Dense fine-mapping study identifies new susceptibility loci for primary biliary cirrhosis

We genotyped 2,861 cases of primary biliary cirrhosis (PBC) from the UK PBC Consortium and 8,514 UK population controls across 196,524 variants within 186 known autoimmune risk loci. We identified 3 loci newly associated with PBC (at P <5 × 10(-8)), increasing the number of known susceptibility loci to 25. The most associated variant at 19p12 is a low-frequency nonsynonymous SNP in TYK2, further implicating JAK-STAT and cytokine signaling in disease pathogenesis. An additional five loci contained nonsynonymous variants in high linkage disequilibrium (LD; r(2) > 0.8) with the most associated variant at the locus. We found multiple independent common, low-frequency and rare variant association signals at five loci. Of the 26 independent non-human leukocyte antigen (HLA) signals tagged on the Immunochip, 15 have SNPs in B-lymphoblastoid open chromatin regions in high LD (r(2) > 0.8) with the most associated variant. This study shows how data from dense fine-mapping arrays coupled with functional genomic data can be used to identify candidate causal variants for functional follow-up.

Inscribing value on business model innovations: Insights from industrial projects commercializing disruptive digital innovations

In this paper we seek to show how marketing activities inscribe value on business model innovation, representative of an act, or sequence of socially interconnecting acts. Theoretically we ask two interlinked questions: (1) how can value inscriptions contribute to business model innovations? (2) how can marketing activities support the inscription of value on business model innovations? Semi-structured in-depth interviews were conducted with the thirty-seven members from across four industrial projects commercializing disruptive digital innovations. Various individuals from a diverse range of firms are shown to cast relevant components of their agency and knowledge on business model innovations through negotiation as an ongoing social process. Value inscription is mutually constituted from the marketing activities, interactions and negotiations of multiple project members across firms and functions to counter destabilizing forces and tensions arising from the commercialization of disruptive digital innovations. This contributes to recent conceptual thinking in the industrial marketing literature, which views business models as situated within dynamic business networks and a context-led evolutionary process. A contribution is also made to debate in the marketing literature around marketing's boundary-spanning role, with marketing activities shown to span and navigate across functions and firms in supporting value inscriptions on business model innovations.

Betwixt spaces: Students’ accounts of turning point experiences in first-year transitions

'Not belonging' is becoming a prevalent theme within accounts of the first-year student experience at university. In this study the notion of not belonging is extended by assuming a more active role for the idea of liminality in a student's transition into the university environments of academic and student life. In doing so, the article suggests that the transition between one place (home) and another (university) can result in an 'in-between-ness' - a betwixt space. Through an interpretative methodology, the study explores how students begin to move from this betwixt space into feeling like fully-fledged members of university life. It is concluded that there is a wide range of turning points associated with the students' betwixt transition, which shapes, alters or indeed accentuates the ways in which they make meaningful connections with university life. Moreover, transitional turning point experiences reveal a cast of characters and symbolic objects; capture contrasting motivations and evolving relationships; display multiple trajectories of interpersonal tensions and conflicts; highlight discontinuities as well as continuities; and together, simultaneously liberate and constrain the students' transition into university life.

SN 2009ip á la PESSTO:No evidence for core-collapse yet

We present observations of the interacting transient SN 2009ip, from the start of the outburst in October 2012 until the end of the 2012 observing season. The transient reached a peak of $M_V$=-17.7 mag before fading rapidly, with a total integrated luminosity of 1.9$\times10^{49}$ erg over the period of August-December 2012. The optical and near infrared spectra are dominated by narrow emission lines, signaling a dense circumstellar environment, together with multiple components of broad emission and absorption in H and He at velocities between 0.5-1.2$\times10^4$ km s$^{-1}$\. We see no evidence for nucleosynthesized material in SN 2009ip, even in late-time pseudo-nebular spectra. We set a limit of $

Three-port DC-DC Converter for Stand-Alone Photovoltaic Systems

System efficiency and cost effectiveness are of critical importance for photovoltaic (PV) systems. This paper addresses the two issues by developing a novel three-port DC-DC converter for stand-alone PV systems, based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation and multiple operating modes for domestic and aerospace applications. A theoretical analysis is conducted to analyze the operating modes followed by simulation and experimental work. The paper is focused on a comprehensive modulation strategy utilizing both PWM and phase-shifted control that satisfies the requirement of PV power systems to achieve MPPT and output voltage regulation. A 250 W converter was designed and prototyped to provide experimental verification in term of system integration and high conversion efficiency.

