bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Learning for Latent Space Data Assimilation LSDA in Subsurface Flow Systems
Authors: Mohd Razak Syamil , Jahandideh Atefeh , Djuraev Ulugbek , Jafarpour Behnam 
Published: October 2021

Abstract
We present a deep learning architecture for efficient reduced-order implementation of ensemble data assimilation. Specifically, deep learning is used to improve two important aspects of data assimilation workflows: (i) low-rank representation of complex reservoir property distributions for geologically consistent feature-based model updating, and (ii) efficient prediction of the statistical information that are required for model updating. The proposed method uses deep convolutional autoencoders to nonlinearly map the original complex and high-dimensional parameters onto a low-dimensional parameter latent space that compactly represents the original parameters. In addition, a low-dimensional data latent space is constructed to predict the observable response of each model parameter realization, which can be used to compute the statistical information needed for the data assimilation step. The two mappings are developed as a joint deep learning architecture with two autoencoders that are connected and trained together. The training uses an ensemble of model parameters and their corresponding production response predictions as needed in implementing the standard ensemble-based data assimilation frameworks. Simultaneous training of the two mappings leads to a joint data-parameter manifold that captures the most salient information in the two spaces for a more effective data assimilation, where only relevant data and parameter features are included. Moreover, the parameter-to-data mapping provides a fast forecast model that can be used to increase the ensemble size for a more accurate data assimilation, without a major computational overhead. We implement the developed approach to a series of numerical experiments, including a 3D example based on the Volve field in the North Sea. For data assimilation methods that involve iterative schemes, such as ensemble smoothers with multiple data assimilation or iterative forms of ensemble Kalman filter, the proposed approach offers a computationally competitive alternative. Our results show that a fully low-dimensional implementation of ensemble data assimilation using deep learning architectures offers several advantages compared to standard algorithms, including joint data-parameter reduction that respects the salient features in each space, geologically consistent feature-based updates, increased ensemble sizes to improve the accuracy and computational efficiency of the calculated statistics for the update step.
A Physics-Based Proxy for Surface and Subsurface Coupled Simulation Models
Authors: Yang Changdong , He Jincong , Du Song , Wang Zhenzhen , Onishi Tsubasa , Guan Xiaoyue , Chen Jianping , Wen Xian- Huan 
Published: October 2021

Abstract
Full-physics subsurface simulation models coupled with surface network can be computationally expensive. In this paper, we propose a physics-based subsurface model proxy that significantly reduces the run-time of the coupled model to enable rapid decision-making for reservoir management.
In the coupled model the subsurface reservoir simulator generates well inflow performance relationship (IPR) curves which are used by the surface network model to determine well rates that satisfy surface constraints. In the proposed proxy model, the CPU intensive reservoir simulation is replaced with an IPR database constructed from a data pool of one or multiple simulation runs. The IPR database captures well performance that represents subsurface reservoir dynamics. The proxy model can then be used to predict the production performance of new scenarios – for example new drilling sequence – by intelligently looking up the appropriate IPR curves for oil, gas and water phases for each well and solving it with the surface network. All necessary operational events in the surface network and field management logic (such as facility constraints, well conditional shut-in, and group guide rate balancing) for the full-coupled model can be implemented and honored.
In the proposed proxy model, while the reservoir simulation component is eliminated for efficiency. The entirety of the surface network model is retained, which offers certain advantages. It is particularly suitable for investigating the impact of different surface operations, such as maintenance schedule and production routing changes, with the aim of minimizing production capacity off-line due to maintenance. Replacing the computationally intensive subsurface simulation with the appropriate IPR significantly improves the run time of the coupled model while preserving the essential physics of the reservoir. The accuracy depends on the difference between the scenarios that the proxy is trained on and the scenarios being evaluated. Initial testing with a complex reservoir with more than 300 wells showed the accuracy of the proxy model to be more than 95%. The computation speedup could be an order of magnitude, depending largely on complexity of the surface network model.
Prior work exists in the literature that uses decline curves to replicate subsurface model performance. The use of the multi-phase IPR database and the intelligent lookup mechanism in the proposed method allows it to be more accurate and flexible in handling complexities such as multi-phase flow and interference in the surface network.
Alpine Rockwall Erosion Patterns Follow Elevation-Dependent Climate Trajectories
Authors: Draebing Daniel , Mayer Till , Jacobs Benjamin , McColl Samuel 
Published: October 2021

