906 resultados para New Space Vector Modulation
Resumo:
Error-correcting codes and matroids have been widely used in the study of ordinary secret sharing schemes. In this paper, the connections between codes, matroids, and a special class of secret sharing schemes, namely, multiplicative linear secret sharing schemes (LSSSs), are studied. Such schemes are known to enable multiparty computation protocols secure against general (nonthreshold) adversaries.Two open problems related to the complexity of multiplicative LSSSs are considered in this paper. The first one deals with strongly multiplicative LSSSs. As opposed to the case of multiplicative LSSSs, it is not known whether there is an efficient method to transform an LSSS into a strongly multiplicative LSSS for the same access structure with a polynomial increase of the complexity. A property of strongly multiplicative LSSSs that could be useful in solving this problem is proved. Namely, using a suitable generalization of the well-known Berlekamp–Welch decoder, it is shown that all strongly multiplicative LSSSs enable efficient reconstruction of a shared secret in the presence of malicious faults. The second one is to characterize the access structures of ideal multiplicative LSSSs. Specifically, the considered open problem is to determine whether all self-dual vector space access structures are in this situation. By the aforementioned connection, this in fact constitutes an open problem about matroid theory, since it can be restated in terms of representability of identically self-dual matroids by self-dual codes. A new concept is introduced, the flat-partition, that provides a useful classification of identically self-dual matroids. Uniform identically self-dual matroids, which are known to be representable by self-dual codes, form one of the classes. It is proved that this property also holds for the family of matroids that, in a natural way, is the next class in the above classification: the identically self-dual bipartite matroids.
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We focus on full-rate, fast-decodable space–time block codes (STBCs) for 2 x 2 and 4 x 2 multiple-input multiple-output (MIMO) transmission. We first derive conditions and design criteria for reduced-complexity maximum-likelihood (ML) decodable 2 x 2 STBCs, and we apply them to two families of codes that were recently discovered. Next, we derive a novel reduced-complexity 4 x 2 STBC, and show that it outperforms all previously known codes with certain constellations.
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The 2×2 MIMO profiles included in Mobile WiMAX specifications are Alamouti’s space-time code (STC) fortransmit diversity and spatial multiplexing (SM). The former hasfull diversity and the latter has full rate, but neither of them hasboth of these desired features. An alternative 2×2 STC, which is both full rate and full diversity, is the Golden code. It is the best known 2×2 STC, but it has a high decoding complexity. Recently, the attention was turned to the decoder complexity, this issue wasincluded in the STC design criteria, and different STCs wereproposed. In this paper, we first present a full-rate full-diversity2×2 STC design leading to substantially lower complexity ofthe optimum detector compared to the Golden code with only a slight performance loss. We provide the general optimized form of this STC and show that this scheme achieves the diversitymultiplexing frontier for square QAM signal constellations. Then, we present a variant of the proposed STC, which provides a further decrease in the detection complexity with a rate reduction of 25% and show that this provides an interesting trade-off between the Alamouti scheme and SM.
Resumo:
Multiple-input multiple-output (MIMO) techniques have become an essential part of broadband wireless communications systems. For example, the recently developed IEEE 802.16e specifications for broadband wireless access include three MIMOprofiles employing 2×2 space-time codes (STCs), and two of these MIMO schemes are mandatory on the downlink of Mobile WiMAX systems. One of these has full rate, and the other has full diversity, but neither of them has both of the desired features. The third profile, namely, Matrix C, which is not mandatory, is both a full rate and a full diversity code, but it has a high decoder complexity. Recently, the attention was turned to the decodercomplexity issue and including this in the design criteria, several full-rate STCs were proposed as alternatives to Matrix C. In this paper, we review these different alternatives and compare them to Matrix C in terms of performances and the correspondingreceiver complexities.
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Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.
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AIM: To prospectively study the intraocular pressure (IOP) lowering effect and safety of the new method of very deep sclerectomy with collagen implant (VDSCI) compared with standard deep sclerectomy with collagen implant (DSCI). METHODS: The trial involved 50 eyes of 48 patients with medically uncontrolled primary and secondary open-angle glaucoma, randomized to undergo either VDSCI procedure (25 eyes) or DSCI procedure (25 eyes). Follow-up examinations were performed before surgery and after surgery at day 1, at week 1, at months 1, 2, 3, 6, 9, 12, 18, and 24 months. Ultrasound biomicroscopy was performed at 3 and 12 months. RESULTS: Mean follow-up period was 18.6+/-5.9 (VDSCI) and 18.9+/-3.6 (DSCI) months (P=NS). Mean preoperative IOP was 22.4+/-7.4 mm Hg for VDSCI and 20.4+/-4.4 mm Hg for DSCI eyes (P=NS). Mean postoperative IOP was 3.9+/-2.3 (VDSCI) and 6.3+/-4.3 (DSCI) (P<0.05) at day 1, and 12.2+/-3.9 (VDSCI) and 13.3+/-3.4 (DSCI) (P=NS) at month 24. At the last visit, the complete success rate (defined as an IOP of < or =18 mm Hg and a percentage drop of at least 20%, achieved without medication) was 57% in VDSCI and 62% in DSCI eyes (P=NS) ultrasound biomicroscopy at 12 months showed a mean volume of the subconjunctival filtering bleb of 3.9+/-4.2 mm3 (VDSCI) and 6.8+/-7.5 mm3 (DSCI) (P=0.426) and 5.2+/-3.6 mm3 (VDSCI) and 5.4+/-2.9 mm3 (DSCI) (P=0.902) for the intrascleral space. CONCLUSIONS: Very deep sclerectomy seems to provide stable and good control of IOP at 2 years of follow-up with few postoperative complications similar to standard deep sclerectomy with the collagen implant.
