bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predatory Invitations from Journals: More Than Just a Nuisance?
Authors: Clemons Mark , de Costa e Silva Miguel , Joy Anil Abraham , Cobey Kelly D. , Mazzarello Sasha , Stober Carol , Hutton Brian 
Published: February 2017

Abstract
Physicians and academic researchers are frequently targeted with spam invitations to submit manuscripts to predatory journals. This study was conducted to understand the nature and characteristics of these invitations. All spam e-mails received by an academic medical oncologist over a 3-month period were collected and categorized. Presumed predatory journal invitations were analyzed and cross-checked against Beall’s list of “potential, probable, or possible predatory” journals and publishers. Invitations to submit to predatory journals were the most common single type of spam received.
Association of biophysical profile with neonatal outcome: an observational study
Authors: Singh Gurmeet , Sood Reena , Kaur Karandeep 
Published: February 2017

Background: Perinatal asphyxia is a common cause of neonatal mortality and morbidity in India. Antenatal surveillance prevents foetal injury and death and improves long term neurological outcome through optimal timing of delivery while avoiding unnecessary interventions such as caesarean delivery or preterm delivery.Methods: After thorough history and physical examination, all patients underwent BPP assessment with USG and electronic foetal heart rate tracing and association between BPP score and various parameters were studied. Results: Low BPP scores were associated with low Apgar score, increased rate of neonatal admissions and increased neonatal deaths. For BPP score of 6 there were 5 deaths constituting 71.4% of the total cases.Conclusions: BPP score was found to be significantly associated with Apgar score and neonatal outcomes.
A study of anemia in primary hypothyroidism
Authors: Kulkarni Vrinda K. , Jadhav Dilip U. 
Published: February 2017

Background: The association between anemia and hypothyroidism has been recognized, although the prevalence of anemia in hypothyroid patients varies widely between studies. The main objectives were to study the prevalence, type, etiology of anemia in primary hypothyroidism and to correlate severity of anemia with severity of hypothyroidism.Methods: A case control study was carried out in a tertiary care hospital. Newly diagnosed 60 overt primary hypothyroid patients and 180 euthyroid controls were evaluated for anemia. Morphological types of anemia, their etiology were studied. Severity of anemia was correlated with that of hypothyroidism.Results: Anemia was observed in 45 patients with hypothyroidism. Symptoms due to anemia were significantly higher in cases than in the anemic controls. RBC morphology showed normocytic normochromic in 39, microcytic hypochromic in 14 and macrocytic in 7 cases. Serum iron was significantly lower in the cases than in the controls. Serum anti-TPO positivity was 63.33% in cases as compared to 10% in controls. Anemia was severe in cases with high TSH.Conclusions: The prevalence of anemia was 75% which was higher than that seen in the euthyroid controls. Hypothyroid patients were more symptomatic for anemia than the controls. Normocytic normochromic type of anemia was the most common type in our study. Autoimmunity in the form of anti-TPO positivity was detected in 69% of anemic cases. Iron deficiency was observed in the cases more than in the controls. There was a statistically significant negative correlation between TSH and hemoglobin.
Alternative uses of dermoscopy in general dermatology
Authors: Papakonstantinou Eleni , Raap Ulrike 
Published: February 2017

<p>Over the last few years, dermoscopy has been shown to be an effective diagnostic tool in assisting the noninvasive diagnosis not only of skin tumors but also of various general dermatological disorders. The use of dermoscopy has offered a new morphological dimension supporting the diagnosis and clinical follow-up of several dermatological conditions. Within the last years, dermoscopy is gaining ground in general dermatology as well. Among the large spectrum of skin infections, specific dermoscopic patterns have been described for common skin infections such as viral warts, molluscum contagiosum, scabies, and pediculosis, as well as for tinea nigra, tungiasis, and cutaneous larva migrans. Also, common skin disorders such as psoriasis, pityriasis rosea or lichen planus show characteristic dermoscopic patterns. The aim of this article is to provide an overview of the use of dermoscopy in general dermatology by analyzing the dermoscopic differential diagnosis of relatively common dermatological disorders grouped according to their clinical characteristics.</p>
Konsep Ketuhanan (T’ien) dan Relevansinya dengan Pembentukan Etos Kerja dalam Ajaran Kong Hu Cu (Konfusius)
Authors: Nazwar Nazwar 
Published: February 2017

