Does leptin predict successful induction of labor?

Obesity in pregnancy is becoming increasingly common and is associated with many pregnancy-related complications such as failed induction of labor (IOL). Leptin, an adipocytokine important in energy homeostasis, is found in higher levels in obese individuals. Leptin has also been demonstrated to have an inhibitory effect on myometrial contractility in vitro. We hypothesize that leptin may play a part in the mechanism of dysfunctional labor. Thus, we sought to compare the maternal plasma leptin levels in women that had a successful vaginal delivery post-IOL vs. those who had a C-section post-IOL

Recovery from cesarean delivery at UIHC: a comparison to Enhanced Recovery Protocols

Enhanced Recovery After Surgery programs (ERAS) have been used by some specialties for years, and are now becoming popular for gynecologic and obstetrics surgeries. ERAS programs consist of evidence-based interventions during a patient’s hospital stay that are intended to promote early return to activities such as eating, ambulation, and voiding and to manage pain. These programs reduce the risk of complications post-operatively and shorten a patient’s hospital stay. The University of Iowa Hospitals and Clinics (UIHC) is developing an ERAS protocol for cesarean deliveries. Our goal was to determine how current practices and outcomes for cesarean deliveries at UIHC compare to established ERAS programs. We also sought to identify which patients would be appropriate candidates for an ERAS protocol at UIHC

USING GHSL TO ANALYZE URBANIZATION AND LAND-USE EFFICIENCY IN THE PHILIPPINES FROM 1975–2020: TRENDS AND IMPLICATIONS FOR SUSTAINABLE DEVELOPMENT

This study analyzed the trends and patterns of urbanization and changes in land-use efficiency in the Philippines from 1975–2020 using the Global Human Settlement Layers (GHSL). Utilizing the GHS-BUILT-S, GHS POP, and GHS-SMOD raster datasets from the GHSL Data Package 2023, we examined the spatiotemporal expansion of built-up areas and the growth of population in urban and rural regions of the country. Using the same datasets, we also measured the country's achievement of Sustainable Development Goal (SDG)11.3, particularly on inclusive and sustainable urbanization through efficient land utilization, by computing the ratio of land consumption rate (LCR) to the population growth rate (PGR), also known as LCRPGR. The results of our analysis revealed an increasing trend in the overall built-up area and population of the Philippines within the examined period. Built-up areas and population in urban regions more than tripled in size from 1975 to 2020, demonstrating a notable shift towards more urbanized regions over time. In addition to presenting evidence of the Philippines' developmental progress and urbanization, our analysis of GHSL data shows a decline in land consumption, a deceleration in population growth, and an overall enhancement in land-use efficiency within the country. These findings suggest a shift towards more controlled and sustainable land development practices, supporting the country's goal of sustainable urbanization and land management. The implications of these findings are crucial for policymakers and urban planners in the Philippines, offering valuable insights to guide the formulation of effective and comprehensive land management strategies. Further work includes conducting localized analyses at the city or municipality level to provide valuable insights into the unique urbanization patterns and land-use dynamics across different islands and regions, enabling tailored policy interventions and spatial planning strategies to promote sustainable development

Interplay between Microorganisms and Geochemistry in Geological Carbon Storage

Citation: Kirk, MF, Altman, SJ, Santillan, EFU, Bennett, PC (2016) Interplay between microorganisms and geochemistry in geological carbon storage. International Journal of Greenhouse Gas Control 47, 386-395.Researchers at the Center for Frontiers of Subsurface Energy Security (CFSES) have conducted laboratory and modeling studies to better understand the interplay between microorganisms and geochemistry for geological carbon storage (GCS). We provide evidence of microorganisms adapting to high pressure CO2 conditions and identify factors that may influence survival of cells to CO2 stress. Factors that influenced the ability of cells to survive exposure to high-pressure CO2 in our experiments include mineralogy, the permeability of cell walls and/or membranes, intracellular buffering capacity, and whether cells live planktonically or within biofilm. Column experiments show that, following exposure to acidic water, biomass can remain intact in porous media and continue to alter hydraulic conductivity. Our research also shows that geochemical changes triggered by CO2 injection can alter energy available to populations of subsurface anaerobes and that microbial feedbacks on this effect can influence carbon storage. Our research documents the impact of CO2 on microorganisms and in turn, how subsurface microorganisms can influence GCS. We conclude that microbial presence and activities can have important implications for carbon storage and that microorganisms should not be overlooked in further GCS research

Preference incorporation in MOEA/D using an outranking approach with imprecise model parameters