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The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.
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Recognition systems play a key role in a range of biological processes, including mate choice, immune defence and altruistic behaviour. Social insects provide an excellent model for studying recognition systems because workers need to discriminate between nestmates and non-nestmates, enabling them to direct altruistic behaviour towards closer kin and to repel potential invaders. However, the level of aggression directed towards conspecific intruders can vary enormously, even among workers within the same colony. This is usually attributed to differences in the aggression thresholds of individuals or to workers having different roles within the colony. Recent evidence from the weaver ant Oecophylla smaragdina suggests that this does not tell the whole story. Here I propose a new model for nestmate recognition based on a vector template derived from both the individual's innate odour and the shared colony odour. This model accounts for the recent findings concerning weaver ants, and also provides an alternative explanation for why the level of aggression expressed by a colony decreases as the diversity within the colony increases, even when odour is well-mixed. The model makes additional predictions that are easily tested, and represents a significant advance in our conceptualisation of recognition systems.
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To evaluate the risk of transmission of vector-borne diseases, regular updates of the geographic distribution of insect vectors are required. In the archipelago of Cape Verde, nine mosquito species have been reported. Of these, four are major vectors of diseases that have been present in the archipelago: yellow fever, lymphatic filariasis, malaria and, currently, an outbreak of dengue. In order to assess variation in mosquito biodiversity, we have carried out an update on the distribution of the mosquito species in Cape Verde, based on an enquiry of 26 unpublished technical reports (1983-2006) and on the results of an entomological survey carried out in 2007. Overall, there seems to be a general trend for an expansion of biological diversity in the islands. Mosquito species richness was negatively correlated with the distance of the islands from the mainland but not with the size of the islands. Human- and/or sporadic climatic-mediated events of dispersal may have contributed to a homogenization of species richness regardless of island size but other ecological factors may also have affected the mosquito biogeography in the archipelago. An additional species, Culex perexiguus, was collected for the first time in the archipelago during the 2007 survey.
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Les inhibiteurs de la protéase du VIH (IP) constituent une des classes de traitements antirétroviraux parmi les plus utilisés au cours de l'infection par le VIH. Leur utilisation est associée à divers effets secondaires, notamment la dyslipidémie, la résistance à l'insuline, la lipodystrophie et certaines complications cardio-vasculaires. Ces molécules ont également des propriétés anti-tumorales, décrites chez des patients non infectés par le VIH. Pourtant, les mécanismes moléculaires à l'origine de ces effets annexes restent méconnus. Dans ce travail, nous démontrons que les IP, comme le Nelfinavir, le Ritonavir, le Lopinavir, le Saquinavir et l'Atazanavir, entrainent la production d'interleukine-lß (IL-lß), une puissante cytokine pro-inflammatoire, connue pour son rôle central dans les maladies inflammatoires. La sécrétion d'IL-lß requiert la formation de l'inflammasome, un complexe protéique intracellulaire servant de plateforme d'activation de la caspase-1 et, par la suite, à la maturation protéolytique de certaines cytokines, dont l'IL-lß. Dans les macrophages murins en culture primaire, ainsi que dans une lignée de monocytes humains, nous démontrons que les IP augmentent la maturation et la sécrétion de l'IL-lß via l'induction d'un inflammasome dépendant de ASC. De plus, nous établissons que les IP induisent spécifiquement l'activation de AIM2, un inflammasome détectant la présence intracytosolique d'ADN viral ou bactérien. Nos résultats démontrent l'existence d'une nouvelle voie d'activation de l'inflammasome AIM2 par un signal endogène dont la nature reste à définir. Ces données suggèrent que AIM2 pourrait jouer un rôle important dans la promotion de l'activité anti-tumorale ainsi que dans les autres effets annexes observés chez les patients traités par IP. -- HIV protease inhibitors (Pis) are among the most often used classes of antiretroviral drugs for HIV infection. Treatment of patients with HIV-PIs is associated with the development of metabolic side effects including dyslipidemia, insulin resistance, lipodystrophy and cardiovascular complications. In addition, these drugs have been reported to have anti¬tumoral properties in non-infected patients, however the molecular mechanisms causing these off-target effects are still unclear. Here we show that the HIV-PIs, such as Nelfinavir, Ritonavir, Lopinavir, Saquinavir and Atazanavir, activate the production of interleukin-lß (IL-lß), a potent pro-inflammatory cytokine that plays a central role in the pathogenesis of inflammatory diseases. The release of IL-lß depends on the activation of the inflammasome, a multiprotein complex that serves as a platform for caspase-1 activation and subsequent proteolytic maturation of cytokines including IL-lß. We found that in mouse primary macrophages as well as in a human monocytic cell line, the HIV-PIs augment the maturation and secretion of IL-lß by triggering an ASC-dependent inflammasome activation. Moreover, we show that the HIV-PIs specifically engage AIM2, a recently characterized inflammasome -forming protein that was described to detect the cytosolic release of bacterial and viral DNA. Our findings demonstrate a new pathway of activation of the AIM2 inflammasome by a yet to be defined endogenous signal and may suggest a possible role for AIM2 in promoting anti¬tumoral activity and off-target effects observed in HIV-PIs treated patients.
