bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidental presence of non recurrent laryngeal nerve in our series of thyroidectomy
Authors: Bage Atul M. , Muthuvel Lakshman Bhaskar , A. C. Akshaya , Bage Nutan N. 
Published: March 2019

<p class="abstract"><strong>Background:</strong> Recurrent laryngeal nerve (RLN) injury is one of the most important and preventable complications of thyroidectomy which is the cause of post-operative iatrogenic vocal cord paralysis. The non-recurrent laryngeal nerve (NRLN), which is found in 0.25–0.99 of the patients who undergo thyroid surgery, is a rare embryologically-derived variant of the recurrent laryngeal nerve (RLN). Identification and prevention of injury to the laryngeal nerve is very important in thyroid surgery. The objective of the study was to highlight the incidence of Non-recurrent laryngeal nerve in our series of thyroidectomy cases.</p><p class="abstract"><strong>Methods:</strong> In the Department of Otorhinolaryngology, Pondicherry a retrospective analysis of all the thyroid surgeries that were operated between August 2006-November 2018 for various indications on a total of 1006 patients was done with specific interest in the lookout for anatomical variant of recurrent laryngeal nerve and findings were recorded. </p><p class="abstract"><strong>Results:</strong> Among all the cases, two patients with MNG who had underwent Total thyroidectomy were found to have anatomical variants of recurrent laryngeal nerve (non recurrent laryngeal nerve) intra operatively.</p><p class="abstract"><strong>Conclusions:</strong> The NRLN is a rare finding and is associated to an increased risk in iatrogenic injury especially during thyroid surgeries unless thorough anatomical knowledge and cautious dissection is not done.</p><p> </p>
In the Shadow of Ghadar: Marxism and Anti-Colonialism in Colonial Punjab
Authors: Jan Ammar Ali 
Published: March 2019

The Ghadr Party, an eclectic group of diasporic Punjabis, was perhaps one of the most significant political movements led by emigre Indians in the early twentieth century. Designated as one of the biggest threats to colonial rule in the 1910s, the Ghadr Party spread its operations over five continents, and repeatedly committed acts of sabotage aimed at colonial officials from India. By the 1920s, however, the birth of popular movements in India marginalized various groups that believed in the spectacular actions of a vanguard as a strategy for overcoming the stifling impact of colonial rule. Members of the party, eager to find a foothold in the changed political scenario, opened discussions for building a popular front in Punjab, with many returning to the country to participate in such an endeavour. In this article, I study the encounter between the Ghadarite tradition and the communist movement in colonial Punjab through the writings of Sohan Singh Josh, who attempted to bring these two traditions together to produce a viable political project. I argue that Ghadar's encounter with Marxism not only influenced the former, but also radically transformed Marxism itself, particularly on questions of History, violence and volition.
DECOLONIZING GHADAR
Authors: Dhami Mandavni 
Published: March 2019

This paper confronts the unspoken/unwritten patriarchal and settler colonial roots of Ghadar and its history through Toni Morrison’s ([1987] 2008) method of using imagination to construct re-memories of the truths that dominant histories erase. To do this, this paper draws on feminist critiques of the state, the private/public divide, the individual/citizen, and manhood/masculinities (Bederman [1995] 2006; Kaplan [2002] 2006; Pateman [1983] 2006; Pettman [1996] 2006) and thereby genders Radha D’Souza’s discussion of the colonial/imperial disconnecting of people from places (2014, 63). Focussing on the Punjabi context, this paper takes up Ghadarites’ employment of the private/public divide, their manipulation of patriarchal power, their appropriation of women’s bodies/voices, and their participation in “logic[s] of genocide” (Smith 2011, 51) as means of claiming access to citizen/political rights. Ultimately, it is argued that Ghadar was a movement for access to manhood power, whiteness and settler coloniality.
Advanced Maternal Age: Adverse Outcomes of Pregnancy, A Meta-Analysis
Authors: Pinheiro Rosa Lomelino , Areia Ana Luísa , Mota Pinto Anabela , Donato Helena 
Published: March 2019

