136 resultados para Rosa multiflora


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This paper demonstrates the integration and usage of Process Query Language (PQL), a special-purpose programming language for querying large collections of process models based on process model behavior, in the Apromore open-source process model repository. The resulting environment provides a unique user experience when carrying out process model querying tasks. The tool is useful for researchers and practitioners working with large process model collections, and specifically for those with an interest in model retrieval tasks as part of process compliance, process redesign and process standardization initiatives.

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In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.

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The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

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Familial juvenile hyperuricaemic (gouty) nephropathy (FJHN), is an autosomal dominant disease associated with a reduced fractional excretion of urate, and progressive renal failure. FJHN is genetically heterogeneous and due to mutations of three genes: uromodulin (UMOD), renin (REN) and hepatocyte nuclear factor-1beta (HNF-1β) on chromosomes 16p12, 1q32.1, and 17q12, respectively. However, UMOD, REN or HNF-1β mutations are found in only ~45% of FJHN probands, indicating the involvement of other genetic loci in ~55% of probands. To identify other FJHN loci, we performed a single nucleotide polymorphism (SNP)-based genome-wide linkage analysis, in six FJHN families in whom UMOD, HNF-1β and REN mutations had been excluded. Parametric linkage analysis using a 'rare dominant' model established linkage in five of the six FJHN families, with a LOD score >+3, at 0% recombination, between FJHN and SNPs at chromosome 2p22.1-p21. Analysis of individual recombinants in two unrelated affected individuals defined a ~5.5 Mbp interval, flanked telomerically by SNP RS372139 and centromerically by RS896986 that contained the locus, designated FJHN3. The interval contains 28 genes, and DNA sequence analysis of the most likely candidate, solute carrier family 8 member 1 (SLC8A1), did not identify any abnormalities in the FJHN3 probands. FJHN3 is likely located within a ~5.5 Mbp interval on chromosome 2p22.1-p21, and identifying the genetic abnormality will help to further elucidate mechanisms predisposing to gout and renal failure.

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New Video Gamer: Africa Needs More Technology (CNN 12/12/2011) In December 2011 CNN news service online edition (Sutter, 2011) posted a short item about Cwi Nqane, a Khoisan man who entered Samsung’s Namibian World Cyber Games (WCG) heats held at the 2011 the annual Windhoek Show. Cwi Nqane won a place on the Namibian WCG team playing a smartphone game called Asphalt 6: Adrena-line (Gameloft, 2011). Cwi was presented with a ‘top of the line’ Samsung Galaxy tablet and subsequently sent to compete in Korea. Later, other news and game news websites re-reported the incident, which inspired a variety of enthusiastic comment about tech-nology and ‘new knowledge’. Then Kotaku news service picked up the item (Narcisse, 2011) and took a very different slant. Kotaku proposed that Samsung was exploiting Cwi and had assumed the role of a Techno-Tarzan: “striding into Nqane’s homeland and swinging him off into the wonders of the modern world where they can trot him out as a curiosity”. These two perspectives on the story of Cwi’s WCG entry expose two dominant views on Indigenous knowledges and technologies: ICTs as progress for in-digenous peoples and ICTs as disruptive and exploitative. Neither position, however, allows for the claiming of digital technology by indigenous communities, indeed both views position indigenous cultures as being outsiders.

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Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available.

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Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

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This paper addresses the following predictive business process monitoring problem: Given the execution trace of an ongoing case,and given a set of traces of historical (completed) cases, predict the most likely outcome of the ongoing case. In this context, a trace refers to a sequence of events with corresponding payloads, where a payload consists of a set of attribute-value pairs. Meanwhile, an outcome refers to a label associated to completed cases, like, for example, a label indicating that a given case completed “on time” (with respect to a given desired duration) or “late”, or a label indicating that a given case led to a customer complaint or not. The paper tackles this problem via a two-phased approach. In the first phase, prefixes of historical cases are encoded using complex symbolic sequences and clustered. In the second phase, a classifier is built for each of the clusters. To predict the outcome of an ongoing case at runtime given its (uncompleted) trace, we select the closest cluster(s) to the trace in question and apply the respective classifier(s), taking into account the Euclidean distance of the trace from the center of the clusters. We consider two families of clustering algorithms – hierarchical clustering and k-medoids – and use random forests for classification. The approach was evaluated on four real-life datasets.

