Enhancing IEEE 802.11n WLANs using group-orthogonal code-division multiplex

The definition of the next generation of wireless networks is well under way within the IEEE 802.11 High Throughput Task Group committee. The resulting standard, to be called IEEE 802.11n, is expected to be a backward-compatible evolution of the successful IEEE 802.11a/g systems also based on multicarrier techniques. It can be anticipated that 802.11n systems will outperform its predecessors in terms of transmission rate and/or performance, mainly, due to the use of multiple antennae technology for transmission and reception. In this paper we propose to incorporate group-orthogonal (GO) code division multiplex (CDM) into the IEEE 802.11n specifications to further enhance its performance. It is shown how GO-CDM can take full advantage of the diversity offered by the multiple antennae and multicarrier transmission by using an iterative maximum likelihood (ML) joint detector. Furthermore, the use of GO-CDM does not compromise the backward compatibility with legacy systems.     

Naloxone-induced opiate withdrawal produces long-lasting and context-independent changes in aggressive and social behaviors of postdependent male mice.

The purpose of this study was to determine whether an environment associated with naloxone-induced morphine withdrawal affects aggressive or social behaviors in postdependent mice. Morphine-dependent or saline-treated mice received 3 naloxone injections in 1 of 2 different environments (A or B); 15 days afterward, when the mice were completely drug free, an aggression test was carried out in Environment A. All the mice suffering morphine withdrawal showed a significant increase in aggression, irrespective of the environment in which the withdrawal took place. In these conditions, the impact of morphine dependence and the 3 induced withdrawals was so profound that the environment could not be discriminative. In addition, modifications in the behavioral profile of postdependent mice that suffered only spontaneous withdrawal were long-lasting, with the mice carrying out more attacks during social investigation without presenting threat postures. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Misfit Dislocation Core Phase in Complex Oxide Heteroepitaxy

Misfit dislocations form self‐organized nanoscale linear defects exhibiting their own distinct structural, chemical, and physical properties which, particularly in complex oxides, hold a strong potential for the development of nanodevices. However, the transformation of such defects from passive into potentially active functional elements necessitates a deep understanding of the particular mechanisms governing their formation. Here, different atomic resolution imaging and spectroscopic techniques are combined to determine the complex structure of misfit dislocations in the perovskite type La_0.67Sr_0.33MnO₃/LaAlO₃ heteroepitaxial system. It is found that while the position of the film–substrate interface is blurred by cation intermixing, oxygen vacancies selectively accumulate at the tensile region of the dislocation strain field. Such accumulation of vacancies is accompanied by the reduction of manganese cations in the same area, inducing chemical expansion effects, which partly accommodate the dislocation strain. The formation of oxygen vacancies is only partially electrically compensated and results in a positive net charge q ≈ +0.3 ± 0.1 localized in the tensile region of the dislocation, while the compressive region remains neutral. The results highlight a prototypical core model for perovskite‐based heteroepitaxial systems and offer insights for predictive manipulation of misfit dislocation properties.     

Exploiting multivalued knowledge in variable selection heuristics for SAT solvers

We show that we can design and implement extremely efficient variable selection heuristics for SAT solvers by identifying, in Boolean clause databases, sets of Boolean variables that model the same multivalued variable and then exploiting that structural information. In particular, we define novel variable selection heuristics for two of the most competitive existing SAT solvers: Chaff, a solver based on look-back techniques, and Satz, a solver based on look-ahead techniques. Our heuristics give priority to Boolean variables that belong to sets of variables that model multivalued variables with minimum domain size in a given state of the search process. The empirical investigation conducted to evaluate the new heuristics provides experimental evidence that identifying multivalued knowledge in Boolean clause databases and using variable selection heuristics that exploit that knowledge leads to large performance improvements.      

