Clypeal patterning in the paper wasp Polistes dominulus: no evidence of adaptive value in the wild

Status signals function in a number of species to communicate competitive ability to conspecific rivals during competition for resources. In the paper wasp Polistes dominulus, variable black clypeal patterns are thought to be important in mediating competition among females. Results of previous behavioral experiments in the lab indicate that P dominulus clypeal patterns provide information about an individual's competitive ability to rivals during agonistic interactions. To date, however, there has been no detailed examination of the adaptive value of clypeal patterns in the wild. To address this, we looked for correlations between clypeal patterning and various fitness measures, including reproductive success, hierarchical rank, and survival, in a large, free-living population of P. dominulus in southern Spain. Reproductive success over the nesting season was not correlated with clypeal patterning. Furthermore, there was no relationship between a female's clypeal patterning and the rank she achieved within the hierarchy or her survival during nest founding. Overall, we found no evidence that P dominulus clypeal patterns are related to competitive ability or other aspects of quality in our population. This result is consistent with geographical variation in the adaptive value of clypeal patterns between P. dominulus populations; however, data on the relationship between patterning and fitness from other populations are required to test this hypothesis.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Inventory of sparse forest populations using adaptive cluster sampling

Abstract

HIV-1 vaccines and adaptive trial designs.

Developing a vaccine against the human immunodeficiency virus (HIV) poses an exceptional challenge. There are no documented cases of immune-mediated clearance of HIV from an infected individual, and no known correlates of immune protection. Although nonhuman primate models of lentivirus infection have provided valuable data about HIV pathogenesis, such models do not predict HIV vaccine efficacy in humans. The combined lack of a predictive animal model and undefined biomarkers of immune protection against HIV necessitate that vaccines to this pathogen be tested directly in clinical trials. Adaptive clinical trial designs can accelerate vaccine development by rapidly screening out poor vaccines while extending the evaluation of efficacious ones, improving the characterization of promising vaccine candidates and the identification of correlates of immune protection.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Effectiveness of a specialized outpatient palliative care service as experienced by patients and caregivers.

Abstract Objectives: In Germany since 2007 patients with advanced life-limiting diseases are eligible for Specialized Outpatient Palliative Care (SOPC). To provide this service, SOPC teams have been established as a new facility in the health care system. The objective of this study was to evaluate the effectiveness of one of the first SOPC teams based at the Munich University Hospital. Methods: All patients treated by the SOPC team and their primary caregivers were eligible for this prospective nonrandomized study. The main topics of the surveys before and after involvement of the SOPC team were: for patients, the assessment of symptom burden (Minimal Documentation System for Palliative Medicine, MIDOS), satisfaction with quality of palliative care (Palliative Outcome Scale, POS), and quality of life (McGill Quality of Life Questionnaire, MQOL); for caregivers, burden of care (Häusliche Pflegeskala, home care scale, HPS), anxiety and depression (Hospital Anxiety and Depression Scale, HADS), and quality of life (Quality of Life in Life-Threatening Illness-Family Carer Version, QOLLTI-F). Results: Of 100 patients treated between April and November 2011, 60 were included in the study (median age 67.5 years, 55% male, 87% oncological diseases). In 23 of 60 patients, only caregivers could be interviewed. The median interval between the first and second interview was 2.5 weeks. Quality of life increased significantly in patients (p<0.05) and caregivers (p<0.001), as did the patients' perception of quality of palliative care (POS, p<0.001), while the caregivers' psychological distress and burden of care significantly decreased (HADS, p<0.001; HPS, p<0.001). Conclusions: The involvement of an SOPC team leads to a significant improvement in the quality of life of patients and caregivers and can lower the burden of home care for the caregivers of severely ill patients.

Evidence for adaptive radiation from a phylogenetic study of plant defenses.

One signature of adaptive radiation is a high level of trait change early during the diversification process and a plateau toward the end of the radiation. Although the study of the tempo of evolution has historically been the domain of paleontologists, recently developed phylogenetic tools allow for the rigorous examination of trait evolution in a tremendous diversity of organisms. Enemy-driven adaptive radiation was a key prediction of Ehrlich and Raven's coevolutionary hypothesis [Ehrlich PR, Raven PH (1964) Evolution 18:586-608], yet has remained largely untested. Here we examine patterns of trait evolution in 51 North American milkweed species (Asclepias), using maximum likelihood methods. We study 7 traits of the milkweeds, ranging from seed size and foliar physiological traits to defense traits (cardenolides, latex, and trichomes) previously shown to impact herbivores, including the monarch butterfly. We compare the fit of simple random-walk models of trait evolution to models that incorporate stabilizing selection (Ornstein-Ulenbeck process), as well as time-varying rates of trait evolution. Early bursts of trait evolution were implicated for 2 traits, while stabilizing selection was implicated for several others. We further modeled the relationship between trait change and species diversification while allowing rates of trait evolution to vary during the radiation. Species-rich lineages underwent a proportionately greater decline in latex and cardenolides relative to species-poor lineages, and the rate of trait change was most rapid early in the radiation. An interpretation of this result is that reduced investment in defensive traits accelerated diversification, and disproportionately so, early in the adaptive radiation of milkweeds.

C4 Photosynthesis evolved in grasses via parallel adaptive genetic changes.

Phenotypic convergence is a widespread and well-recognized evolutionary phenomenon. However, the responsible molecular mechanisms remain often unknown mainly because the genes involved are not identified. A well-known example of physiological convergence is the C4 photosynthetic pathway, which evolved independently more than 45 times [1]. Here, we address the question of the molecular bases of the C4 convergent phenotypes in grasses (Poaceae) by reconstructing the evolutionary history of genes encoding a C4 key enzyme, the phosphoenolpyruvate carboxylase (PEPC). PEPC genes belong to a multigene family encoding distinct isoforms of which only one is involved in C4 photosynthesis [2]. By using phylogenetic analyses, we showed that grass C4 PEPCs appeared at least eight times independently from the same non-C4 PEPC. Twenty-one amino acids evolved under positive selection and converged to similar or identical amino acids in most of the grass C4 PEPC lineages. This is the first record of such a high level of molecular convergent evolution, illustrating the repeatability of evolution. These amino acids were responsible for a strong phylogenetic bias grouping all C4 PEPCs together. The C4-specific amino acids detected must be essential for C4 PEPC enzymatic characteristics, and their identification opens new avenues for the engineering of the C4 pathway in crops.

Probabilistic algorithms for blind adaptive multiuser detection

In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

Statistical reference criteria for adaptive signal processing in digital communications

A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

Effectiveness of anti-psychotics and related drugs in the Huntington French-speaking group cohort.

PURPOSE: Huntington's disease is a rare condition. Patients are commonly treated with antipsychotics and tetrabenazine. The evidence of their effect on disease progression is limited and no comparative study between these drugs has been conducted. We therefore compared the effectiveness of antipsychotics on disease progression. METHODS: 956 patients from the Huntington French Speaking Group were followed for up to 8 years between 2002 and 2010. The effectiveness of treatments was assessed using Unified Huntington's Disease Rating Scale (UHDRS) scores and then compared using a mixed model adjusted on a multiple propensity score. RESULTS: 63% of patients were treated with antipsychotics during the survey period. The most commonly prescribed medications were dibenzodiazepines (38%), risperidone (13%), tetrabenazine (12%) and benzamides (12%). There was no difference between treatments on the motor and behavioural declines observed, after taking the patient profiles at the start of the drug prescription into account. In contrast, the functional decline was lower in the dibenzodiazepine group than the other antipsychotic groups (Total Functional Capacity: 0.41 ± 0.17 units per year vs. risperidone and 0.54 ± 0.19 vs. tetrabenazine, both p<0.05). Benzamides were less effective than other antipsychotics on cognitive evolution (Stroop interference, Stroop color and Literal fluency: p<0.05). CONCLUSIONS: Antipsychotics are widely used to treat patients with Huntington's disease. Although differences in motor or behavioural profiles between patients according to the antipsychotics used were small, there were differences in drug effectiveness on the evolution of functional and cognitive scores.

Release Process Effectiveness - Case of Operating Room Management Software

Työn päätavoitteena oli tuoda esiin tärkeimmät julkistamisprosessin tehokkuuteen vaikuttavat tekijät. Tutkimuksessa tarkasteltiin aihetta julkistamisprojektien vetäjän näkökulmasta. Kirjallinen selvitys kattaa keskeisimmät ohjelmistoprosessin, palvelun laadun sekä projektihallinnan teoriat. Kokeellisena aineistona käytettiin asiakkailta ja myynnin sekä käyttöönoton organisaatioilta tullutta palautetta ja asiantuntijahaastatteluita. Case-tuotteena tarkasteltiin suuren kansainvälisen yrityksen jälleenmyymää leikkaussalihallinnan ohjelmistoa. Tärkeimpiä julkistamisprosessin tehokkuuteen vaikuttavia tekijöitä ovat tiekartan ja julkistamispakettien sisällön hallinta, projektin aikataulujen pitäminen, rehellinen ja nopea kommunikaatio myyntikanavaan ja asiakkaille, sekä hyvin toteutettu testaus. Työssä käydään läpi esimerkkistrategioita kehittymiseen näillä alueilla.