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Objective: This study examined associations of asthma and food allergy with symptoms of depression and anxiety at 14 and 21 years of age to determine whether condition-specific associations exist. Methods: Data come from 4972 adolescents in the Mater University Study of Pregnancy. Symptoms of depression and anxiety were assessed using the Youth Self-Report and Young Adult Self-Report. Results: Condition-specific associations between asthma and depression, OR=1.37 [1.12, 1.67] and between food allergy and anxiety, OR=1.26 [1.04, 1.76] were found during adolescence, but not in young adulthood. Whereas asthma was associated with resolved depression, OR=1.70 [1.13, 2.55], food allergy was associated with persistent anxiety, OR=1.26 [1.01, 1.59]. Conclusions: In adolescents, asthma is associated with an increased risk of clinically relevant symptoms of depression and food allergy with and increased risk of clinically relevant symptoms of anxiety. Future research is needed to clarify directionality and mechanisms explaining these relationships. Health professionals should be aware of the increased risk of mental health problems in adolescents with asthma or food allergy.

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An FAO/IAEA Co-ordinated Research Project (CRP) on “Resolution of Cryptic Species Complexes of Tephritid Pests to Overcome Constraints to SIT Application and International Trade” was conducted from 2010 to 2015. As captured in the CRP title, the objective was to undertake targeted research into the systematics and diagnostics of taxonomically challenging fruit fly groups of economic importance. The scientific output was the accurate alignment of biological species with taxonomic names; which led to the applied outcome of assisting FAO and IAEA Member States in overcoming technical constraints to the application of the Sterile Insect Technique (SIT) against pest fruit flies and the facilitation of international agricultural trade. Close to 50 researchers from over 20 countries participated in the CRP, using coordinated, multidisciplinary research to address, within an integrative taxonomic framework, cryptic species complexes of major tephritid pests. The following progress was made for the four complexes selected and studied: Anastrepha fraterculus complex – Eight morphotypes and their geographic and ecological distributions in Latin America were defined. The morphotypes can be considered as distinct biological species on the basis of differences in karyotype, sexual incompatibility, post-mating isolation, cuticular hydrocarbon, pheromone, and molecular analyses. Discriminative taxonomic tools using linear and geometric morphometrics of both adult and larval morphology were developed for this complex. Bactrocera dorsalis complex – Based on genetic, cytogenetic, pheromonal, morphometric, and behavioural data, which showed no or only minor variation between the Asian/African pest fruit flies Bactrocera dorsalis, B. papayae, B. philippinensis and B. invadens, the latter three species were synonymized with B. dorsalis. Of the five target pest taxa studied, only B. dorsalis and B. carambolae remain as scientifically valid names. Molecular and pheromone markers are now available to distinguish B. dorsalis from B. carambolae. Ceratitis FAR Complex (C. fasciventris, C. anonae, C. rosa) – Morphology, morphometry, genetic, genomic, pheromone, cuticular hydrocarbon, ecology, behaviour, and developmental physiology data provide evidence for the existence of five different entities within this fruit fly complex from the African region. These are currently recognised as Ceratitis anonae, C. fasciventris (F1 and F2), C. rosa and a new species related to C. rosa (R2). The biological limits within C. fasciventris (i.e. F1 and F2) are not fully resolved. Microsatellites markers and morphological identification tools for the adult males of the five different FAR entities were developed based on male leg structures. Zeugodacus cucurbitae (formerly Bactrocera (Zeugodacus) cucurbitae) – Genetic variability was studied among melon fly populations throughout its geographic range in Africa and the Asia/Pacific region and found to be limited. Cross-mating studies indicated no incompatibility or sexual isolation. Host preference and genetic studies showed no evidence for the existence of host races. It was concluded that the melon fly does not represent a cryptic species complex, neither with regard to geographic distribution nor to host range. Nevertheless, the higher taxonomic classification under which this species had been placed, by the time the CRP was started, was found to be paraphyletic; as a result the subgenus Zeugodacus was elevated to genus level.

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This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