Resumo:
This study describes a task that combines random searching with goal directed navigation. The testing was conducted on a circular elevated open field (80 cm in diameter), with an unmarked target area (20 cm in diameter) in the center of 1 of the 4 quadrants. Whenever the rat entered the target area, the computerized tracking system released a pellet to a random point on the open field. Rats were able to learn the task under light and in total darkness, and on a stable or a rotating arena. Visual information was important in light, but idiothetic information became crucial in darkness. Learning of a new position was quicker under light than in total darkness on a rotating arena. The place preference task should make it possible to study place cells (PCs) when the rats use an allothetic (room frame) or idiothetic (arena frame) representation of space and to compare the behavioral response with the PCs' activity.
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Glioblastoma are rapidly proliferating brain tumors in which hypoxia is readily recognizable, as indicated by focal or extensive necrosis and vascular proliferation, two independent diagnostic criteria for glioblastoma. Gene expression profiling of glioblastoma revealed a gene expression signature associated with hypoxia-regulated genes. The correlated gene set emerging from unsupervised analysis comprised known hypoxia-inducible genes involved in angiogenesis and inflammation such as VEGF and BIRC3, respectively. The relationship between hypoxia-modulated angiogenic genes and inflammatory genes was associated with outcome in our cohort of glioblastoma patients treated within prospective clinical trials of combined chemoradiotherapy. The hypoxia regulation of several new genes comprised in this cluster including ZNF395, TNFAIP3, and TREM1 was experimentally confirmed in glioma cell lines and primary monocytes exposed to hypoxia in vitro. Interestingly, the cluster seems to characterize differential response of tumor cells, stromal cells and the macrophage/microglia compartment to hypoxic conditions. Most genes classically associated with the inflammatory compartment are part of the NF-kappaB signaling pathway including TNFAIP3 and BIRC3 that have been shown to be involved in resistance to chemotherapy.Our results associate hypoxia-driven tumor response with inflammation in glioblastoma, hence underlining the importance of tumor-host interaction involving the inflammatory compartment.
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New method for rearing Spodoptera frugiperda in laboratory shows that larval cannibalism is not obligatory. Here we show, for the first time, that larvae of the fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera, Noctuidae), can be successfully reared in a cohort-based manner with virtually no cannibalism. FAW larvae were reared since the second instar to pupation in rectangular plastic containers containing 40 individuals with a surprisingly ca. 90% larval survivorship. Adult females from the cohort-based method showed fecundity similar to that already reported on literature for larvae reared individually, and fertility higher than 99%, with the advantage of combining economy of time, space and material resources. These findings suggest that the factors affecting cannibalism of FAW larvae in laboratory rearings need to be reevaluated, whilst the new technique also show potential to increase the efficiency of both small and mass FAW rearings.
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Purposes of this Report: • Recommend the most logical and economical options to address state governmental space needs in the Polk County metropolitan area to the year 2010. • Include building size, location, phasing, financing, method of project delivery and estimated cost. • Develop a software tool to compare costs of leasing vs. ownership of space. Methodology: Identify: 1. Current amount and location of owned and leased space, by agency; 2. Types of space and whether best located on or off of the Capitol Complex; 3. Utilization of space, noting over-crowding and under-utilization; 4. Current number of workstations for full and part time employees, Personnel Employment Organization (PEO) workers, contractors, interns, etc.; and, 5. History of staff levels to assist in the prediction of staff growth. Scope: This report focuses on 10 state-owned buildings located on the Capitol Complex and 48 leased spaces in the Polk County metropolitan area. (See Figures 1 and 2.) • Due to a separate space study under way by the Legislature, implications of area and staff for the State Capitol building are included only for the Governor, Lieutenant Governor, Treasurer, Secretary of State, Auditor and the Department of Management. • Because it is largely a museum building that does not have office space available for other agencies, the area and staff of the Historical Building are not fully addressed. • Only the parking implications of the new Judicial Building are included in this study because the building space is under the jurisdiction of the Judicial Branch and not available for other agencies. Several state-owned buildings are not included in the scope of this report, generally because they have highly focused purposes, and their space is not available for assignment to other agencies. Several leased locations are not included for similar reasons, including leases that do not fall within the authority of the Department of General Services.
Resumo:
In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).