bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling of Deep Polymer Gel Conformance Treatments Using Machine Learning
Authors: Alghazal Mohammed , Ertekin Turgay 
Published: November 2020

Abstract
Polymer gel technologies have been widely employed in conformance-control applications to improve sweep and recovery from high permeability reservoirs. Modeling of polymer gel propagation, gelation time, and adsorption in the porous media requires a complex full-order computation of diffusivity equations, heat transfer and chemical reactions for components partitioning in oleic and aqueous phases. This paper presents a soft-computing alternative and data-driven approach to using machine learning to model deep polymer gel treatments in fractured reservoirs.
Reference simulation models of various dual-permeability systems were used to generate the dataset for the machine learning model, an artificial neural network. A second-order reaction scheme for gel formulation was used to describe the chemical reaction between the polymer, polyacrylamide, and the cross-linker component, chromium acetate. Viscosities, adsorption properties and residual resistance factors of the polymer and produced gel were populated based on experimental data. Various conformance design factors and reservoir properties were parameterized for inclusion in the neural network, including: temperature, injection rate, gel concentration, bottom-hole pressure, drainage radius, porosity, fracture spacing and permeability.
Feature analysis of the input variables indicated that ten parameters are sufficient to train the model and predict the performance of the conformance treatment with indicators including the oil and water rate profiles improvement after applying the polymer gel treatment. The dataset was randomly divided into 80% training, 10% validation and 10% testing sets. Early stopping and monitoring of the validation and testing set's errors were used to generalize the solution and enhance the performance of the neural network. Hyperparameter tuning showed that using a deep multi-hidden layers neural network was more effective than increasing the neurons in a single hidden layer. The weights and biases of the model were adjusted using a mean squared error loss function and a gradient descent optimizer. A correlation of 90% was achieved for the test samples with a mean absolute deviation of less than 10% for all modeled variables. The developed neural network model was able to reduce the complexity of the full-order simulation model by accurately predicting the performance of polymer gel treatments in fractured reservoirs at 200 times faster speed than commercial simulators with only ten input variables of polymer gel design and reservoir properties.
This work presents a unique surrogate modeling approach based on machine learning to describe complex polymer gel kinetics and flow dynamics in deep conformance applications. The presented neural network model can be used to robustly predict the oil recovery performance of polymer gel treatments in fractured reservoirs outperforming commercial simulators in terms of computational complexity and processing speed.
Capturing in Gas Treating Plants Technology Review and Selection
Authors: Sivanandam Surendarbabu , Al Ali Mariam 
Published: November 2020

Abstract
Increase in the requirement of reduction of CO2 emission / carbon footprint demands the need for CO2 capturing units in existing gas treatment facilities. The location of the CO2 capturing unit in the sour gas treating plant have economic impact with respect to CO2 recovery and unit technical cost (UTC). A case study is presented to demonstrate the optimum location of the CO2 recovery unit with available licensed technology.
Based on production profile and composition for Asab 1 & 2, the potential acid gas removed from acid gas removal unit (AGRU) is quantified. The amount of CO2 in acid gas to be recovered in view to having a SRU unit, had the choice of CO2 recovery from: (1) low pressure amine based CO2 capturing units, (2) high pressure CO2 capturing units based on amine / physical solvents, or (3) CO2 recovery from tail gas of sulphur recovery unit (SRU).
A technology selection study was carried out to select appropriate technology for CO2 capture with optimum unit technical cost (UTC).
The study findings are summarized as below: Low pressure amine based CO2 recovery unit, along with the tri-ethylene glycol (TEG) based CO2 dehydration and conditioning and CO2 pumping / compression units configuration, is considered to have optimum unit technical cost (UTC). The low pressure amine based CO2 recovery unit acts as an acid gas enrichment (AGE) unit upstream of the sulphur recovery unit (SRU). As the CO2 is recovered, the total enriched acid gas feed (with higher H2S concentration) to sulphur recovery unit will reduce, hence the size of the sulphur recovery unit (SRU) will come down.Tri-ethylene glycol (TEG) based CO2 drying technology is considered with advantage over other available technologies like mole sieves, membrane based process etc.
The CO2 capturing unit scheme selected during the conceptual design stage will be further developed in detail during the FEED stage. The CO2 recovered will be utilized for enhanced oil recovery, which will aid increased oil production and value to the company. As the CO2 recovery unit is planned along with SRU, the CO2 emission from the SRU unit will also be reduced.
Simulation and Benefit Estimates of EOR in Wara and Burgan 3SU Reservoirs, Greater Burgan Field
Authors: Al-Qattan Abrar , Kazemi Nia Korrani Aboulghasem , Jerauld Gary , Choo Raymond 
Published: November 2020