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Introduction and Objectives Joint moments and joint powers during gait are widely used to determine the effects of rehabilitation programs as well as prosthetic fitting. Following the definition of power (dot product of joint moment and joint angular velocity) it has been previously proposed to analyse the 3D angle between both vectors, αMw. Basically, joint power is maximised when both vectors are parallel and cancelled when both vectors are orthogonal. In other words, αMw < 60° reveals a propulsion configuration (more than 50% of the moment contribute to positive power) while αMw > 120° reveals a resistance configuration (more than 50% of the moment contribute to negative power). A stabilisation configuration (less than 50% of the moment contribute to power) corresponds to 60° < αMw < 120°. Previous studies demonstrated that hip joints of able-bodied adults (AB) are mainly in a stabilisation configuration (αMw about 90°) during the stance phase of gait. [1, 2] Individuals with transfemoral amputation (TFA) need to maximise joint power at the hip while controlling the prosthetic knee during stance. Therefore, we tested the hypothesis that TFAs should adopt a strategy that is different from a continuous stabilisation. The objective of this study was to compute joint power and αMw for TFA and to compare them with AB. Methods Three trials of walking at self-selected speed were analysed for 8 TFAs (7 males and 1 female, 46±10 years old, 1.78±0.08 m 82±13 kg) and 8 ABs (males, 25±3 years old, 1.75±0.04, m 67±6 kg). The joint moments are computed from a motion analysis system (Qualisys, Goteborg, Sweden) and a multi-axial transducer (JR3, Woodland, USA) mounted above the prosthetic knee for TFAs and from a motion analysis system (Motion Analysis, Santa Rosa, USA) and force plates (Bertec, Columbus, USA) for ABs. The TFAs were fitted with an OPRA (Integrum, AB, Gothengurg, Sweden) osseointegrated implant system and their prosthetic designs include pneumatic, hydraulic and microprocessor knees. Previous studies showed that the inverse dynamics computed from the multi-axial transducer is the proper method considering the absorption at the foot and resistance at the knee. Results The peak of positive power at loading response (H1) was earlier and lower for TFA compared to AB. Although the joint power is lower, the 3D angle between joint moment and joint angular velocity, αMw, reveals an obvious propulsion configuration (mean αMw about 20°) for TFA compared to a stabilisation configuration (mean αMw about 70°) for AB. The peaks of negative power at midstance (H2) and of positive power at preswing / initial swing (H3) occurred later, lower and longer for TFA compared to AB. Again, the joint powers are lower for TFA but, in this case, αMw is almost comparable (with a time lag), demonstrating a stabilisation (almost a resistance for TFA, mean αMw about 120°) and a propulsion configuration, respectively. The swing phase is not analysed in the present study. Conclusion The analysis of hip joint power may indicate that TFAs demonstrated less propulsion and resistance than ABs during the stance phase of gait. This is true from a quantitative point of view. On the contrary, the 3D angle between joint moment and joint angular velocity, αMw, reveals that TFAs have a remarkable propulsion strategy at loading response and almost a resistance strategy at midstance while ABs adopted a stabilisation strategy. The propulsion configuration, with αMw close to 0°, seems to aim at maximising the positive joint power. The configuration close to resistance, with αMw far from 180°, might aim at unlocking the prosthetic knee before swing while minimising the negative power. This analysis of both joint power and 3D angle between the joint moment and the joint angular velocity provides complementary insights into the gait strategies of TFA that can be used to support evidence-based rehabilitation and fitting of prosthetic components.

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A play in two parts on the subject of racism. Part One presents the story of the Montgomery bus boycott arising from the refusal of Rosa Parkes to give up her seat on a bus and leading to the rise of Martin Luther King, Jr. Part Two is set in contemporary Australia, in the household of a group of young people who re-create the sixties' Freedom Ride in order to heal the spirit of Auntie, an Aboriginal woman, who is the centre of their world.

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An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called ‘Meltdown’, performs a number of data remediation steps before classifying melt curves and estimating melting temperatures. The final output is a report that summarizes the results of a differential scanning fluorimetry experiment. Meltdown uses a Bayesian classification scheme, enabling reproducible identification of various trends commonly found in DSF datasets. The goal of Meltdown is not to replace human analysis of the raw data, but to provide a sensible interpretation of the data to make this useful experimental technique accessible to naïve users, as well as providing a starting point for detailed analyses by more experienced users.

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This paper addresses the problem of discovering business process models from event logs. Existing approaches to this problem strike various tradeoffs between accuracy and understandability of the discovered models. With respect to the second criterion, empirical studies have shown that block-structured process models are generally more understandable and less error-prone than unstructured ones. Accordingly, several automated process discovery methods generate block-structured models by construction. These approaches however intertwine the concern of producing accurate models with that of ensuring their structuredness, sometimes sacrificing the former to ensure the latter. In this paper we propose an alternative approach that separates these two concerns. Instead of directly discovering a structured process model, we first apply a well-known heuristic technique that discovers more accurate but sometimes unstructured (and even unsound) process models, and then transform the resulting model into a structured one. An experimental evaluation shows that our “discover and structure” approach outperforms traditional “discover structured” approaches with respect to a range of accuracy and complexity measures.