Abstract
Mountainous topography reflects an interplay between tectonic uplift, crustal strength, and climate-conditioned erosion cycles. During glaciations, glacial erosion increases bedrock relief, whereas during interglacials relief is lowered by rockwall erosion. In the first landscape-scale, multi-process investigation of postglacial rockwall erosion patterns, we show that paraglacial, frost cracking and permafrost processes jointly drive rockwall erosion. Field observations and modelling experiments demonstrate that all three processes are strongly conditioned by elevation. Our findings provide a multi-process explanation for the increase of rockwall erosion rates with elevation across the European Alps. As alpine basins warm during deglaciation, changing intensities and elevation-dependent interactions between periglacial and paraglacial processes result in elevational shifts in rockwall erosion patterns. Future climate warming will shift the intensity and elevation distribution of these processes, resulting in overall lower erosion rates across the Alps, but with more intensified erosion at the highest topography most sensitive to climate change.
Quantum Statistics of Light Emitted from a Pillar Microcavity
Authors: Khudaiberganov Timur A. , Arakelian Sergei M. 
Published: October 2021

Abstract
A quantum behavior of the light emitted by exciton polaritons excited in a pillar semiconductor microcavity with embedded quantum well is investigated. Considering the bare excitons and photon modes as coupled quantum oscillators allows for an accurate accounting of the nonlinear and dissipative effects. In particular, using the method of quantum states presentation in a quantum phase space via quasiprobability functions (namely, a P-function and a Wigner function), we study the effect of the laser and the exciton-photon detuning on the second order correlation function of the emitted photons. We determine the conditions for the phenomena of bunching, giant bunching, and antibunching of the emitted light. In particular, we predict the effect of a giant bunching for the case of a large exciton to photon population ratio. Within the domain of parameters supporting a bistability regime we demonstrate the effect of bunching of photons.
Thru-Hole Epitaxy: Is Remote Epitaxy Really Remote?
Authors: Jang Dongsoo , Ahn Chulwoo , Lee Youngjun , Lee Seungjun , Lee Hyunkyu , Kim Donghoi , Kwon Young-Kyun , Choi Jaewu , Kim Chinkyo 
Published: October 2021

Abstract
The remote epitaxy was originally proposed to grow a film, which is not in contact but crystallographically aligned with a substrate and easily detachable due to a van der Waals material as a space layer. Here we show that the claimed remote epitaxy is more likely to be nonremote ‘thru-hole’ epitaxy. On a substrate with thick and symmetrically incompatible van der Waals space layer or even with a three-dimensional amorphous oxide film in-between, we demonstratively grew GaN domains through thru-holes via connectedness-initiated epitaxial lateral overgrowth, not only readily detachable but also crystallographically aligned with a substrate. Our proposed nonremote thru-hole epitaxy, which is embarrassingly straightforward and undemanding, can provide wider applicability of the benefits known to be only available by the claimed remote epitaxy.
Optimal Design of Adaptive Neuro-Fuzzy Inference System Using PSO And Ant Colony Optimization For Estimation of Uncertain Observed Values
Authors: Danesh Mahdi , Danesh Sedighe 
Published: October 2021

Abstract
This study employs a new method for regression model prediction in an uncertain environment and presents fuzzy parameter estimation of fuzzy regression models using triangular fuzzy numbers. These estimation methods are obtained by new learning algorithms in which linear programming is used. In this study, the new algorithm is a combination of a fuzzy rule-based system, on the basis of particle swarm optimization (PSO) and ant Colony Optimization AC\({O}_{R}\). In addition, a simulation and a practical example in the field of machining process are applied to indicate the performance of the proposed methods in dealing with problems where the observed variables have the nature of uncertainty and randomness. Finally, the results of the proposed algorithms are evaluated.
Kinetics And Thermodynamic Properties of Trametes Polyzona WRF03 Laccase
Authors: Ezike Tobechukwu Christian , Ezugwu Arinze Linus , Udeh Jerry Okwudili , Ugwuoke Kenneth Chinekwu , Eze Sabinus Oscar Onyebuchi , Chilaka Ferdinand Chiemeka 
Published: October 2021