Artikel ini membahas konsep Ketuhanan Konfusius yang berkaitan dengan etika kerja para penganutnya. Konsep ketuhanan yang dianalisa berdasar pada perspektif Filsafat, kemudian ditarik kepada realita tindakan sosial penganut ajaran Konfusius, dengan menggunakan data yang diperoleh berupa semangat kerja dan pemenuhan kebutuhan hidup para penganut pandangan hidup ini. Berdasarkan hasil penelitian, ditemukan bahwa konsep ketuhanan yang terdapat dalam ajaran Konfusius adalah paradigma fungsional. Dalam keyakinan tersebut, relasi antara Tuhan dan manusia didasarkan pada nilai fungsi. Tuhan diyakini berdasar pada peranannya terhadap kehidupan manusia. Begitupun sebaliknya, manusia diyakini berperan dalam pemenuhan keinginan Tuhan. Sehingga dalam ibadahnya yang paling menonjol adalah ritual korban. Semakin banyak korban yang dipersembahkan, maka kehidupanpun akan semakin subur dan makmur. Berdasarkan paradigma demikian, para penganut Konfusius kemudian mempunyai semangat kerja tinggi. Dengan tujuan selain pemenuhan kebutuhan hidup, juga merupakan usaha pemenuhan kebutuhan spiritual dalam rangka ibadah kepada T’ien (Tuhan).This article discusses the concept of God Confucius relating to the work ethic of its adherents. The concept of God that is analyzed based on the perspective of philosophy, then pulled to the reality of social action adherents of Confucianism, using the data obtained in the form of morale and subsistence adherents of this view of life. Based on this research, it was found that the concept of God contained in the teachings of Confucius is the functional paradigm. In that belief, the relationship between God and man is based on the value of the function. God is believed, based on its role in human life. Vice versa, humans are believed to play a role in the fulfillment of God's will. Thus, in the worship of the most prominent is the ritual sacrifice. The more sacrifices be offered, the more fertile and prosperous life will be. Based on such a paradigm, the Confucians then have a high morale. For purposes other than the needs of life, is also a spiritual business needs in order to the worship to T'ien (God).
Curriculum Development of Madrasah Tahfidz-Based Pesantren
Authors: Husna Nawa , Arifin Zainal 
Published: February 2017