Arbuscular mycorrhizal fungal communities are phylogenetically clustered at small scales

Next-generation sequencing technologies with markers covering the full Glomeromycota phylum were used to uncover phylogenetic community structure of arbuscular mycorrhizal fungi (AMF) associated with Festuca brevipila. The study system was a semi-arid grassland with high plant diversity and a steep environmental gradient in pH, C, N, P and soil water content. The AMF community in roots and rhizosphere soil were analyzed separately and consisted of 74 distinct operational taxonomic units (OTUs) in total. Community-level variance partitioning showed that the role of environmental factors in determining AM species composition was marginal when controlling for spatial autocorrelation at multiple scales. Instead, phylogenetic distance and spatial distance were major correlates of AMF communities: OTUs that were more closely related (and which therefore may have similar traits) were more likely to co-occur. This pattern was insensitive to phylogenetic sampling breadth. Given the minor effects of the environment, we propose that at small scales closely related AMF positively associate through biotic factors such as plant-AMF filtering and interactions within the soil biota.

Plan Selection for Probabilistic BDI Agents

When an agent wants to fulfill its desires about the world, the agent usually has multiple plans to choose from and these plans have different pre-conditions and additional effects in addition to achieving its goals. Therefore, for further reasoning and interaction with the world, a plan selection strategy (usually based on plan cost estimation) is mandatory for an autonomous agent. This demand becomes even more critical when uncertainty on the observation of the world is taken into account, since in this case, we consider not only the costs of different plans, but also their chances of success estimated according to the agent's beliefs. In addition, when multiple goals are considered together, different plans achieving the goals can be conflicting on their preconditions (contexts) or the required resources. Hence a plan selection strategy should be able to choose a subset of plans that fulfills the maximum number of goals while maintaining context consistency and resource-tolerance among the chosen plans. To address the above two issues, in this paper we first propose several principles that a plan selection strategy should satisfy, and then we present selection strategies that stem from the principles, depending on whether a plan cost is taken into account. In addition, we also show that our selection strategy can partially recover intention revision.

A hybrid harmony search with arithmetic crossover operation for economic dispatch

Economic dispatch (ED) problems often exhibit non-linear, non-convex characteristics due to the valve point effects. Further, various constraints and factors, such as prohibited operation zones, ramp rate limits and security constraints imposed by the generating units, and power loss in transmission make it even more challenging to obtain the global optimum using conventional mathematical methods. Meta-heuristic approaches are capable of solving non-linear, non-continuous and non-convex problems effectively as they impose no requirements on the optimization problems. However, most methods reported so far mainly focus on a specific type of ED problems, such as static or dynamic ED problems. This paper proposes a hybrid harmony search with arithmetic crossover operation, namely ACHS, for solving five different types of ED problems, including static ED with valve point effects, ED with prohibited operating zones, ED considering multiple fuel cells, combined heat and power ED, and dynamic ED. In this proposed ACHS, the global best information and arithmetic crossover are used to update the newly generated solution and speed up the convergence, which contributes to the algorithm exploitation capability. To balance the exploitation and exploration capabilities, the opposition based learning (OBL) strategy is employed to enhance the diversity of solutions. Further, four commonly used crossover operators are also investigated, and the arithmetic crossover shows its efficiency than the others when they are incorporated into HS. To make a comprehensive study on its scalability, ACHS is first tested on a group of benchmark functions with a 100 dimensions and compared with several state-of-the-art methods. Then it is used to solve seven different ED cases and compared with the results reported in literatures. All the results confirm the superiority of the ACHS for different optimization problems.

A Conditional Approach for Modelling Patient Re-admissions in Hospital using a mixture of Coxian phase-type distributions incorporating Bayes Theorem

The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.