Abstract
The Greater Burgan field in Kuwait is the largest sandstone oilfield in the world. Kuwait Oil Company (KOC) recognizes that enhanced oil recovery (EOR) is of strategic importance to maximize recovery and extend field life. We studied several EOR options using reservoir simulation to evaluate the benefits of using low salinity waterflood (LSW), low salinity polymer (LSP) injection and high salinity polymer (HSP) injection applications in Wara and Burgan upper (3SU) reservoirs.
Full-field reservoir-simulation with adequate resolution for EOR assessment of giant fields (e.g., Greater Burgan) is computationally expensive, if even possible. To overcome this, we ran high-resolution sector-models, representing different areas, with inputs from laboratory and single-well-chemical-tracer-tests and generated type-curve profiles (e.g. oil recovery vs. cumulative pore-volume injection). A scaling-up tool was developed that considers infrastructure-facility constraints (e.g., high- and low-salinity capacities and injection priority of field areas), combines type-curve profiles, and outputs field-level profiles. At sector-level, we optimized all EOR slug sizes. For cases with polymer, polymer concentration was optimized on basis of polymer amount required per incremental oil barrel.
The following five development scenarios were studied: 1) HSP everywhere across Wara and Burgan (3SU) reservoirs 2) LSW everywhere across the reservoirs 3) LSP everywhere across the reservoirs 4) secondary LSW for certain areas of the reservoirs and HSP for remaining areas 5) secondary LSP for certain areas of the reservoirs and HSP for remaining areas. The scenario #3 shows the highest incremental oil as it adds the benefits of both LSW and polymer injection. However, using low salinity-polymer in conjunction with high salinity-polymer (i.e., scenario #5) gives the highest incremental oil peak rate. In general, polymer flooding reduces the amount of water production. Use of low salinity without polymer resulted in higher water production. Significantly less volumes of polymer are associated with low-salinity water injection as compared with high-salinity water injection. Optimal polymer concentration was found to be well above that which gave unit mobility ratio. Although, the EOR incremental benefits and their corresponding screening-level economics look reasonable for the EOR schemes investigated, the schemes vary significantly in feasibility, capital costs and operating costs. A long-term injectivity pilot of high-salinity polymer is planned.
Our approach combines the understanding of recovery efficiency that comes from detailed type pattern modelling with understanding of realistic facility constraints to rapidly generate realistic field-wide projections. We evaluated several facilities options corresponding to the five EOR development scenarios and generated cost profiles that were used in economic modelling.
Molecular Characteristics and Changing&nbsp;Trend&nbsp;of Methicillin-Resistant Staphylococcus Aureus&nbsp;From&nbsp;Invasive&nbsp;Infections between&nbsp;2012 and 2018
Authors: Xiao Yonghong , Zhu Yunying , Wang Yuan , Xu Hao , Xiao Tingting , Yang Kai , Zhang Shuntian , Zhou Yanzi , Ji Jinru , Shen Ping 
Published: November 2020

Abstract
Background Methicillin-resistant Staphylococcus aureus (MRSA) is a major global problem. The analysis of the molecular characteristics and changing trend of MRSA is essential for the control and treatment of diseases caused by the pathogen.Methods A total of 162 MRSA isolates from invasive infections between 2012 and 2018 were collected, molecular typing and antimicrobial susceptibility tests to explore its molecular epidemiologic change in a hospital were performed.Results All of the 162 MRSA isolates (86.4% HA-MRSA and 13.6% CA-MRSA) were divided into 16 different ST and 30 Spa types. The major STs were ST5 (96/162, 59.3%) and the predominant spa type was t311(83/162, 51.2%). Five SCCmec types were found and the most common SCCmec type was type II (101/162, 61.7%). The prevalence of ST5 MRSA gradually declined from 2014 to 2018 but the prevalence of ST59 MRSA significantly increased. At the same time, livestock-associated methicillin-resistant S.aureus ST239 and ST9 were detected. 28 isolates were Panton-valentine leucocidin (pvl) gene positive (28/162, 17.3%). The most prevalent pvl-positive clone was ST59-IVa-t437. Comparing with HA-MRSA, CA-MRSA had a lower probability of ST5 (9.1% vs, 67.1%, P=0.000) but a higher probability of ST59 (63.6% vs. 11.4%, P=0.000), not only that, it was more likely to carrying pvl-positive gene (36.4% vs. 14.3%, P=0.028).Conclusions The molecular types of MRSA were getting complex over time. ST5-II-t311 was the predominant clone of MRSA isolate with a downward incidence from 2012 to 2018. ST59 MRSA strains, which is thought community related strain are spreading into hospitals and has an upward incidence during the investigational period.
Analysis of MDR1 Polymorphisms Among HIV-Infected Individuals on ARV Therapy from Western India
Authors: Singh HariOm , Samani Dharmesh , Chauware Vijay , Dhole T.N 
Published: November 2020