Pharmacological Inhibition of IKK to Tackle Latency and Hyperinflammation in Chronic HIV-1 Infection

HIV latent infection may be associated with disrupted viral RNA sensing, interferon (IFN) signaling, and/or IFN stimulating genes (ISG) activation. Here, we evaluated the use of compounds selectively targeting at the inhibitor of nuclear factor-κB (IκB) kinase (IKK) complex subunits and related kinases (TBK1) as a novel pathway to reverse HIV-1 latency in latently infected non-clonal lymphoid and myeloid cell in vitro models. IKK inhibitors (IKKis) triggered up to a 1.8-fold increase in HIV reactivation in both, myeloid and lymphoid cell models. The best-in-class IKKis, targeting TBK-1 (MRT67307) and IKKβ (TCPA-1) respectively, were also able to significantly induce viral reactivation in CD4+ T cells from people living with HIV (PLWH) ex vivo. More importantly, although none of the compounds tested showed antiviral activity, the combination of the distinct IKKis with ART did not affect the latency reactivation nor blockade of HIV infection by ART. Finally, as expected, IKKis did not upregulate cell activation markers in primary lymphocytes and innate immune signaling was blocked, resulting in downregulation of inflammatory cytokines. Overall, our results support a dual role of IKKis as immune modulators being able to tackle the HIV latent reservoir in lymphoid and myeloid cellular models and putatively control the hyperinflammatory responses in chronic HIV-1 infection.     

Modeling the relative GHG emissions of conventional and shale gas production

Recent reports show growing reserves of unconventional gas are available and that there is an appetite from policy makers, industry, and others to better understand the GHG impact of exploiting reserves such as shale gas. There is little publicly available data comparing unconventional and conventional gas production. Existing studies rely on national inventories, but it is not generally possible to separate emissions from unconventional and conventional sources within these totals. Even if unconventional and conventional sites had been listed separately, it would not be possible to eliminate site-specific factors to compare gas production methods on an equal footing. To address this difficulty, the emissions of gas production have instead been modeled. In this way, parameters common to both methods of production can be held constant, while allowing those parameters which differentiate unconventional gas and conventional gas production to vary. The results are placed into the context of power generation, to give a ″well-to-wire″ (WtW) intensity. It was estimated that shale gas typically has a WtW emissions intensity about 1.8-2.4% higher than conventional gas, arising mainly from higher methane releases in well completion. Even using extreme assumptions, it was found that WtW emissions from shale gas need be no more than 15% higher than conventional gas if flaring or recovery measures are used. In all cases considered, the WtW emissions of shale gas powergen are significantly lower than those of coal.     

Resolution-based lower bounds in MaxSAT

The lower bound (LB) implemented in branch and bound MaxSAT solvers is decisive for obtaining a competitive solver. In modern solvers like MaxSatz and MiniMaxSat, the LB relies on the cooperation of the underestimation and inference components. Actually, the underestimation component of some solvers guides the application of the inference component when a conflict is reached and certain structures are found. In this paper we analyze algorithmic and logical aspects of the underestimation components that have been implemented in MaxSatz during its evolution. From an algorithmic point of view, we define novel strategies for selecting unit clauses in UP (the underestimation of LB in UP is the number of independent inconsistent subformulas detected using unit propagation), the extension of UP with failed literal detection, and a clever heuristic for guiding the application of MaxSAT resolution when UP augmented with failed literal detection is applied in the presence of cycles structures. From a logical point of view, we prove that the inconsistent subformulas detected by UP are minimally unsatisfiable, but this property does not hold if failed literal detection is added. In the presence of cycle structures in conflicts detected by UP augmented with failed literal detection, we prove that the application of MaxSAT resolution produces smaller inconsistent subformulas and, besides, generates additional clauses that may be used to improve the LB. The conducted empirical investigation indicates that the LB techniques described in this paper lead to better quality LBs.     

A Unified Approach to Dynamic Length Algorithms for Adaptive Linear Equalizers

The number of taps is an important factor which affects nearly all the performance and complexity measures of adaptive equalizers. Recently, dynamic length algorithms for the adaptive finite impulse response (FIR) filters have attracted considerable attention and several methods have been proposed. Nevertheless, the relationship among these techniques is still unclear which makes the performance comparison remaining difficult. In this paper, a unified explanation of these techniques is presented which summarizes all proposed algorithms and provides a platform for their performance comparison. Moreover, a new type of dynamic length algorithms, the varying threshold dynamic length algorithm (VT-DLA) is proposed. Simulation results show that the performance of the new algorithm outperforms that of existing algorithms