The purpose of the research was to know deeper about the concept of Madrasah tahfidz based Pesantren with 30 chapters of tahfidz al-Qur’an system and to know how the implementation of curriculum development of madrasah tahfidz based Pesantren (school boarding) in MITQ TBS Kudus, Central Java. The research was a descriptive-qualitative with phenomenological approach with data collection techniques: in-depth interviews, non-participant observation, and documentation. The analysis of the data was by reduction, display, and provided conclusions. The results showed (1) the concept of madrasah tahfidz based pesantren in MITQ TB Kudus, Central Java emphasized on the time allocation of tahfidz al-Qur’an with more portion such as 48 hours per week to reach tahfidz al-Qur'an 30 chapters, and (2) curriculum development of madrasah tahfidz based Pesantren (school boarding) in TBS MITQ Kudus, Central Java included: diagnosis of needs, development of education purposes, curriculum of KTSP, curriculumof Religion Ministry and the local curriculum (pesantren), learning experiences, and the development of curriculum evaluation.Penelitian ini bertujuan untuk mengetahui lebih mendalam mengenai konsep madrasah tahfidz berbasis pesantren dengan sistem tahfidz al-Qur’an 30 juz serta mengetahui bagaimana pelaksanaan pengembangan kurikulum madrasah tahfidz berbasis pesantren di MITQ TBS Kudus Jawa Tengah. Penelitian ini adalah penelitian deskriptif-kualitatif dengan pendekatan fenomenologi dengan teknik pengumpulan data: wawancara mendalam, observasi non partisipan, dan dokumentasi. Analisis data melalui reduksi, display, dan memberikan kesimpulan. Hasil penelitian menunjukkan (1) konsep madrasah tahfidz berbasis pesantren di MITQ TBS Kudus Jawa Tengah menekankan pada alokasi waktu tahfidz al-Qur’an dengan porsi lebih yaitu 48 jam perminggu untuk mencapai tahfidz al-Qur’an 30 juz, dan (2) pengembangan kurikulum madrasah tahfidz berbasis pesantren di MITQ TBS Kudus Jawa Tengah meliputi: diagnosis kebutuhan, pengembangan tujuan pendidikan, kurikulum KTSP, kurikulum Kementerian Agama dan kurikulum muatan lokal (pesantren), pengalaman belajar, dan pengembangan evaluasi kurikulum.
Methodology to Estimate the Economic Impact of Intelligent Wells Considering Reservoir Uncertainties
Authors: Morais V. L. , Fioravanti A. R. , Schiozer D. J. 
Published: February 2017

Abstract
This work presents a method to test the use of intelligent wells in probabilistic scenarios. The proposed algorithm assists the decision about the number, position and operation of the interval control valves (ICV). The procedure focuses on the evaluation of intelligent well controls when optimizing complex oil field production strategies considering geological uncertainties.
The method assists the ICV application in uncertain scenarios, seeking to enhance flexibility and to improve the expected monetary value (EMV) during the field development phase. This work presents a detailed analysis of a production strategy previously optimized for conventional wells. The algorithm divides the production period into smaller time sections and optimizes them individually in a time sequence. For each section, performance indicators evaluate wells and regions for the potential to install ICV. We simulate the different combinations only of promising regions, restricting search space, which results in fewer simulation runs.
We used the benchmark case UNISIM-I-D, which is based on the Namorado field (Campos Basin, Brazil). EMV of the representative models was the objective function and we optimized ICV controls for a long-term exploitation strategy (lifecycle optimization procedure). We compared the proposed proactive control with an optimized reactive control to assess the results.
The study considers two different platform capacities (one optimized for the conventional well strategy and one with reduced capacity). We also show that when a platform restricts water production, the ICV closure affects not only the nearest wells but also other wells with high water rates, so this also must be evaluated.
Most ICV studies use techniques that are computationally expensive in real field evaluations. Barreto and Schiozer (2015) optimizes ICV placement with a low number of simulations but they check the viability of a single ICV implementation in each cycle. We propose testing various ICV simultaneously, respecting the influence of cross parameters by partitioning the production period into a sequence of predetermined time sections and optimizing each time section individually, forward in time.
The proposed optimization process demands a feasible number of simulation runs, enabling use in practical applications and complex reservoirs.
Model-Based Multi-Objective Optimization Methods for Efficient Management of Subsurface Flow
Authors: Fu Jianlin , Wen Xian-Huan 
Published: February 2017

Abstract
Multi-objective optimization (MOO) that accounts for several distinct, possibly conflicting, objectives is expected to be capable of providing improved reservoir management (RM) solutions for efficient oil field development owing to the overall optimization of subsurface flow. Considering the complexity and diversity of MOO problems in model-based RM, we develop three MOO methods (MOAdjoint, MOGA, and MOPSO) in this work to address various oil field development problems. MOAdjoint combines a weighted sum technique with a gradient-based method for solving large-scale continuous problems that have thousands of variables. An adjoint method is used to compute efficiently the derivatives of objective functions with respect to decision variables and a sequential quadratic programming method is used for optimization search. MOGA is a population-based method, which combines a Pareto-ranking technique with genetic algorithm (GA) to address small-scale discrete problems. MOPSO is another population-based method, which combines a Pareto-ranking technique with particle swarm optimization (PSO) for a wide spectrum of optimization problems. Their advantages and disadvantages are highlighted. An example is used to compare the three methods. Results show that MOPSO seems particularly suitable for medium-scale RM problems, mainly because of its relatively high rate of convergence and efficient recovery of Pareto front.
Trajectory-Based DEIM TDEIM Model Reduction Applied to Reservoir Simulation
Authors: Tan Xiaosi , Gildin Eduardo , Trehan Sumeet , Yang Yahan , Hoda Nazish 
Published: February 2017