Exploiting evidence from unstructured data to enhance master data management

Master data management (MDM) integrates data from multiple
structured data sources and builds a consolidated 360-
degree view of business entities such as customers and products.
Today’s MDM systems are not prepared to integrate
information from unstructured data sources, such as news
reports, emails, call-center transcripts, and chat logs. However,
those unstructured data sources may contain valuable
information about the same entities known to MDM from
the structured data sources. Integrating information from
unstructured data into MDM is challenging as textual references
to existing MDM entities are often incomplete and
imprecise and the additional entity information extracted
from text should not impact the trustworthiness of MDM
data.
In this paper, we present an architecture for making MDM
text-aware and showcase its implementation as IBM InfoSphere
MDM Extension for Unstructured Text Correlation,
an add-on to IBM InfoSphere Master Data Management
Standard Edition. We highlight how MDM benefits from
additional evidence found in documents when doing entity
resolution and relationship discovery. We experimentally
demonstrate the feasibility of integrating information from
unstructured data sources into MDM.

Aspirin as a potential treatment in sepsis or acute respiratory distress syndrome

Sepsis is a common condition that is associated with significant morbidity, mortality and health-care cost. Pulmonary and non-pulmonary sepsis are common causes of the acute respiratory distress syndrome (ARDS). The mortality from ARDS remains high despite protective lung ventilation, and currently there are no specific pharmacotherapies to treat sepsis or ARDS. Sepsis and ARDS are characterised by activation of the inflammatory cascade. Although there is much focus on the study of the dysregulated inflammation and its suppression, the associated activation of the haemostatic system has been largely ignored until recently. There has been extensive interest in the role that platelet activation can have in the inflammatory response through induction, aggregation and activation of leucocytes and other platelets. Aspirin can modulate multiple pathogenic mechanisms implicated in the development of multiple organ dysfunction in sepsis and ARDS. This review will discuss the role of the platelet, the mechanisms of action of aspirin in sepsis and ARDS, and aspirin as a potential therapy in treating sepsis and ARDS.

Identity of a Tilapia Pheromone Released by Dominant Males that Primes Females for Reproduction

Knowledge of the chemical identity and role of urinary pheromones in fish is scarce, yet it is necessary in order to understand the integration of multiple senses in adaptive responses and the evolution of chemical communication [1]. In nature, Mozambique tilapia (Oreochromis mossambicus) males form hierarchies, and females mate preferentially with dominant territorial males, which they visit in aggregations or leks [2]. Dominant males have thicker urinary bladder muscular walls than subordinates or females and store large volumes of urine, which they release at increased frequency in the presence of subordinate males or preovulatory, but not postspawned, females [3–5]. Females exposed to dominant-male urine augment their release of the oocyte maturation-inducing steroid 17α,20β-dihydroxypregn-4-en-3-one (17,20β-P) [6]. Here we isolate and identify a male Mozambique tilapia urinary sex pheromone as two epimeric (20α- and 20β-) pregnanetriol 3-glucuronates. We show that both males and females have high olfactory sensitivity to the two steroids, which cross-adapt upon stimulation. Females exposed to both steroids show a rapid, 10-fold increase in production of 17,20β-P. Thus, the identified urinary steroids prime the female endocrine system to accelerate oocyte maturation and possibly promote spawning synchrony. Tilapia are globally important as a food source but are also invasive species, with devastating impact on local freshwater ecosystems [7, 8]. Identifying the chemical cues that mediate reproduction may lead to the development of tools for population control [9–11].