Multi-objective Optimization Evolutionary Algorithms (MOEAs) face numerous challenges when they are used to solve Many-objective Optimization Problems (MaOPs). Decomposition-based strategies, such as MOEA/D, divide an MaOP into multiple single-optimization sub-problems, achieving better diversity and a better approximation of the Pareto front, and dealing with some of the challenges of MaOPs. However, these approaches still require one to solve a multi-criteria selection problem that will allow a Decision-Maker (DM) to choose the final solution. Incorporating preferences may provide results that are closer to the region of interest of a DM. Most of the proposals to integrate preferences in decomposition-based MOEAs prefer progressive articulation over the “a priori” incorporation of preferences. Progressive articulation methods can hardly work without comparable and transitive preferences, and they can significantly increase the cognitive effort required of a DM. On the other hand, the “a priori” strategies do not demand transitive judgements from the DM but require a direct parameter elicitation that usually is subject to imprecision. Outranking approaches have properties that allow them to suitably handle non-transitive preferences, veto conditions, and incomparability, which are typical characteristics of many real DMs. This paper explores how to incorporate DM preferences into MOEA/D using the “a priori” incorporation of preferences, based on interval outranking relations, to handle imprecision when preference parameters are elicited. Several experiments make it possible to analyze the proposal's performance on benchmark problems and to compare the results with the classic MOEA/D without preference incorporation and with a recent, state-of-the-art preference-based decomposition algorithm. In many instances, our results are closer to the Region of Interest, particularly when the number of objectives increases

Complete Calabi-Yau metrics from Kahler metrics in D=4

In the present work the local form of certain Calabi-Yau metrics possessing a local Hamiltonian Killing vector is described in terms of a single non linear equation. The main assumptions are that the complex $(3,0)$-form is of the form $e^{ik}\widetilde{\Psi}$, where $\widetilde{\Psi}$ is preserved by the Killing vector, and that the space of the orbits of the Killing vector is, for fixed value of the momentum map coordinate, a complex 4-manifold, in such a way that the complex structure of the 4-manifold is part of the complex structure of the complex 3-fold. The link with the solution generating techniques of [26]-[28] is made explicit and in particular an example with holonomy exactly SU(3) is found by use of the linearization of [26], which was found in the context of D6 branes wrapping a holomorphic 1-fold in a hyperkahler manifold. But the main improvement of the present method, unlike the ones presented in [26]-[28], does not rely in an initial hyperkahler structure. Additionally the complications when dealing with non linear operators over the curved hyperkahler space are avoided by use of this method.Comment: Version accepted for publication in Phys.Rev.

NEAR-REAL TIME HAZARD MONITORING AND INFORMATION DISSEMINATION THROUGH INTEGRATION OF REMOTE SENSING, GIS, NUMERICAL MODELLING, WEB APPLICATIONS AND SOCIAL MEDIA

In mitigating and helping lessen the possible effects and damages of disaster to the communities, the transmission of information or end products derived from remote sensing and other multidisciplinary technologies into the community should be immediate, accessible and comprehensive to aid in better planning and decision-making procedures. In this paper, we share a hazard information dissemination procedure which integrates the use of outputs derived from numerical models, web applications and systems as well as the use of social media and telecommunications to promote the utilization of advanced science and technology outputs that could represent and visualize various flooding scenarios through social media and dynamic communication between stakeholders

An ACO-based Hyper-heuristic for Sequencing Many-objective Evolutionary Algorithms that Consider Different Ways to Incorporate the DM's Preferences

Many-objective optimization is an area of interest common to researchers, professionals, and practitioners because of its real-world implications. Preference incorporation into Multi-Objective Evolutionary Algorithms (MOEAs) is one of the current approaches to treat Many-Objective Optimization Problems (MaOPs). Some recent studies have focused on the advantages of embedding preference models based on interval outranking into MOEAs; several models have been proposed to achieve it. Since there are many factors influencing the choice of the best outranking model, there is no clear notion of which is the best model to incorporate the preferences of the decision maker into a particular problem. This paper proposes a hyper-heuristic algorithm—named HyperACO—that searches for the best combination of several interval outranking models embedded into MOEAs to solve MaOPs. HyperACO is able not only to select the most appropriate model but also to combine the already existing models to solve a specific MaOP correctly. The results obtained on the DTLZ and WFG test suites corroborate that HyperACO can hybridize MOEAs with a combined preference model that is suitable to the problem being solved. Performance comparisons with other state-of-the-art MOEAs and tests for statistical significance validate this conclusion

New non compact Calabi-Yau metrics in D=6

A method for constructing explicit Calabi-Yau metrics in six dimensions in terms of an initial hyperkahler structure is presented. The equations to solve are non linear in general, but become linear when the objects describing the metric depend on only one complex coordinate of the hyperkahler 4-dimensional space and its complex conjugated. This situation in particular gives a dual description of D6-branes wrapping a complex 1-cycle inside the hyperkahler space, which was studied by Fayyazuddin. The present work generalize the construction given by him. But the explicit solutions we present correspond to the non linear problem. This is a non linear equation with respect to two variables which, with the help of some specific anzatz, is reduced to a non linear equation with a single variable solvable in terms of elliptic functions. In these terms we construct an infinite family of non compact Calabi-Yau metrics.Comment: A numerical error has been corrected together with the corresponding analysis of the metri