Abstract
Background: The multidrug resistance protein, MDR1 is involved in the transport of numerous drugs. Polymorphism of MDR1 is linked with the treatment outcome. Antiretroviral (ARV) regimen is being used to manage the progression of HIV infection. Ethnic disparities have been observed in the distribution of MDR1 genotypes.Methods: MDR1 polymorphisms (1236 C/T, 3435 C/T) was genotyped in 34 HIV-infected individuals with ARV-associated hepatotoxicity, 131 HIV-infected individuals without ARV-associated hepatotoxicity, and one-fifty-five healthy individuals by utilization of PCR-RFLP.Results: The incidence of haplotype TC of MDR1 was found to be more in HIV infected individuals with hepatotoxicity than the non-hepatotoxic ones, thus indicating a greater risk for hepatotoxicity severity (OR=1.96, P=0.06). Whereas the haplotypes TT and CC were found to be linked with a reduced risk for hepatotoxicity severity (OR= 0.16, P=0.006; OR= 0.46, P=0.06). A higher occurrence of MDR1 1236TT genotype was seen among patients with hepatotoxicity who consumed alcohol (28.6% versus 14.8%, OR=1.50). In patients with hepatotoxicity on nevirapine, there was an increased incidence of MDR1 1236TT genotype in contrast with efavirenz (21.7% versus 9.1%, OR=2.11). In HIV-infected people on nevirapine, the incidence of MDR1 1236CT, 1236TT genotypes was found to be more as compared to the ones on efavirenz (43.7% versus 33.3%, OR=1.66; 12.6% versus 8.3%, OR=1.96). Also a higher occurrence of MDR1 1236TT genotype was found in the hepatotoxicity cases on nevirapine, who consume alcohol as compared to the alcohol nonusers on nevirapine (40.0% versus 16.67%, OR=2.21).Conclusion: Haplotype TC was associated with the increased severity of hepatotoxicity because of synergistic effect. In the HIV infected individuals on nevirapine who consume alcohol, the presence of MDR1 1236TT and 3435CT genotypes may have a combined effect on vulnerability to hepatotoxicity severity and progression of HIV infection.
Involvement of Acid-Sensing Ion Channel 1a&nbsp;Contribute to&nbsp;The Effect of Extracellular Acidosis on&nbsp;Vascular Endothelialcell Damage&nbsp;of&nbsp;Henoch-Schönlein&nbsp;Purpura&nbsp;Patients
Authors: Wang Jin-Kun , Bo Yan , Zhou Qi-lian , Yuan Li-ping 
Published: November 2020