Abstract
Two well-known model reduction methods, namely the trajectory piecewise linearization (TPWL) approximation and the discrete empirical interpolation method (DEIM) are combined to utilize their benefits and avoid their shortcomings to generate reduced order models for reservoir simulation. To this end, we use the trajectory-based DEIM (TDEIM) to approximate the nonlinear terms in the simulation. Specifically, the nonlinear terms in the test simulation can be expressed as the sum of the nonlinear terms evaluated at the closest available training point from the high-fidelity training trajectory and a perturbed term defined as the difference between the the test and the training terms. We only interpolate this perturbed term in the reduced space of DEIM instead of the original nonlinear term, resulting in computational savings and improvement in accuracy. TDEIM is further combined with the proper orthogonal decomposition (POD) method to provide an efficient POD-TDEIM framework. We test our new methodology on two examples, involving two-phase (water-oil) heterogeneous reservoir models. First, the performance of POD-TDEIM is compared with POD-TPWL and POD-DEIM on a 2D reservoir model. For the same set of high-fidelity training runs, POD-TDEIM outperforms the other two methods. We further propose an extended TDEIM in which the nonlinear term is expanded along the training trajectory to include one more derivative term. An example with a 3D reservoir model is then presented to show the capability of the extended TDEIM to further improve the accuracy of the reduced model.
A Gauss–Newton Trust Region Solver for Large Scale History Matching Problems
Authors: Gao Guohua , Jiang Hao , Hagen Paul Van , Vink Jeroen C. , Wells Terence 
Published: February 2017

Abstract
Solving the Gauss-Newton trust region sub-problem with traditional solvers involves solving a symmetric linear system with dimensions the same as the number of uncertain parameters, and it is extremely computational expensive for history matching problems with large number of uncertain parameters. A new trust region (TR) solver is developed to save both memory usage and computational cost, and its performance is compared with the well-known direct TR solver using factorization and iterative TR solver using conjugate-gradient approach.
The original Gauss-Newton trust region sub-problem involves solving linear system with the number of uncertain parameters. With application of the matrix inverse lemma, it is transformed to a new problem that involves solving linear system with the number of observed data. For history matching problems where the number of uncertain parameters is much larger than the number of observed data, both memory usage and CPU time can be significantly reduced when compared to solving the original problem directly. An auto-adaptive power-law transformation technique is developed to transform the original strong nonlinear function to a new function that behaves more like a linear function. Finally, the Newton-Raphson method with some modifications is applied to solve the trust region sub-problem.
The proposed approach is applied to find best-match solutions in Bayesian style assisted history matching problems. It is first validated on a set of synthetic test problems with different numbers of uncertain parameters and different numbers of observed data. In terms of efficiency, the new approach is shown to significantly reduce both the computational cost and memory usage, e.g., by a factor of more than 10, when compared to the direct TR solver of the GALAHAD optimization library. In terms of robustness, the new approach is able to reduce the risk of failure to find the right solution significantly, when compared to the iterative TR solver of the GALAHAD optimization library. Our numerical results indicate that the new solver can solve large scale trust region sub-problems using reasonably small amounts of CPU time (in seconds) and memory (in MB). Compared to the CPU time and memory used for completing one reservoir simulation run for the same problem (in hours and in GB), the cost for finding the best-match parameter values using our new trust region solver is negligible. The proposed approach has been implemented in our in-house reservoir simulation and history matching system and has been validated on a real reservoir simulation model. This illustrates the main result of this paper: the development of a robust Gauss-Newton trust region approach, which is applicable for large scale history matching problems with negligible extra cost in CPU and memory.
A Localized Variable Switching Method for Mass-Variable Based Reservoir Simulators
Authors: Alpak Faruk O. , Vink Jeroen C. 
Published: February 2017

