Evolutionary and dispersal history of Eurasian house mice Mus musculus clarified by more extensive geographic sampling of mitochondrial DNA.

We examined the sequence variation of mitochondrial DNA control region and cytochrome b gene of the house mouse (Mus musculus sensu lato) drawn from ca. 200 localities, with 286 new samples drawn primarily from previously unsampled portions of their Eurasian distribution and with the objective of further clarifying evolutionary episodes of this species before and after the onset of human-mediated long-distance dispersals. Phylogenetic analysis of the expanded data detected five equally distinct clades, with geographic ranges of northern Eurasia (musculus, MUS), India and Southeast Asia (castaneus, CAS), Nepal (unspecified, NEP), western Europe (domesticus, DOM) and Yemen (gentilulus). Our results confirm previous suggestions of Southwestern Asia as the likely place of origin of M. musculus and the region of Iran, Afghanistan, Pakistan, and northern India, specifically as the ancestral homeland of CAS. The divergence of the subspecies lineages and of internal sublineage differentiation within CAS were estimated to be 0.37-0.47 and 0.14-0.23 million years ago (mya), respectively, assuming a split of M. musculus and Mus spretus at 1.7 mya. Of the four CAS sublineages detected, only one extends to eastern parts of India, Southeast Asia, Indonesia, Philippines, South China, Northeast China, Primorye, Sakhalin and Japan, implying a dramatic range expansion of CAS out of its homeland during an evolutionary short time, perhaps associated with the spread of agricultural practices. Multiple and non-coincident eastward dispersal events of MUS sublineages to distant geographic areas, such as northern China, Russia and Korea, are inferred, with the possibility of several different routes.

ML approaches to channel estimation for pilot-aided multi-rate DS/CDMA systems

This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation purposes. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channelestimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basicsystem parameters such as number of codes, spreading factors, or traffic to training power ratio.

Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon.

BACKGROUND: Elucidating disease and developmental dysfunction requires understanding variation in phenotype. Single-species model organism anatomy ontologies (ssAOs) have been established to represent this variation. Multi-species anatomy ontologies (msAOs; vertebrate skeletal, vertebrate homologous, teleost, amphibian AOs) have been developed to represent 'natural' phenotypic variation across species. Our aim has been to integrate ssAOs and msAOs for various purposes, including establishing links between phenotypic variation and candidate genes. RESULTS: Previously, msAOs contained a mixture of unique and overlapping content. This hampered integration and coordination due to the need to maintain cross-references or inter-ontology equivalence axioms to the ssAOs, or to perform large-scale obsolescence and modular import. Here we present the unification of anatomy ontologies into Uberon, a single ontology resource that enables interoperability among disparate data and research groups. As a consequence, independent development of TAO, VSAO, AAO, and vHOG has been discontinued. CONCLUSIONS: The newly broadened Uberon ontology is a unified cross-taxon resource for metazoans (animals) that has been substantially expanded to include a broad diversity of vertebrate anatomical structures, permitting reasoning across anatomical variation in extinct and extant taxa. Uberon is a core resource that supports single- and cross-species queries for candidate genes using annotations for phenotypes from the systematics, biodiversity, medical, and model organism communities, while also providing entities for logical definitions in the Cell and Gene Ontologies. THE ONTOLOGY RELEASE FILES ASSOCIATED WITH THE ONTOLOGY MERGE DESCRIBED IN THIS MANUSCRIPT ARE AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/2013-02-21/ CURRENT ONTOLOGY RELEASE FILES ARE AVAILABLE ALWAYS AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/

Multi-slice three-dimensional myocardial strain tensor quantification using zHARP.

In this article we propose a novel method for calculating cardiac 3-D strain. The method requires the acquisition of myocardial short-axis (SA) slices only and produces the 3-D strain tensor at every point within every pair of slices. Three-dimensional displacement is calculated from SA slices using zHARP which is then used for calculating the local displacement gradient and thus the local strain tensor. There are three main advantages of this method. First, the 3-D strain tensor is calculated for every pixel without interpolation; this is unprecedented in cardiac MR imaging. Second, this method is fast, in part because there is no need to acquire long-axis (LA) slices. Third, the method is accurate because the 3-D displacement components are acquired simultaneously and therefore reduces motion artifacts without the need for registration. This article presents the theory of computing 3-D strain from two slices using zHARP, the imaging protocol, and both phantom and in-vivo validation.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Involvement of family physicians in structured programs for chronic diseases or multi-morbidity in Switzerland.