Introduction: The risks of pregnancy in women of advanced maternal age are not consensual amongst studies. The aim of this metaanalysis was to determine whether women of advanced maternal age (≥ 35 years old) had worse obstetrical and perinatal outcomes than non- advanced maternal age women (20 - 34 years old) in singleton, naturally-conceived pregnancies.Material and Methods: We searched PubMed/ MEDLINE, IndexRMP and the Cochrane Database of Systematic Reviews. Ten studies were included according to the following criteria: population of > 1000 nulliparous and/or multiparous women with singleton gestations who did not undergo any type of infertility treatment. Using Review Manager v. 5.3, two meta-analysis were performed: one comparing the outcomes of 20 - 34-year-old vs 35 - 40-year-old women, and another comparing the outcomes of 35 - 40-year-old women vs > 40-year-old women.Results: Women aged 35 - 40 years old were more likely to have > 12 years of education than 20 - 34 years old and > 40 years old women. Advanced maternal age women (35 - 40 and > 40 years old) were more likely to be overweight and having gestational diabetes and gestational hypertension. They were also more likely to undergo induced labour and elective caesarean deliveries. Furthermore, they had worse perinatal outcomes such as preterm delivery, low birthweight babies, higher rates of Neonatal Intensive Care Unit admission and worse Apgar scores. Advanced maternal age women had higher rates of perinatal mortality and stillbirth.Discussion: Most authors present similar results to our study. Although the majority of adverse outcomes can be explained through the physio-pathological changes regarding the female reproductive apparatus that come with aging and its inherent comorbidities, according to the existing literature advanced maternal age can be an independent risk factor per se. In older pregnant women without comorbidities such as gestational hypertension or diabetes there are still worse obstetric and perinatal outcomes, which indicate that advanced maternal age is an independent strong risk factor alone.Conclusion: Advanced maternal age women are at a higher risk of adverse obstetrical and perinatal outcomes. In both comparisons, worse outcomes were more prevalent in the older group, suggesting that poorer outcomes are more prevalent with increasing age.
LC-MS/MS based targeted metabolomics method for analysis of serum and cerebrospinal fluid
Authors: Plewa Szymon , Dereziński Paweł , Florczak-Wyspiańska Jolanta , Popławska-Domaszewicz Karolina , Kozubski Wojciech , Sokół Bartosz , Jankowski Roman , Matysiak Jan , Kokot Zenon J. 
Published: March 2019

Introduction. Recent instrumentation and software advancement enabled to develop new, high‑throughput targeted metabolomics methods for in‑depth exploration of metabolome in a quantitative manner.Material and Methods. The presented targeted metabolomics approach allows to analyze both of serum and CSF in the same way, with identical sample preparation procedures. The analyses were carried out using high‑performance liquid chromatography system coupled to triple quadrupole tandem mass spectrometer with electrospray ion source (LC‑ESI‑QqQ‑MS/MS). Results. The applied targeted metabolomics approach enabled to determine a wide panel of metabolites from different chemical classes of compounds including: acylcarnitines, amino acids and biogenic amines, glycerophospholipids, sphingolipids and sum of hexoses. Finally, 148 metabolites in serum and 57 in cerebrospinal fluid were determined.Conclusions. Here we presented the results of successful implementation of the method of analysis of low‑molecular weight compounds in human serum and CSF using targeted metabolomics. The evaluation of selected groups of metabolites resulted in obtaining the mean concentrations of panel of metabolites in serum and CSF, which gives a valuable information about the metabolome of these matrices.
Robust Fuzzy Timestep Selector for a Fully Implicit Reservoir Simulator
Authors: Crumpton Paul 
Published: March 2019

