Influence of Seabed Morphology and Substrate Composition On Mass-Transport Flow Processes and Pathways: Insights From the Magdalena Fan, Offshore Colombia

Although the effects of interactions between turbidity currents and the seabed have been widely studied, the roles of substrate and bathymetry on the emplacement of mass-transport complexes (MTCs) remain poorly constrained. This study investigates the effect of bathymetric variability and substrate heterogeneity on the distribution, morphology, and internal characteristics of nine MTCs imaged within a 3D seismic volume in the southern Magdalena Fan, offshore Colombia. The MTCs overlie substrate units composed mainly of channel–levee-complex sets, with subsidiary deposits of MTCs. MTC dispersal was influenced by tectonic relief, associated with a thin-skinned, deep-water fold-and-thrust belt, and by depositional relief, associated with the underlying channel–levee-complex sets; it was the former that exerted the first-order control on the location of mass-transport pathways. Channel–levee-complex sets channelized, diverted, or blocked mass flows, with the style of response largely controlled by their orientation with respect to the direction of the incoming flow and by the height of the levees with respect to flow thickness. MTC erosion can be relatively deep above channel-fill deposits, whereas more subtle erosional morphologies are observed above adjacent levee units. In the largest MTC, the distribution of the seismic facies is well imaged, being influenced by the underlying bathymetry, with internal horizontal contraction occurring updip of bathymetric highs, erosion and bypass predominating above higher gradient slopes, and increased disaggregation characterizing the margins. Hence, bathymetric irregularities and substrate heterogeneity together influence the pathways, geometries, and internal characteristics of MTCs, which could in turn influence flow rheology, runout distances, the presence and continuity of underlying reservoirs, and the capacity of MTCs to act as either hydrocarbon seals or reservoirs

Influence of Seabed Morphology and Substrate Composition On Mass-Transport Flow Processes and Pathways: Insights From the Magdalena Fan, Offshore Colombia

Although the effects of interactions between turbidity currents and the seabed have been widely studied, the roles of substrate and bathymetry on the emplacement of mass-transport complexes (MTCs) remain poorly constrained. This study investigates the effect of bathymetric variability and substrate heterogeneity on the distribution, morphology, and internal characteristics of nine MTCs imaged within a 3D seismic volume in the southern Magdalena Fan, offshore Colombia. The MTCs overlie substrate units composed mainly of channel–levee-complex sets, with subsidiary deposits of MTCs. MTC dispersal was influenced by tectonic relief, associated with a thin-skinned, deep-water fold-and-thrust belt, and by depositional relief, associated with the underlying channel–levee-complex sets; it was the former that exerted the first-order control on the location of mass-transport pathways. Channel–levee-complex sets channelized, diverted, or blocked mass flows, with the style of response largely controlled by their orientation with respect to the direction of the incoming flow and by the height of the levees with respect to flow thickness. MTC erosion can be relatively deep above channel-fill deposits, whereas more subtle erosional morphologies are observed above adjacent levee units. In the largest MTC, the distribution of the seismic facies is well imaged, being influenced by the underlying bathymetry, with internal horizontal contraction occurring updip of bathymetric highs, erosion and bypass predominating above higher gradient slopes, and increased disaggregation characterizing the margins. Hence, bathymetric irregularities and substrate heterogeneity together influence the pathways, geometries, and internal characteristics of MTCs, which could in turn influence flow rheology, runout distances, the presence and continuity of underlying reservoirs, and the capacity of MTCs to act as either hydrocarbon seals or reservoirs

Using Computer Simulation for Reducing the Appointment Lead-Time in a Public Pediatric Outpatient Department

Pediatric outpatient departments aim to provide a pleasant, effective and continuing care to children. However, a problem in these units is the long waiting time for children to receive an appointment. Prolonged appointment lead-time remains a global challenge since it results in delayed diagnosis and treatment causing increased morbidity and dissatisfaction. Additionally, it leads to an increased number of hospitalization and emergency department visits which augments the financial burden faced by healthcare systems. Despite these considerations, the studies directly concentrating on the reduction of appointment lead-time in these departments are largely limited. Therefore, this paper proposes the application of Discrete-event Simulation (DES) approach to evaluate potential improvement strategies aiming at reducing average appointment lead-time. Initially, the outpatient department is characterized to effectively identify the main activities, process variables, interactions, and system constraints. After data collection, input analysis is conducted through intra-variable independence, homogeneity and goodness-of-fit tests followed by the creation of a simulation model representing the real pediatric outpatient department. Then, Mann-Whitney tests are used to prove whether the model was statistically comparable with the real-world system. After this, the outpatient department performance is assessed in terms of average appointment lead-time and resource utilization. Finally, three improvement scenarios are assessed technically and financially, to determine if they are viable for implementation. A case study of a mixed-patient type environment in a public pediatric outpatient department has been explored to validate the proposed methodology. Statistical tests demonstrate that appointment lead-time in pediatric outpatient departments may be meaningfully minimized using this approach. © 2019, Springer Nature Switzerland AG

Integrating Lean Six Sigma and discrete-event simulation for shortening the appointment lead-time in gynecobstetrics departments: a case study