Abstract
Field-scale simulations of complex processes, often suffer from long simulation times. One of the main reasons is that the Newton-Raphson (NR) process used to solve each simulation time step requires many iterations and small time-step sizes to converge. Since the selection of solution variables impacts the nonlinearity of the equations, it is attractive to have a practical method to rapidly explore the use of alternative primary variables in general-purpose reservoir simulators.
Many reservoir simulators use pressure, saturations, and temperature in each gridblock as primary solution variables, which are referred to as natural variables. There is also a class of reservoir simulators that uses pressure, total component masses (or moles), and internal energy in each gridblock as primary variables. These simulators are referred to as mass-variable based reservoir simulators. For a given choice of primary variables, most simulators have dedicated, highly optimized procedures to compute the required derivatives and chain rules required to build the Jacobian matrix. Hence, it is usually not possible to switch between mass and natural variables. In this work, however, we establish a link at the numerical solution level between naturaland mass-variable formulations and design a novel (nonlinear) block-local method that transforms mass-variable shifts (computed at each NR iteration) into equivalent natural variable shifts.
We demonstrate on a number of simulation models of various complexity that, by use of the proposed approach, a mass-variable based flow simulator can still effectively use natural variables, where the change of variables can be made locally per gridblock. Results indicate that in some models the total number of NR iterations, linear solver (LS) iterations, and backups are reduced when using natural variables, instead of mass variables. However, the improvement is fairly modest and not generally observed. Our findings also signify that, depending on the specific characteristics of the simulation problem at hand, mass-variable based simulators may perform comparably or outperform natural-variable based simulators.
The proposed variable switching method can be used effectively to evaluate the impact of using different primary solution variables on problem nonlinearity and solver efficiency. With this method, the impact of interchanging primary solution variables on problem nonlinearity can be rapidly evaluated.
Quantifying Value of Information using Ensemble Variance Analysis
Authors: He Jincong , Sarma Pallav , Bhark Eric , Tanaka Shusei , Chen Bailian , Wen Xian-Huan , Kamath Jairam 
Published: February 2017

Abstract
Data acquisition programs such as surveillance and pilots play an important role in minimizing subsurface risks and improving decision quality for reservoir management. In order for design optimization and investment justification of these programs, it is crucial to be able to quantify the expected uncertainty reduction and the value of information (VOI) attainable from a given design. This problem is challenging as the data from the acquisition program is uncertain at the time of the analysis. In this paper a method called ensemble variance analysis (EVA) is proposed. Based on a multi-Gaussian assumption between the observation data and the objective function, the EVA method quantifies the expected uncertainty reduction from covariance information that is estimated from an ensemble of simulations. The result of EVA can then be used with a decision tree to quantify the VOI of a given data acquisition program.
The proposed method has several novel features compared to existing methods. Firstly, the EVA method considers data-objective function relationship directly. Therefore it can handle nonlinear forward models and an arbitrary number of parameters. Secondly, for cases when the multi-Gaussian assumption between the data and objective function does not hold, the EVA method still provides a lower bound on expected uncertainty reduction, which can be useful in providing a conservative estimate of the surveillance/pilot performance. Finally, EVA also provides an estimate of the shift in the mean of the objective function distribution, which is crucial for VOI calculation. In this paper, the EVA workflow for expected uncertainty reduction quantification is described. The result from EVA is benchmarked with recently proposed rigorous sampling methods, and the capacity of the method for VOI quantification is demonstrated for a pilot analysis problem using a field-scale reservoir model.