Abstract
The objective of this work is to avoid wasteful timestep cuts of the reservoir simulator by developing a timestep-selector that controls the linear and non-linear iterations as well as the physical quantities. Using a Fuzzy logic framework, a non-linear timestep selector has been developed that reduces run time, and increases robustness for challenging nonlinear simulations.
From a linear analysis standpoint a fully implicit reservoir simulator has no stability limit on the size the timestep. However, in practice the non-linearity prevents arbitrary timestep size being chosen. Without any theory to guide us the timestep choice it is left to heuristics, usually based on physical engineering constraints such as the previous time steps, maximum pressure and saturation changes. This can be very effective, but can lead to many timestep cuts, and sometimes lead to failure of the simulator. This is especially common for highly non-linear dual-porosity, dual-permeability reservoirs which are very common in the Middle East. Here a Fuzzy logic framework is used to construct a non-linear timestep selector which takes many inputs (linear and non-linear convergence data as well as pressure and saturation changes) and breaks down the complexity. Firstly fuzzification of the inputs into fuzzy sets (e.g. High medium and low) then applications of rules (e.g. if linear high then timestep is low) and de-fuzzification into a crisp timestep to be used for the next iteration. This process provides us with a powerful framework to construct various strategies for controlling the timestep. In contrast, traditional timestep controllers use crisp logic, this is difficult to blend multiple conflicting inputs to a timestep selector.
To demonstrate the effectiveness of this approach results are presented on a suite of cases, covering a wide range of models including compositional and dual-porosity cases. For some cases a dramatic 3x improvement is observed, however, what is more important, is on average the new timestep selector significantly improves performance, especially for the slow challenging cases; by reducing the time steps wasted due to timestep cuts. Perhaps what is most impressive is that the fuzzy controller did achieve the goals of the fuzzy rules to keep the non-linear and linear iterations under control, which had the benefit of reducing total failures of the simulator.
A fuzzy logic framework is applied to timestep selection of a fully implicit reservoir simulator. A combination of convergence data as well as physical quantities are used as inputs which has led to a robust and extendable timestep selector.
Von Neumann Stable, Implicit, High Order, Finite Volume WENO Schemes
Authors: Arbogast Todd , Huang Chieh-Sen , Zhao Xikai 
Published: March 2019

Abstract
Simulation of flow and transport in petroleum reservoirs involves solving coupled systems of advection diffusion-reaction equations with nonlinear flux functions, diffusion coefficients, and reactions/wells. It is important to develop numerical schemes that can approximate all three processes at once, and to high order, so that the physics can be well resolved. In this paper, we propose an approach based on high order, finite volume, implicit, Weighted Essentially NonOscillatory (iWENO) schemes. The resulting schemes are locally mass conservative and, being implicit, suited to systems of advection-diffusion reaction equations. Moreover, our approach gives unconditionally L-stable schemes for smooth solutions to the linear advection-diffusion-reaction equation in the sense of a von Neumann stability analysis. To illustrate our approach, we develop a third order iWENO scheme for the saturation equation of two-phase flow in porous media in two space dimensions. The keys to high order accuracy are to use WENO reconstruction in space (which handles shocks and steep fronts) combined with a two-stage Radau-IIA Runge-Kutta time integrator. The saturation is approximated by its averages over the mesh elements at the current time level and at two future time levels; therefore, the scheme uses two unknowns per grid block per variable, independent of the spatial dimension. This makes the scheme fairly computationally efficient, both because reconstructions make use of local information that can fit in cache memory, and because the global system has about as small a number of degrees of freedom as possible. The scheme is relatively simple to implement, high order accurate, maintains local mass conservation, applies to general computational meshes, and appears to be robust. Preliminary computational tests show the potential of the scheme to handle advection-diffusion-reaction processes on meshes of quadrilateral gridblocks, and to do so to high order accuracy using relatively long time steps. The new scheme can be viewed as a generalization of standard cell-centered finite volume (or finite difference) methods. It achieves high order in both space and time, and it incorporates WENO slope limiting.
A Compositional Model for Gas Injection IOR/EOR in Tight Oil Reservoirs Under Coupled Nanopore Confinement and Geomechanics Effects
Authors: Tian Ye , Xiong Yi , Wang Lei , Lei Zhengdong , Zhang Yuan , Yin Xiaolong , Wu Yu-Shu 
Published: March 2019