Abstract
The effect of thermal treatment on the activity of laccase from Trametes polyzona WRF03 was studied at pH and temperature ranges of 3.0 to 6.5 and of 40 to 70 oC respectively. Kinetic data revealed that the heat inactivation of Trametes polyzona WRF03 laccase (TpL) was pH dependent and followed first-order kinetics. There was a positive correlation between activation energy (Ea) for thermal inactivation of TpL and the reaction pH. Highest activation energy, Ea, value of 175.49 kJ/mol was obtained at pH 6.0. On the contrary, the z-value decreased with a lowest value of 12.37 oC at pH 6.0. The high Ea value and low z-value were indicative of the thermo-stable nature of TpL which suggests that pH 6.0 had a compensatory stabilizing effect on TpL against its thermal denaturation. There was a gradual decrease in the enthalpy of denaturation (∆Ho) and Gibb’s free-energy with every 10 % rise in temperature within the investigated pH range, suggesting that TpL was more stable at 40 oC. Positive values of entropy of inactivation (ΔSº) at each temperature indicated that there was no aggregation during the inactivation processes. Thus, these results provided useful information about the behaviour of TpL under certain pH and temperature combination with respect to biotechnological application. Thus, the kinetic and thermodynamic data could be used to design a model to predict the thermal inactivation of TpL during industrial application.
Geographical Distribution of Zebu Breeds in Brazil And Their Relationship With Environmental Variables and Human Development Indicator
Authors: Lima Paulo Ricardo Martins , Peripolli Vanessa , Josahkian Luiz Antônio , McManus Concepta 
Published: October 2021

Abstract
The aim of this study was to evaluate the geographical distribution of zebu breeds in Brazil and correlate their occurrence with environmental variables and human development indicator. The herds of purebred zebu cattle in Brazil were classified as beef breeds (Brahman, Polled Brahman, Nelore, Polled Nelore and Tabapuã), dairy breeds (Gir and Polled Gir), and dual-purpose breeds (Guzerá, Indubrasil, Polled Indubrasil, Sindhi and Polled Sindhi), all breeds being spatialized in ArcGIS program. Variables examined included environmental and human development indicator. The statistical analysis included analysis and logistic regression.The lower distribution of zebu cattle in the states of Northeast compared to other locations is probably due to its extreme climate, highly susceptible to long periods of high temperatures and lower precipitation, which directly affects local livestock. The beef breeds were evenly spread throughout the country. The location occupied for beef breeds was influenced by environmental variables, showing a higher incidence with increased precipitation, normalized difference vegetation index (NDVI), temperature, relative humidity and temperature humidity index (THI), as well as establishments without family agriculture and rivers and streams with forest protection. The location used for dual-purpose and dairy breeds was influenced by areas with cultivated cutting forages, areas with integrated crop-livestock forest systems and areas with rotational grazing system, indicating a higher occupation in fertile lands. The Gir breed, the only one with dairy exploration in this study, showed herds in establishments with family agriculture, characterized by small to medium farms, and in regions with higher altitude.
Effects of Jia Wei Dachaihu-Tang on gut microbiota and inflammatory markers in patients with overweight or obesity: study protocol for a randomized, controlled, double-blinded trial
Authors: Gao Yang , Hong Peipei , Liao Tingting , Han Xuke , Zhou Shan , Chen Qiu 
Published: October 2021

Abstract
Background

The increasing number of overweight and obesity has posed an enormous hazard to the health of worldwide people, but the present methods for it still exist a few drawbacks, which implied that new effective treatment is urgently needed. Jia Wei Dachaihu-Tang (JWDT), a Chinese herbal medicine formulation wildly used to remedy obesity in clinical practice, has been confirmed its effectiveness and safety in our previous studies. In the study, the impacts of JWDT on gut microbiota and inflammatory markers in patients with overweight or obesity will be further investigated.
Methods/design:

