studies a MNCs’ financial strategy and shows how debt policy allows multinational groups to shift profits from low-tax to high-tax jurisdictions. By letting the MNC choose both leverage and the percentage of profit shifting, we depart from the relevant literature which has mainly focused on the latter. Using the AMADEUS dataset we show that: i) subsidiaries’ leverage increases with the statutory tax rate, levied in the country where it operates; ii) this positive effect is lower, the higher the parent company tax rate is. Furthermore, an increase in the parent company’s tax rate is estimated to raise its subsidiaries’ leverage.capital structure, default, multinationals, profit shifting, taxation

The Human MDM2 Oncoprotein Increases the Transcriptional Activity and the Protein Level of the p53 Homolog p63

Genetic alteration of the p53 tumor suppressor gene, which monitors DNA damage and operates cell cycle checkpoints, is a major factor in the development of human malignancies. The p53 protein belongs to a family that also includes two structurally related proteins, p63 and p73. Although all three proteins share similar transcriptional functions and antiproliferative effects, each of them appears to play a distinct role in development and tumor suppression. One of the principal regulators of p53 activity is the MDM2 protein. The interaction of MDM2 with p53 inhibits p53 transcriptional activity and targets p53 for ubiquitin-dependent degradation. The ability of MDM2 to inhibit p53 functions is antagonized by the ARF oncosuppressor protein. We show here that like p53, the p63alpha and p63gamma isoforms are able to associate with human MDM2 (HDM2). Overexpression of HDM2 increased the steady-state level of intracellular p63 and enhanced its transcriptional activity. Both effects appeared to be counteracted by ARF coexpression. These data indicate that p63 can be activated by HDM2 under conditions in which p53 is inhibited. Therefore, HDM2 expression could support p63-specific transcriptional functions on a common set of genes, keeping interference by p53 at a minimum

Characterization of the most frequent ATP7B mutation causing Wilson disease in hepatocytes from patient induced pluripotent stem cells

H1069Q substitution represents the most frequent mutation of the copper transporter ATP7B causing Wilson disease in Caucasian population. ATP7B localizes to the Golgi complex in hepatocytes but moves in response to copper overload to the endo-lysosomal compartment to support copper excretion via bile canaliculi. In heterologous or hepatoma-derived cell lines, overexpressed ATP7B-H1069Q is strongly retained in the ER and fails to move to the post-Golgi sites, resulting in toxic copper accumulation. However, this pathogenic mechanism has never been tested in patients' hepatocytes, while animal models recapitulating this form of WD are still lacking. To reach this goal, we have reprogrammed skin fibroblasts of homozygous ATP7B-H1069Q patients into induced pluripotent stem cells and differentiated them into hepatocyte-like cells. Surprisingly, in HLCs we found one third of ATP7B-H1069Q localized in the Golgi complex and able to move to the endo-lysosomal compartment upon copper stimulation. However, despite normal mRNA levels, the expression of the mutant protein was only 20% compared to the control because of endoplasmic reticulum-associated degradation. These results pinpoint rapid degradation as the major cause for loss of ATP7B function in H1069Q patients, and thus as the primary target for designing therapeutic strategies to rescue ATP7B-H1069Q function