Abstract
Gas injection has become the top choice for IOR/EOR pilots in tight oil reservoirs because of its high injectivity. The effects of nanoconfinement and geomechanics are generally considered as non-negligible, but its coupled effects and resulting flow and displacement are still not well understood for gas injection. We hence present a general compositional model and simulator to investigate the complicated multiphase and multicomponent behaviors during gas injection in tight oil reservoirs.
This compositional model is able to account for vital physics in unconventional reservoirs, including nanopore confinement, molecular diffusion, rock-compaction, and non-Darcy flow. The MINC method is implemented to handle fractured media. The nanopore confinement effect is modeled by including capillarity in VLE calculations. The rock compaction effect is represented by solving the mean stress from a governing geomechanical equation which is fully coupled with the mass balance equations to ensure the numerical stability as well as a physically correct solution. The equations are discretized with integral finite difference method and then solved numerically by Newton's method.
The simulator is validated against a commercial compositional software (CMG-GEM) before it is applied to simulate gas injection. Huff-n-puff with dry gas in Eagle Ford is investigated. The simulation result shows that if the reservoir pressure is much higher than the bubble point pressure, the nanopore confinement effect will have a minimal impact on the recovery factor (RF) for both the depletion and the first few cycles of gas huff-n-puff. Geomechanics is found to be an influencing factor on RF but not always in a detrimental way, as enhanced rock compaction drive could offset the reduction of permeability in certain scenarios. Gas huff-n-puff would improve the RF of each component compared with the depletion. The heavy component would first have a higher recovery than the light component at the first few cycles of huff-n-puff, but its RF will be outpaced by the light component when the gas saturation in the matrix surpasses the critical gas saturation. Lastly, considering the nanopore confinement effects would slightly reduce the RF of the light component but increase the RF of the heavy component after huff-n-puff when combined with the critical gas saturation effect in the matrix.
This study presents a 3D multiphase, multicomponent simulator which is a practical tool for accurately modeling of primary depletion as well as gas injection IOR/EOR processes in unconventional oil reservoirs. This simulator is not only of great importance for assisting researchers to understand complex multiphase and multicomponent behaviors in tight oil production but also of great use for engineers to optimize gas injection parameters in field applications.
Continuous Relative Permeability Model for Compositional Reservoir Simulation, Using the True Critical Point and Accounting for Miscibility
Authors: Martin Petitfrère , Romain De Loubens , Leonardo Patacchini 
Published: March 2019

Abstract
Compositional simulators conventionally use Li's correlation to approximate the critical temperature (Tc) of hydrocarbon mixtures, used to arbitrarily label them as ‘gas’ or ‘oil’ outside the two-phase (gas/oil) envelope. Tc also feeds into the calculation of hydrocarbon-to-water relative permeabilities, typically interpolated between oil-to-water and gas-to-water based on the parameter Tc/T. This approach is clearly inconsistent when crossing the phase envelope in case of incorrect phase labeling.
We here propose to replace Li's correlation by a rigorous calculation of Tc using Michelsen's (1984)'s algorithm when phase identification is required. Using the gas-oil interfacial tension (IFT) within the phase envelope, and a fictitious gas-oil IFT computed at the saturation pressure (psat) outside the envelope, the hydrocarbon-to-water relative permeability is then built by interpolation between oil-to-water and gas-to-water relative permeabilities. The derivatives of psat (hence the IFT) with respect to the primary variables are computed analytically, to ensure robust fully implicit simulations.
In order to address the observation that gas/oil relative permeability curves tend to straight lines when approaching to the critical point, a second level of interpolation with respect to the IFT is applied within the phase envelope between miscible and immiscible three-phase models. Continuity is, by construction, guaranteed at any possible phase-state transition.
The proposed relative permeability model is first tested standalone (i.e., on a single cell) with different hydrocarbon mixtures, by analysis of the dependent parameter (true or fictitious IFT) and the relative permeabilities at different p-T conditions; in particular, continuity at each relevant interface of the p-T diagram is illustrated.
The model is secondly implemented in our In-House Research Reservoir Simulator (IHRRS), and tested on a synthetic 2D cross-section undergoing near-critical gas injection. We observe that with conventional models based on Li's correlation, discontinuities in the relative permeability model when crossing the phase envelope occur, as well as spurious phase flipping. No such unphysical behavior is observed with the proposed approach, while requiring the same input data.
There is of course a computational cost involved in properly calculating Tc, which is partly offset by the improved model convergence; because it is a cell-by-cell calculation, the overhead however scales down very well with parallelization.
Sequential Implicit Newton Method for Coupled Multi-Segment Wells
Authors: Li Jiawei , Wong Zhi Yang , Tomin Pavel , Tchelepi Hamdi 
Published: March 2019