Long waiting time to appointment may be a worry for pregnant women, particularly those who need perinatology consultation since it could increase anxiety and, in a worst case scenario, lead to an increase in fetal, infant, and maternal mortality. Treatment costs may also increase since pregnant women with diverse pathologies can develop more severe complications. As a step towards improving this process, we propose a methodological approach to reduce the appointment lead-time in outpatient gynecobstetrics departments. This framework involves combining the Six Sigma method to identify defects in the appointment scheduling process with a discrete-event simulation (DES) to evaluate the potential success of removing such defects in simulation before we resort to changing the real-world healthcare system. To do these, we initially characterize the gynecobstetrics department using a SIPOC diagram. Then, six sigma performance metrics are calculated to evaluate how well the department meets the government target in relation to the appointment lead-time. Afterwards, a cause-and-effect analysis is undertaken to identify potential causes of appointment lead-time variation. These causes are later validated through ANOVA, regression analysis, and DES. Improvement scenarios are next designed and pretested through computer simulation models. Finally, control plans are deployed to maintain the results achieved through the implementation of the DES-Six sigma approach. The aforementioned framework was validated in a public gynecobstetrics outpatient department. The results revealed that mean waiting time decreased from 6.9 days to 4.1 days while variance passed from 2.46 days2 to 1.53 days2

Hybridization between wild and cultivated potato species in the Peruvian Andes and biosafety implications for deployment of GM potatoes

The nature and extent of past and current hybridization between cultivated potato and wild relatives in nature is of interest to crop evolutionists, taxonomists, breeders and recently to molecular biologists because of the possibilities of inverse gene flow in the deployment of genetically-modified (GM) crops. This research proves that natural hybridization occurs in areas of potato diversity in the Andes, the possibilities for survival of these new hybrids, and shows a possible way forward in case of GM potatoes should prove advantageous in such areas

Determination of the Fermion Pair Size in a Resonantly Interacting Superfluid

Fermionic superfluidity requires the formation of pairs. The actual size of these fermion pairs varies by orders of magnitude from the femtometer scale in neutron stars and nuclei to the micrometer range in conventional superconductors. Many properties of the superfluid depend on the pair size relative to the interparticle spacing. This is expressed in BCS-BEC crossover theories, describing the crossover from a Bardeen-Cooper-Schrieffer (BCS) type superfluid of loosely bound and large Cooper pairs to Bose-Einstein condensation (BEC) of tightly bound molecules. Such a crossover superfluid has been realized in ultracold atomic gases where high temperature superfluidity has been observed. The microscopic properties of the fermion pairs can be probed with radio-frequency (rf) spectroscopy. Previous work was difficult to interpret due to strong and not well understood final state interactions. Here we realize a new superfluid spin mixture where such interactions have negligible influence and present fermion-pair dissociation spectra that reveal the underlying pairing correlations. This allows us to determine the spectroscopic pair size in the resonantly interacting gas to be 2.6(2)/kF (kF is the Fermi wave number). The pairs are therefore smaller than the interparticle spacing and the smallest pairs observed in fermionic superfluids. This finding highlights the importance of small fermion pairs for superfluidity at high critical temperatures. We have also identified transitions from fermion pairs into bound molecular states and into many-body bound states in the case of strong final state interactions.Comment: 8 pages, 7 figures; Figures updated; New Figures added; Updated discussion of fit function

Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies

An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)’s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Uniform electron gases

We show that the traditional concept of the uniform electron gas (UEG) --- a homogeneous system of finite density, consisting of an infinite number of electrons in an infinite volume --- is inadequate to model the UEGs that arise in finite systems. We argue that, in general, a UEG is characterized by at least two parameters, \textit{viz.} the usual one-electron density parameter $\rho$ and a new two-electron parameter $\eta$. We outline a systematic strategy to determine a new density functional $E(\rho,\eta)$ across the spectrum of possible $\rho$ and $\eta$ values.Comment: 8 pages, 2 figures, 5 table

The Clinical Alliance and Research in Electroconvulsive Therapy Network: An Australian Initiative for Improving Service Delivery of Electroconvulsive Therapy

Objective There is currently substantial heterogeneity in electroconvulsive therapy (ECT) treatment methods between clinical settings. Understanding how this variation in clinical practice is related to treatment outcomes is essential for optimizing service delivery. The Clinical Alliance and Research in ECT Network is a clinical and research framework with the aims of improving clinical practice, enabling auditing and benchmarking, and facilitating the collection of naturalistic clinical data. Methods The network framework and clinical and treatment variables collected and rationale for the use of particular outcome measures are described. Survey results detailing the use of ECT across initial participating clinical centers were examined. Results The data are reported from 18 of 22 participating centers, the majority based in Australia. Melancholic unipolar depression was the most common clinical indication (78%). Right unilateral (44%) and bifrontal (39%) were the most commonly used electrode placements. Eighty one percent of the centers used individual seizure titration for initial dosing. Conclusions There was substantial heterogeneity in the use of ECT between participating centers, indicating that the Network is representative of modern ECT practice. The Clinical Alliance and Research in ECT Network may therefore offer the opportunity to improve service delivery and facilitate the investigation of unresolved research questions pertaining to modern ECT practice