This trial will be a randomized, double-blinded, parallel-group, placebo-controlled single-center trial recruiting 60 participants who are 18 to 80 years of age with a body mass index(BMI) ≥ 25 kg/m2. Participants will be enrolled on a random basis and are equally assigned to either Jia Wei Dachaihu-Tang or placebo for 12 weeks. The primary outcome is the change in BMI during this trial. Secondary outcomes contain changes in waist circumference, waist to hip ratio, blood lipid, insulin resistance index (HOMA-IR), body composition, inflammatory factors, gut microbiome, appetite, etc. Blood and fecal sample collection will be conducted at the baseline and after the 12-week intervention.
Discussion

This study will further testify the therapeutic effect of JWDT in overweight or obesity, and investigate its power on insulin resistance, body composition, gut microbiota, inflammation, appetite, food intake, emotion. Furthermore, investigators attempt to pursue the possible mechanism that JWDT ameliorates overweight and obesity from the perspective of gut microbiota, expecting to provide new targets and directions for the treatment of obesity.
Trial registration:

The protocol has been registered on the Chinese Clinical Trial Registry (ChiCTR2000040889) on 14 December 2020,http://www.chictr.org.cn/abouten.aspx.
Ecological niche modeling, niche overlap, and good old Rabinowitz’s rarities applied to the conservation of gymnosperms in a global biodiversity hotspot
Authors: Quiroga Paula , Souto Cintia 
Published: October 2021

Abstract
ContextBiodiversity hotspots harbor 77% of endemic plant species. Patagonian Temperate Forest (PTF) is a biodiversity hotspot, but over the past centuries, has been over-exploited, fragmented and replaced with exotic species plantations, lately plus the threat of climate change. ObjectivesOur aim is to better understand patterns of habitat suitability and niche overlap of nine endemic gymnosperm species, key elements of the PTF, complementing traditional approaches of biodiversity conservation. MethodsUsing R packages and 3024 occurrence data, we deployed ecological niche models (ENM) in MaxEnt via KuENM, and classified species according to Rabinowitz’s types of rarity. We then overlapped their niches calculating Schoener's D index, and considered types of rarity in a spatial ecological context. Finally, we overlay high species’ suitability and protected areas and detect conservation priorities using GapAnalysis. ResultsWe generated simplified ENMs for nine Patagonian gymnosperms and found that most niches overlap, and only one species displayed a unique niche. Surprisingly, we found that three species have divergent suitability of habitats across the landscape. We showed that the rarer a species is the smaller niche volume tend to have, that six out of nine studied species have high conservation priority, and that there are conservation gaps in the PTF. ConclusionOur approach showed that there are unprotected suitable areas for native key species at high risk in Patagonian forests. Suggesting that integrating habitat-suitability models of multiple species, types of rarity, and niche overlap, can be a handy tool to identify potential conservation areas in global biodiversity hotspots.
Nitrogen Deficiency in Culture Affects the Metabolic Pathways in Amphora Coffeaeformis for Biodiesel Production
Authors: Wang Kang , Cui Yulin , Meng Chunxiao , Gao Zhengquan , Qin Song 
Published: October 2021

Abstract
Background: Amphora coffeaeformis, a unicellular diatom, can accumulate large amounts of lipids under nitrogen (N) limitation, because of which it can act as a promising raw material for biodiesel production. However, the molecular mechanism underlying lipid accumulation in A. coffeaeformis remains unknown. Results: In this study, we investigated the mechanism underlying lipid accumulation under N deprivation conditions in A. coffeaeformis using RNA-seq. The results showed that the total lipid (TL) content of A. coffeaeformis in normal f/2 medium was 28.22% (TL/DW), which increased to 44.05% after 5 days of N deprivation, while the neutral lipid triacylglycerol (TAG) content increased from 10.41% (TAG/DW) to 25.21%. The transcriptional profile showed that 591 genes were up-regulated, with false discovery rate cutoff of 0.1%, and 1,021 genes were down-regulated, indicating that N deprivation induced wide-ranging reprogramming of regulation, and that most physiological activities were repressed. In addition, ribosome biogenesis, carbon fixation, and photosynthesis in A. coffeaeformis were considerably affected by N deprivation. Conclusions: In summary, the findings initially clarified the molecular mechanism of TAG accumulation and revealed the key genes involved in lipid metabolism in A. coffeaeformis, which will be useful in designing strategies for improving microalgal biodiesel production.
Women Leaders Perceived Barriers and Consequences of Safe Abortion in Rwanda: A Qualitative Study
Authors: Rugema Lawrence , Uwase Marie Ange , Rukundo Athanase , Nizeyimana Vianney , Mporanyi Theobald , Kagaba Aflodis 
Published: October 2021

Abstract
Background: Between 2010 and 2014, approximately 25 million unsafe abortions were performed annually across the globe. Africa alone accounted for 29% of all unsafe abortions, and 62% of the related deaths. Women living in poverty, especially adolescents, lack information about where and how to access safe abortion services. They often do not have the power to make informed decisions on the subject. The purpose of this study is to explore the barriers and consequences of safe abortion as perceived by women leaders in Rwanda. Method: In this qualitative study, seven focus group discussions and seven key informant interviews were performed in October 2019. A total of 51 women leaders participated, their age ranging from 38 to 60 years. Participants were drawn from three districts, namely Gasabo, Kicukiro, and Nyarugenge. For variability of data, participants came from parliament, government ministries, government parastatals, and civil society organizations. All interviews were conducted in Kinyarwanda and later translated into English. Data were analyzed using qualitative content analysis. Results: The emerging theme “strong barriers and numerous consequences of safe abortion” illustrates how women leaders perceive barriers to safe abortion and its related consequences in Rwanda. The theme is divided into two categories: 1) “Perceived barriers of safe abortion” and 2) “Consequences of providing safe abortion”. The sub-categories for the first category are “Reluctance to fully support safe abortion due to perceived unjustified abortions”, “Abortion-related stigma, “Abortion is against cultural and religious beliefs”, and “Emotional attachment to the unborn”. The sub-categories for the second category are “Perceived physiological trauma”, “cause for barrenness/infertility”, “increase in services abuse by adolescents/women”, “increase of workload for healthcare providers”, “increase in sexual activities and STIs”, and “Abortion-related physiological trauma”. Conclusion: The subject of safe abortion evokes mixed reactions among participants, and is entangled with unsafe abortion in most cases. Participants stress that the word ‘abortion’ disturbs, regardless of whether it relates to being safe or unsafe. Participants believe the word ‘abortion’ outweighs the word ‘safe’. Societal expectations play a major role in the decision-making process of any adolescent or a family member faced with a pregnant adolescent regardless of the existing safe abortion law. Community mobilization and sensitization are crucial if safe abortion in accordance with abortion law is to be embraced. Messages that reinforce safe abortion as acceptable and address stigma, fears of trauma, and barrenness should be developed to educate adolescents, parents, and women leaders about safe abortion, to mitigate unsafe abortion-related complications.
Case Report: Gastric Cancer Combined With Bilateral Ovarian Metastasis In Pregnancy
Authors: Zhang Zhenhua , Lv Gang , Liu Mei , Lin Miaohui , Xie Meilin , Zhao Yinghui , Lv Jia 
Published: October 2021

Abstract
Background: The early manifestations of gastric cancer during pregnancy are non-specific. Ovarian mass and ascites are the main manifestations of late ovarian metastasis. Case presentation: A case of late gastric cancer with bilateral ovarian metastasis in pregnancy was reported in our study. Cesarean section and full staging of ovarian malignant tumors were performed at 28+5 weeks of pregnancy, and the prognosis was poor. We performed Cesarean delivery and extracted a vital male newborn of 35 cm, 1020 g, Ap score 3. The newborn is alive and grows normally. Three months later the mother died. The key to improving the prognosis is early diagnosis, and the pre-pregnancy health checkup must be emphasized. Conclusions: During pregnancy, ultrasound, gastroscopy, MRI and other related examinations should be performed to confirm the diagnosis, and individualized treatment plans should be formulated to maximize the protection of the mother and child's interests.