Abstract
Accurate and robust well modeling is essential for performing reservoir simulations of practical interest. The Multi-Segment well (MSWell) model is able to describe the well topology and accurately represent the multiphase multicomponent flow and transport behavior in the wellbore. The fully coupled method (FC) has been developed and widely applied on coupled reservoir and MSWell modeling due to its unconditional stability and consistent implementation. A local well solver can be applied to provide a better nonlinear precondition for MSWell variables in order to accelerate the nonlinear convergence of the FC method.
However, solving the coupled MSWell and reservoir model in a fully implicit scheme can still present limitations on some practical applications. First, the well or surface facility solver can be separate from the existing reservoir simulator, making it challenging to employ the fully implicit method. Second, complex linear and nonlinear solvers need to be designed to pair the specific wells and reservoir models. These solvers have to account for the different flow characteristics and discretization domains between reservoir and MSWell. A sequential coupling scheme can become preferable in such situations.
Sequential fully Implicit method (SFI) splits the fully coupled reservoir and MSWell equations into two parts and solves them sequentially. In spite of accomplishing an implicit coupling in a sequential scheme, SFI suffers the slow outer loop convergence rate especially when reservoir is strongly coupled with the wells, which is very often the case. The slow convergence is caused by the linear convergence rate of the fix point iteration used in the SFI. Here, we developed a sequential implicit Newton's method (SIN) for coupled MSWells. SIN incorporates a Newton update at the end of each sequential step to achieve a quadratic convergence of outer iterations, while require a limited extra computational cost. Numerical results show that SIN attains comparable nonlinear Newton iterations with the FC in the coupled heterogeneous reservoir and complex MSWell problems.
Production Data Integration into Complex Geologic Facies Models: Exploiting the Behavior of Multiple-Point Statistical Simulation for Effective Data Conditioning
Authors: Ma Wei , Jafarpour Behnam 
Published: March 2019

Abstract
Multiple point statistical (MPS) simulation is a modern pattern-based geostatistical approach for describing and stochastically simulating geologic formations with complex connectivity patterns. In MPS geostatistical simulation, a template containing data patterns around each simulation cell is used to extract and store the local conditional probabilities from a training image (TI). To generate a simulated sample, a random path is generated to sequentially visit all unsampled grid cells and draw conditional samples from the corresponding stored conditional probabilities. The grid-based implementation of MPS simulation offers several advantages for integration of hard and soft data. In the Single Normal Equation SIMulation (SNESIM) implementation of MPS for facies simulation, it has been observed that the integration of soft data can result in many facies realizations that do not provide consistent patterns with the incorporated probability map. This is partly explained by the Markov property that only considers probabilities that are co-located with the simulation node, and hence ignoring spatial information from neighboring cells. In addition to this effect, we show another important mechanism is in play in the SNESIM algorithm that explains the observed behavior. Specifically, at the early stage of the simulation when the first few percentage of the simulation nodes on the random path are visited the local conditioning data are limited and the resulting conditional probabilities that are obtained from the TI are not strictly constrained. Hence the conditional probabilities cover a wide range of values in the range [0,1]. However, after this initial stage, as the simulated data populate more cells in the model grid, they tend to severely constrain the conditional probabilities to assume extreme values of 0 or 1. With these extreme values at the later stages of the simulation the probability values that are included in the soft data (as secondary source of information) tend to be disregarded and the facies types are predominantly determined by the TI. We demonstrate and discuss this behavior of the SNESIM algorithm through several examples and present strategies that can be adopted to compensate for this effect. The presented examples are related to indirect integration of the flow data by first inferring probabilistic information about facies types and using the results as soft data for integration into SNESIM algorithm.