Abstract
Background: Henoch-Schönlein purpura (HSP) is a common kind of systematic vasculitis in children characterized by rash, joint pain,abdominal symptoms and renal disease,the detail pathogenesis of HSP has not been elucidated.Acid-sensing ion channels (ASICs) is a proton-gated sodium selective channel that belongs to Degenerin /epithelial Sodium Channel(DEG/ENaC) superfamily,previous research found the expressions of ASIC1a and ASIC3 in the vascular endothelial cells of HSPThis study aims to investigate the molecular mechanisms of silencing of acid-sensing ion channel 1a(ASIC1a) protects the vascular endothelial cells from Henoch-Schonlein purpura(HSP) patients.Findings:Human dermal microvascular endothelial cells ( HDMVEC) were cultured in vitro, siRNA sequences were designed for the coding region of human ASIC1a gene and HDMVEC cells were transfected with recombinant lentivirus( LV) -sh-ASIC1a. The control group ( NC group) without virus transfection and LV-sh-ASIC1a transfection group ( si-ASIC1a group) were set up. The expression of transfixed ASIC1a gene was detected by RT-PCR. After virus transfection 72 h, serum IgA1from HSP patients and serum IgA1 of normal children were added into HDMVEC cells. ASIC1a and cytoskeleton protein ( sm-α f-actin, MLCK) mRNA and protein expressions were detected by real-time PCR and Western blotting Methods.The binding activity of NF- κB with DNA in HDMVEC was determined by electrophoretic mobility shift assay (EMSA).The whole-cell patch-clamp technique was used to record the current changes and electrophysiological characteristics of ASICs in HDMVEC.Cytoskeleton protein ( sm-α f-actin, MLCK) mRNA and protein expressions in the group of si-ASIC1a group were significantly increased compared with the NC control group( P＜0.01). The HSP serum and silencing of ASIC1a had no significant effect on the binding activity of NF-κB with DNA in HDMVEC. Compared with the NC control group, the ASICS current and calcium overload of the si-ASIC1A group were reduced( P＜0.01) ．Conclusions: Silencing ASIC1a can protect HSP vascular endothelial cell injury by inhibiting ASIC1-related calcium influx and reducing the overload of calcium ,not the NF- κB signaling pathway.
COVID-19 Could Trigger Systemic Juvenile Idiopathic Arthritis: First Case Report
Authors: Parvaneh Vadood Javadi , Rahmani Khosro 
Published: November 2020

Abstract
Background: COVID-19 has been reported to cause a variety of signs and symptoms during its three known phases.Case presentation: We report a 7 years-old boy with COVID-19 first presented with an acute abdomen. Then he showed pictures of Kawasaki-like syndrome, a multiorgan inflammatory syndrome in children (MIS-C), and finally systemic juvenile idiopathic arthritis.Conclusion: MIS-C is a result of the hyperinflammatory response of the body to SARS-CoV-2. Although there are increasing reports of this state in children, we reported the first case presenting systemic JIA triggered by COVID-19.
Apolipoprotein E4, Amyloid, and Cognition in Alzheimer’s and Lewy Body Disease
Authors: Jung Jin Ho , Jeon Seun , Baik Kyoungwon , Lee Yang Hyun , Chung Seok Jong , Yoo Han Soo , Jeong Seong Ho , Sohn Young H. , Lee Phil Hyu , Ye Byoung Seok 
Published: November 2020

Abstract
Background: The role of APOE4 in the risk of Alzheimer’s disease, Lewy body disease, and their mixed diseases have not been evaluated in antemortem patients. Also, the APOE4 effect on β-amyloid deposition and cognition, with consideration of both Alzheimer’s and Lewy body diseases, remains unclear. We aimed to determine the APOE4 effects on the risk of Alzheimer’s disease, Lewy body disease, and their mixed diseases, as well as on β-amyloid deposition and cognition after adjusting for the effect of Alzheimer’s disease and Lewy body disease.Methods: Based on clinical features and 18F-Florbetaben and dopamine transporter PET, we recruited 126 controls, 90 patients with typical Alzheimer’s disease (57 pure Alzheimer’s disease, 32 Lewy body variant of Alzheimer’s disease), 77 with typical Lewy body disease (56 pure Lewy body disease, 21 dementia with Lewy bodies with amyloid deposition), and 42 with typical Alzheimer’s disease/dementia with Lewy bodies. We used logistic regression analysis to investigate the effect of APOE4 on the risk of each disease and general linear models to investigate the independent and interaction effects of APOE4, Alzheimer’s disease, and Lewy body disease on β-amyloid deposition and cognition. Results: APOE4 was associated with increased risks of all disease subtypes except pure Lewy body disease. APOE4 was associated with increased frontal β-amyloid burden, typical Alzheimer’s disease was associated with increased β-amyloid burden in all lobar regions, and typical Lewy body disease interacted with APOE4 to increase the occipital β-amyloid burden. The interaction of APOE4 and typical Alzheimer’s disease was associated with more severe memory dysfunction, while that of APOE4 and typical Lewy body disease was associated with poorer Clinical Dementia Rating Sum of Boxes. Conclusions: Our findings suggest that the APOE4 effect on disease risk is dependent on β-amyloid deposition and APOE4 is associated with β-amyloid deposition regardless of the clinical diagnosis; however, APOE4 further interacts with typical Lewy body disease to induce worse general cognition and higher occipital β-amyloid deposition and it interacts with typical Alzheimer’s disease to decrease memory function. This study highlights the possible interaction of β-amyloid and Lewy body pathologies converging in the occipital cortex through the APOE4 effect.
Hypoparathyroidism and Pseudohypoparathyroidism in Pregnancy: An Italian Retrospective Observational Study
Authors: Marcucci Gemma , Altieri Paola , Benvenga Salvatore , Bondanelli Marta , Camozzi Valentina , Cetani Filomena , Cianferotti Luisella , Duradoni Mirko , Fossi Caterina , Uberti Ettore degli , Famà Fausto , Mantovani Giovanna , Marcocci Claudio , Masi Laura , Pagotto Uberto , Palermo Andrea , Parri Simone , Zatelli Maria Chiara , Ruggeri Rosaria Maddalena , Brandi Maria Luisa 
Published: November 2020