The increasing prevalence of chronic diseases and multi-morbidity represents challenges for health systems worldwide. In that perspective, the current organization of healthcare delivery, fragmentation of care, limited use of evidence-based guidelines and patients'insufficient empowerment are some reasons explaining the current limited effectiveness of the management of chronically ill patients. Based on theoretical models such as the Chronic Care Model (CCM), initiatives targeting improvements in the care of patients with chronic diseases have been implemented worldwide since more than a decade. Their development in Switzerland, a health system where more than half of practices are still single handed [6], is only recent and infrequent. Structured programs for patients with chronic diseases or multimorbidity usually propose patient-centered interventions and consider an integrative multidisciplinary approach. Currently, little is known on the existence of such programs and on the role of family physicians (FPs)within these programs, in Switzerland. The objective of this study was to identify and describe current structured programs targeting chronic diseases or multi-morbidity in Switzerland. This may help in examining innovative approaches that are only developed locally but would deserve wider interest for further implementation. We conducted a telephone-based survey between June and November 2013 and contacted systematically key institutions, informants and stakeholders nationwide and in the 26 cantons...

Multi-scale effects of nestling diet on breeding performance in a terrestrial top predator inferred from stable isotope analysis

Inter-individual diet variation within populations is likely to have important ecological and evolutionary implications. The diet-fitness relationships at the individual level and the emerging population processes are, however, poorly understood for most avian predators inhabiting complex terrestrial ecosystems. In this study, we use an isotopic approach to assess the trophic ecology of nestlings in a long-lived raptor, the Bonelli"s eagle Aquila fasciata, and investigate whether nestling dietary breath and main prey consumption can affect the species" reproductive performance at two spatial scales: territories within populations and populations over a large geographic area. At the territory level, those breeding pairs whose nestlings consumed similar diets to the overall population (i.e. moderate consumption of preferred prey, but complemented by alternative prey categories) or those disproportionally consuming preferred prey were more likely to fledge two chicks. An increase in the diet diversity, however, related negatively with productivity. The age and replacements of breeding pair members had also an influence on productivity, with more fledglings associated to adult pairs with few replacements, as expected in long-lived species. At the population level, mean productivity was higher in those population-years with lower dietary breadth and higher diet similarity among territories, which was related to an overall higher consumption of preferred prey. Thus, we revealed a correspondence in diet-fitness relationships at two spatial scales: territories and populations. We suggest that stable isotope analyses may be a powerful tool to monitor the diet of terrestrial avian predators on large spatio-temporal scales, which could serve to detect potential changes in the availability of those prey on which predators depend for breeding. We encourage ecologists and evolutionary and conservation biologists concerned with the multi-scale fitness consequences of inter-individual variation in resource use to employ similar stable isotope-based approaches, which can be successfully applied to complex ecosystems such as the Mediterranean.

Tuning Performance of Multi-threaded programs

Diplomityö tarkastelee säikeistettyä ohjelmointia rinnakkaisohjelmoinnin ylemmällä hierarkiatasolla tarkastellen erityisesti hypersäikeistysteknologiaa. Työssä tarkastellaan hypersäikeistyksen hyviä ja huonoja puolia sekä sen vaikutuksia rinnakkaisalgoritmeihin. Työn tavoitteena oli ymmärtää Intel Pentium 4 prosessorin hypersäikeistyksen toteutus ja mahdollistaa sen hyödyntäminen, missä se tuo suorituskyvyllistä etua. Työssä kerättiin ja analysoitiin suorituskykytietoa ajamalla suuri joukko suorituskykytestejä eri olosuhteissa (muistin käsittely, kääntäjän asetukset, ympäristömuuttujat...). Työssä tarkasteltiin kahdentyyppisiä algoritmeja: matriisioperaatioita ja lajittelua. Näissä sovelluksissa on säännöllinen muistinkäyttökuvio, mikä on kaksiteräinen miekka. Se on etu aritmeettis-loogisissa prosessoinnissa, mutta toisaalta huonontaa muistin suorituskykyä. Syynä siihen on nykyaikaisten prosessorien erittäin hyvä raaka suorituskyky säännöllistä dataa käsiteltäessä, mutta muistiarkkitehtuuria rajoittaa välimuistien koko ja useat puskurit. Kun ongelman koko ylittää tietyn rajan, todellinen suorituskyky voi pudota murto-osaan huippusuorituskyvystä.

Multi-institutional validation of the prognostic value of Ki-67 labeling index in patients treated with radical prostatectomy.