The use of biomarkers to diagnose the ecological impact of pollutants in Mediterranean rivers

Um assunto que requer atenção é a avaliação ecológica da qualidade da água de ecossistemas de água doce. Uma abordagem que surge como promissora é a biomonitorização baseada em biomarcadores, porque pode avaliar a saúde dos organismos e obter sinais de alerta precoce acerca dos riscos ambientais. Até agora, porém, o uso de biomarcadores em espécies de invertebrados, para diagnosticar danos ecológicos nos rios, é escasso. Por essa razão, existe uma necessidade urgente de desenvolver biomarcadores nas principais espécies de macroinvertebrados dos ecossistemas fluviais que são alvo de estudo. Esta tese tem como objectivo averiguar se as respostas in situ, aliadas aos biomarcadores, podem ser um método viável para avaliar os danos ecológicos de contaminantes em ecossistemas de água doce. Numa primeira fase, os biomarcadores foram usados para averiguar os mecanismos fisiológicos de adaptação genética de clones de Daphnia magna ao pesticida organofosforado fenitrothion. Numa segunda fase, os biomarcadores foram usados como ferramentas de diagnóstico de poluição em zonas ribeirinhas. Estes estudos foram realizados com três espécies-chave de macroinvertebrados: Daphnia magna, Corbicula fluminea e Hydropsyche exocellata, nos rios Besós e Llobregat e no Delta do rio Ebro (NE Espanha). Além disso, foram realizados com animais capturados nos rios, ou com ensaios de transplantes, e foram complementados com índices biológicos de macroinvertebrados e análises químicas da água e dos animais. Como os contaminantes químicos têm vários modos toxicológicos de acção e, portanto, afectam várias respostas bioquímicas dos organismos, foram analisados nas três espécies um conjunto de biomarcadores pertencentes a diferentes vias metabólicas. A abordagem experimental indica que o uso combinado de biomarcadores e outras medidas, tais como índices biológicos e testes in situ, contribui para diagnosticar os efeitos prejudiciais de contaminantes nas comunidades ribeirinhas.

Channel modelling for MIMO systems

Systems equipped with multiple antennas at the transmitter and at the receiver, known as MIMO (Multiple Input Multiple Output) systems, offer higher capacities, allowing an efficient exploitation of the available spectrum and/or the employment of more demanding applications. It is well known that the radio channel is characterized by multipath propagation, a phenomenon deemed problematic and whose mitigation has been achieved through techniques such as diversity, beamforming or adaptive antennas. By exploring conveniently the spatial domain MIMO systems turn the characteristics of the multipath channel into an advantage and allow creating multiple parallel and independent virtual channels. However, the achievable benefits are constrained by the propagation channel’s characteristics, which may not always be ideal. This work focuses on the characterization of the MIMO radio channel. It begins with the presentation of the fundamental results from information theory that triggered the interest on these systems, including the discussion of some of their potential benefits and a review of the existing channel models for MIMO systems. The characterization of the MIMO channel developed in this work is based on experimental measurements of the double-directional channel. The measurement system is based on a vector network analyzer and a two-dimensional positioning platform, both controlled by a computer, allowing the measurement of the channel’s frequency response at the locations of a synthetic array. Data is then processed using the SAGE (Space-Alternating Expectation-Maximization) algorithm to obtain the parameters (delay, direction of arrival and complex amplitude) of the channel’s most relevant multipath components. Afterwards, using a clustering algorithm these data are grouped into clusters. Finally, statistical information is extracted allowing the characterization of the channel’s multipath components. The information about the multipath characteristics of the channel, induced by existing scatterers in the propagation scenario, enables the characterization of MIMO channel and thus to evaluate its performance. The method was finally validated using MIMO measurements.

BIMP: A real-time biological model of multi-scale keypoint detection in V1

We present an improved, biologically inspired and multiscale keypoint operator. Models of single- and double-stopped hypercomplex cells in area V1 of the mammalian visual cortex are used to detect stable points of high complexity at multiple scales. Keypoints represent line and edge crossings, junctions and terminations at fine scales, and blobs at coarse scales. They are detected by applying first and second derivatives to responses of complex cells in combination with two inhibition schemes to suppress responses along lines and edges. A number of optimisations make our new algorithm much faster than previous biologically inspired models, achieving real-time performance on modern GPUs and competitive speeds on CPUs. In this paper we show that the keypoints exhibit state-of-the-art repeatability in standardised benchmarks, often yielding best-in-class performance. This makes them interesting both in biological models and as a useful detector in practice. We also show that keypoints can be used as a data selection step, significantly reducing the complexity in state-of-the-art object categorisation. (C) 2014 Elsevier B.V. All rights reserved.