Abstract
Background: Hypoparathyroidism (HypoPT) or pseudo-hypoparathyroidism (pseudo-HypoPT) during pregnancy may cause maternal and fetal/neonatal complications. In this regard, only a few case reports or case series of pregnant or lactating women have been published. The purpose of this study was to describe clinical and biochemical course, pharmacological management, and potential adverse events during pregnancy and post-partum in pregnant women with HypoPT or pseudo-HypoPT. This was a retrospective, observational, multicenter, study involving nine Italian referral centers for endocrine diseases affiliated with the Italian Society of Endocrinology and involved in “Hypoparathyroidism Working Group”.Results: This study identified a cohort of 28 women (between 2005 and 2018) with HypoPT (n=25, 80% postsurgical) and pseudo-HypoPT (n=3). The mean calcium carbonate and calcitriol doses of both groups were increased during pregnancy compared to pre-pregnancy period. During the three trimesters of pregnancy the mean calcium carbonate and calcitriol doses were variable, remaining unchanged throughout gestation respectively in 40% and 60% of women with HypoPT, whilst tended to decrease from the third trimester to the post-partum six months. Most identified women (~70%) did not display maternal complications and (~90%) maintained mean serum albumin-corrected total calcium levels within the low-to-mid normal reference range (8.5±0.8 mg/dl) during pregnancy. The main complications related to pregnancy period included: preterm birth (n=3 HypoPT women), and history of miscarriages (n=6 HypoPT women and n=2 pseudo-HypoPT women). Conclusion: This study shows that mean serum albumin-corrected total calcium levels were carefully monitored during pregnancy and post-pregnancy, with limited evaluation of other biochemical parameters, such as serum phosphate, 24h urinary calcium, 25-OH vitamin D, and creatinine clearance. To avoid complications in mothers and offspring, intense biochemical, clinical and pharmacological monitoring during pregnancy and breastfeeding is highly recommended.
Precipitation Cloud Identification Based on Faster-RCNN for Doppler Weather Radar
Authors: Ran Yuanbo , Wang Haijiang , Tian Li , Wu Jiang , Li Xiaohong 
Published: November 2020

Abstract
Precipitation clouds are visible aggregates of hydrometeor in the air that floating in the atmos-phere after condensation, which can be divided into stratiform cloud and convective cloud. Different precipitation clouds often accompany different precipitation processes. Accurate identification of precipitation clouds is significant for the prediction of severe precipitation processes. Traditional identification methods mostly depend on the differences of radar reflectivity distribution morphology between stratiform and convective precipitation clouds in three-dimensional space. However, all of them have a common shortcoming that the radial velocity data detected by Doppler Weather Radar has not been applied to the identification of precipitation clouds because it is insensitive to the convective movement in the vertical direction. This paper proposes a new method for precipitation clouds identification based on deep learning algorithm, which is according the distribution morphology of multiple radar data. It mainly includes three parts, which are Constant Altitude Plan Position Indicator data (CAPPI) inversion for radar reflectivity, Radial projection of the ground horizontal wind field by using radial velocity data, and the precipitation clouds identification based on Faster-RCNN. The testing result shows that the method proposed in this paper performs better than typical existing algorithms in terms of accuracy rate. Moreover, this method boasts great advantages in running time and adaptive ability.