OBJECTIVE: Several smaller single-center studies have reported a prognostic role for Ki-67 labeling index in prostate cancer. Our aim was to test whether Ki-67 is an independent prognostic marker of biochemical recurrence (BCR) in a large international cohort of patients treated with radical prostatectomy (RP). METHODS: Ki-67 immunohistochemical staining on prostatectomy specimens from 3,123 patients who underwent RP for prostate cancer was retrospectively performed. Univariable and multivariable Cox regression models were used to assess the association of Ki-67 status with BCR. RESULTS: Ki-67 positive status was observed in 762 (24.4 %) patients and was associated with lymph node involvement (LNI) (p = 0.039). Six hundred and twenty-one (19.9 %) patients experienced BCR. The estimated 3-year biochemical-free survivals were 85 % for patients with negative Ki-67 status and 82.1 % for patients with positive Ki-67 status (log-rank test, p = 0.014). In multivariable analysis that adjusted for the effects of age, preoperative PSA, RP Gleason sum, seminal vesicle invasion, extracapsular extension, positive surgical margins, lymphovascular invasion, and LNI, Ki-67 was significantly associated with BCR (HR = 1.19; p = 0.019). Subgroup analysis revealed that Ki-67 is associated with BCR in patients without LNI (p = 0.004), those with RP Gleason sum 7 (p = 0.015), and those with negative surgical margins (p = 0.047). CONCLUSION: We confirmed Ki-67 as an independent predictor of BCR after RP. Ki-67 could be particularly informative in patients with favorable pathologic characteristics to help in the clinical decision-making regarding adjuvant therapy and optimized follow-up scheduling.

Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

Objective assessment of low contrast detectability in computed tomography with Channelized Hotelling Observer.

PURPOSE: Iterative algorithms introduce new challenges in the field of image quality assessment. The purpose of this study is to use a mathematical model to evaluate objectively the low contrast detectability in CT. MATERIALS AND METHODS: A QRM 401 phantom containing 5 and 8 mm diameter spheres with a contrast level of 10 and 20 HU was used. The images were acquired at 120 kV with CTDIvol equal to 5, 10, 15, 20 mGy and reconstructed using the filtered back-projection (FBP), adaptive statistical iterative reconstruction 50% (ASIR 50%) and model-based iterative reconstruction (MBIR) algorithms. The model observer used is the Channelized Hotelling Observer (CHO). The channels are dense difference of Gaussian channels (D-DOG). The CHO performances were compared to the outcomes of six human observers having performed four alternative forced choice (4-AFC) tests. RESULTS: For the same CTDIvol level and according to CHO model, the MBIR algorithm gives the higher detectability index. The outcomes of human observers and results of CHO are highly correlated whatever the dose levels, the signals considered and the algorithms used when some noise is added to the CHO model. The Pearson coefficient between the human observers and the CHO is 0.93 for FBP and 0.98 for MBIR. CONCLUSION: The human observers' performances can be predicted by the CHO model. This opens the way for proposing, in parallel to the standard dose report, the level of low contrast detectability expected. The introduction of iterative reconstruction requires such an approach to ensure that dose reduction does not impair diagnostics.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.

Development of a social service in a multi-party network

Tämän pro gradu-tutkimuksen tarkoituksena oli tutkia monen toimijan sosiaalipalvelukehittäjäverkoston toimivuutta ja sen toimivuuteen vaikuttavia tekijöitä. Aihetta lähestyttiin erilaisten teoreettisten kokonaisuuksien kautta, joiden avulla saatiin luotua tutkimukselle pohja. Viitekehys tutkimukselle luotiin yhdistäen erilaisia teoreettisia aihealueita verkostoista, verkostojen johtamisesta ja palveluista. Tutkimuksessa korostuu motivaation, yhteisen, tarpeeseen perustuvan tavoitteen, sitoutumisen ja orkestroinnin merkitys verkostotoiminnassa hyvän lopputuloksen aikaansaamiseksi. Tutkimuksen empiirisessä osuudessa tehty kvalitatiivinen case-tutkimus keskittyy tiettyyn verkostoon, joka on Socomin koordinoimana kehittänyt Kaakkois-Suomen alueelle uudenlaista sosiaalipalvelua liittyen henkilökohtaiseen apuun. Verkosto on monen toimijan verkosto, jonka jäsenet edustavat erilaisia tahoja ja organisaatioita. Tutkimuksen perusteella verkosto on toiminut hyvin ja tehokkaasti ja saanut luotua toimivan sosiaalipalvelun. Verkosto tukee kirjallisuuskatsauksessa löydettyjen tekijöiden, kuten verkosto-orkestroinnin, sitoutumisen ja yhteisen päämäärän, vaikutusta verkoston toimintaan ja lopputulokseen.

Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization

Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat® software was used, and different data mining algorithms were applied using Weka® software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization.