bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the Controlling Factors for CO2 Sequestration in Depleted Shale Reservoirs Using Data Analytics and Machine Learning
Authors: Hassan Baabbad Hassan Khaled , Artun Emre , Kulga Burak 
Published: June 2022

Abstract
Carbon capture and sequestration (CCS) will generate an industry comparable to, if not greater than, the existing oil and gas sector. Carbon capture and sequestration is the capture of carbon-dioxide from refineries, industrial facilities, and major point sources such as power plants and storing it in subsurface formations. Subsurface formations like unconventional reservoirs can be a good example for storing carbon-dioxide. Despite its importance in the oil and gas industry, our understanding of carbon-dioxide sequestration in unconventional reservoirs still needs to be developed. The objective of this paper is to identify the most important parameters that affect carbon-dioxide sequestration in depleted shale reservoirs using data-analytics and machine-learning.
The dataset used was an extensive shale reservoir dataset which comprised a large set of numerical simulation scenarios. A quality check of the input data was performed for missing variables. Then, a data-analytics based investigation was followed to develop insights into the relationship between reservoir parameters and operational parameters, which were the main predictor variables, as well as between the predictor variables and the main response variable: cumulative CO2 injected. Machine-learning based predictive models such as multiple linear regression, regression tree, bagging, random forest, and boosting were built to predict the cumulative CO2 injected. Variable importance (screening) was carried out to determine the crucial parameters which drive CO2 sequestration performance in shale reservoirs.
The results revealed that there is a relationship between the reservoir and operational parameters, together with the predictor variables and response variable. Operational parameters displayed a monotonic relationship with the cumulative CO2 injected. Random forest provided the best predictive ability among the machine-learning techniques consistent with the theoretical background of random forest. Regression tree had the worst predictive ability mainly because of overfitting. Screening results show that stimulated reservoir volume fracture permeability was the most important variable for the performance of CO2 sequestration. The findings and results reported in this study will allow the exploration and production companies to determine what causes low-performance or high-performance CO2 sequestration process in shale reservoirs.
Impact of Field Development Strategies on CO2 Trapping Mechanisms: A Case Study of CO2-EGR in the DND Tight Gas Field
Authors: Jia Ying , Huang Lei , Yan Jin 
Published: June 2022

Abstract
This paper presents field-scale compositional reservoir flow modeling in the DND tight gas field, to demonstrate the relative partitioning of 3 during and after CO2 injection. The model was developed to study the effect of structural trapping, solubility trapping, residual trapping, and mineralization trapping on the partitioning of CO2 in gas (free or residual), and brine phases over time. Furthermore, we investigated the impact of various injection scenarios, such as Injection pressure, Injection rate and Injection time, on the different trapping mechanisms. First, we used a high-resolution geo-model, which was constructed from wireline logs, seismic surveys, core data, and stratigraphic interpretation. As the initial distribution of fluids plays a vital role in CO2 partitioning, a comprehensive pressure-production history matching was completed. The hysteresis model was used to calculate the amount of CO2 trapped as residual. The water-rock reaction models among CO2 and minerals were added to analyze the mineralization trapping mechanism. CO2 solubility into brine was verified based on experiments. The model results show a new understanding of relative CO2 partitioning in porous media. Although it was believed that structural trapping is the largest of the trapping mechanisms during CO2 injection and post-injection, our results show that in sandstone tight gas field like DND tight gas field, the solubility of CO2 in gas plays a very important role, even in the first stage of CO2 injection. Porosity changes caused by the reaction among CO2 and different minerals during CO2 storage were also analyzed. Comprehensive models were run to estimate the amount of trapped CO2 during and after the injection period. The present work provides valuable insights for optimizing gas production and CO2 storage in sandstone reservoirs like DND tight gas field.
Time-Dependent Moderating Effect of Exposure to Nature on Relations between Perceived Interior Crowding, Social Isolation, and Psychological Distress of Residents during Pandemic of COVID-19
Authors: Mousavinia Seyyedeh Fatemeh 
Published: June 2022

Abstract
Due to the results of the COVID-19 epidemic on mental health, some studies have highlighted the positive effects of nature exposure. Nevertheless, this beneficial role has not yet been explored over time of the pandemic. In mid-rise housing, in addition to the small home size, most people do not have access to private outdoor spaces and they use shared open and green areas. It is necessary to understand how household density and nature exposure affect people's mental health in this housing type. The current study examines the longitudinal changes in (a) social isolation, (b) psychological distress, (c) intensity of the effect of social isolation on psychological distress, and (d) moderating effect of nature exposure on the relation between perceived interior crowding, social isolation, and psychological distress. Focusing on six mid-rise housing developments in Mashhad, longitudinal data were collected from 718 middle-aged women (Mage = 49.63, SD = 12.39) in two waves during the Iranian national lockdowns (wave1 in May 2019 and wave2 in April 2020, before nationwide vaccination). A paired-sample t-test showed increased social isolation and psychological distress after one year of the pandemic. Also, using structural equation modeling and multi-group analysis (wave 1 vs. wave 2) revealed that social isolation has an increasing influence on psychological distress over time. Exposure to nature moderates the effect of perceived interior crowding on psychological distress. However, this moderating role is time-dependent and nature exposure during the time did not necessarily assist in reducing the negative impact of perceived interior crowding. Finally, at any given time, nature exposure mitigated the effect of social isolation on psychological distress.
The association of blood urea nitrogen to creatinine ratio and the prognosis of critically ill patients with cerebral infarction: a cohort study
Authors: Chen Ting , Li Aiping , Gong Qi , Zhou Lin , Zhao Yixuan , Zhou Zhiwen , Zhou Wensheng 
Published: June 2022

Abstract
Background
To evaluate the association between blood urea nitrogen (BUN) to creatinine (Cr) (BUN/Cr) ratio with the in-hospital mortality of critically ill patients with cerebral infarction in intensive care unit (ICU).
Methods
In this cohort study, the data of 3059 participants with cerebral infarction were collected from the Medical Information Mart for Intensive Care (MIMIC)-III and the MIMIC-IV database. After propensity score matching (PSM) on age and gender, 2085 people were involved in and divided into the alive group (n = 1390) and the dead group (n = 695). All subjects in the ICU were followed up until death or discharge. Multivariate logistic analyses were applied for identifying the confounders and the association between BUN/Cr and mortality of cerebral infraction.
Results
The median follow-up time was 10.5 days. Among 2778 participants, 695 were dead at the end of follow-up. Univariate analysis revealed that BUN/Cr [risk ratio (RR) = 1.01, 95% confidence interval (CI): 1.01–1.02] might be associated with the in-hospital mortality of cerebral infraction patients. After adjusting respiratory failure, malignant cancer, anticoagulation, liver disease, white blood cell (WBC), red cell distribution width (RDW) percent, glucose, bicarbonate and temperature, BUN/Cr was associated with an increased risk of in-hospital mortality of cerebral infraction patients (RR = 1.01, 95%CI: 1.01–1.02).
Conclusion
This study evaluated the association between BUN/Cr and the in-hospital mortality of cerebral infarction patients in ICU and found BUN/Cr was associated with an increased risk of in-hospital mortality of patients with cerebral infarction in ICU especially in males, and those with respiratory failure, malignant cancer and without liver disease, as well as those receiving anticoagulation. The findings of our study reminded the clinicians to pay attention on the level of BUN/Cr in cerebral infarction patients in ICU.
Multi-objective optimization of fused deposition modelling for mechanical properties of biopolymer parts using Grey-Taguchi Method
Authors: KUMAR KAPIL , Singh Hari 
Published: June 2022

Abstract
Development of customized functional products for engineering and biomedical applications is a prime objective of 3D printing techniques. As a biomedical application, fabrication of surgical instruments, namely, forceps and hemostat using fused deposition modelling (FDM) process is proposed in this article. The mechanical properties of FDM processed parts depend on various process parameters such as layer height, infill pattern, top/bottom pattern, number of top/bottom layers, infill density, flow, number of shells, printing temperature, build plate temperature, printing speed and fan speed. Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of poly lactic acid (PLA) parts printed by FDM. Taguchi’s L27 orthogonal array (OA) is used to perform the experimentation. Analysis of variance (ANOVA) is used to ascertain the significance of the process parameters and their percent contributions on the evaluation indexes. Finally, an optimal set of the FDM process parameters is obtained by using grey relational analysis (GRA) in order to fabricate the best parts having comprehensive mechanical properties. The types of defects and strong bonding between rasters have been examined by Scanning electron microscopy (SEM).
Outbreak investigation of community associated methicillin-resistant Staphylococcus aureus in a primary and secondary school in Eastern Switzerland
Authors: Waldeck Frederike , Seiffert Salome , Manser Susanne , Zemp Danuta , Walt Angela , Berger Christoph , Albrich Werner C. , Schlegel Matthias , Roloff Tim , Egli Adrian , Nolte Oliver , Kahlert Christian R. 
Published: June 2022

Abstract
Background
In 2018 the number of newly detected methicillin-resistant Staphylococcus aureus (MRSA) cases in children attending primary (age 6–12 years) and secondary school (age 13–16 years) nearly doubled compared to previous years.
Methods
This observation initiated an epidemiological outbreak investigation including a cross-sectional study to determine source of the outbreak, colonization frequency and to identify risk factors for transmission using a questionnaire and to end the outbreak.
Results
During the investigation, 49 individuals were detected with 57 corresponding isolates. Based on the case definition combined with whole genome sequencing, a core cluster was identified that shared common genetic features and a similar antimicrobial susceptibility pattern (efflux-mediated macrolide resistance, tetracycline susceptibility along with presence of Panton-Valentine leukocidin).
Conclusions
Epidemiologic evaluation identified a distinct school as a common risk factor. However, the source of the clustered infections within that school could not be further specified. No further cases could be detected after decolonization of infected and colonized children.
Fate and health risk assessment of heavy metals in Brassica chinensis L. (pak-choi) and soil amended by sludge-based biochar
Authors: Zhang Shijie , Gu Weihua , Bai Jianfeng , Dong Bin , Zhao Jing , Zhuang Xuning 
Published: June 2022

Abstract
Biochar is widely used in agriculture to efficiently solve the problem of sludge. In this study, sludge-based biochar (referred to as BC1, BC2, and BC3) was prepared by mixing sludge with FeCl 3 , Na 2 SiO 3 , and Ca (H 2 PO 4 ) 2 , respectively. Then, it was mixed with fresh soil to plant Brassica chinensis L. The analysis of the effects of the three biochar types showed that all of them were beneficial to the growth of Brassica chinensis L. We added the biochar to the soil and found that the concentration of heavy metals did not exceed the recommended threshold. Additionally, the aboveground part of Brassica chinensis L. met the standard requirement for food safety (GB2762-2017). Notably, BC3 stood out with the best effect on the growth of Brassica chinensis L. and resulted in the improvement of the physical and chemical properties of soil such as ammonium nitrogen, available phosphorus, and available potassium (BC3 was followed by BC2 and BC1). BC3 could efficiently inhibit the migration of heavy metals, thereby reducing the overall heavy metal pollution level and ameliorating the soil nutrients. BC3 could increase the organic carbon by 258.92%, available phosphorus by 234.45%, and available potassium by 37.12% compared with the CK group. The THQ and TTHQ estimates of Brassica chinensis L. were lower than one, indicating that the health risk of heavy metal intake was not prominent. Additionally, the application of the proposed biochar could reduce the form of F1 (acid extracted state) and increase the form of F4 (residue state) in soil. Overall, we conclude that the application of the proposed biochar can promote the root absorption of heavy metals and inhibit the migration of heavy metals.
Time-Frequency Analysis based Deep Interference Classification for Frequency Hopping System
Authors: Xu Changzhi , Ren Jingya , Yu Wanxin , Jin Yi , Cao Zhenxin , Wu Xiaogang , Jiang Weiheng 
Published: June 2022

Abstract
It is known that, interference classification plays an important role in protecting the authorized communication system and avoiding its performance degradation in the hostile environment. In this paper, the interference classification problem for the frequency hopping communication system is discussed. Considering the possibility of presence multiple interferences in the frequency hopping system, in order to fully extract effective features of the interferences from the received signals, the linear and bilinear transform based composite time-frequency analysis method is adopted. Then the time-frequency spectrograms obtained from the time-frequency analysis are constructed as matching pairs and input to the deep neural network for classification. In particular, the Siamese neural network is used as the classifier, where the paired spectrograms are input into the two sub-networks of the deep networks, and these two sub-networks extract the features of the paired spectrograms for interference type classification. The simulation results confirm that the proposed algorithm can obtain higher classification accuracy than both traditional single time-frequency representation based approach and the AlexNet transfer learning or convolutional neural network based methods.
Performance Analysis of Generalized Frequency Division Multiplexing in Various Pulse-shaping Filter with raised cosine and root raised cosine filter
Authors: Gupta Megha , Gamad R.S 
Published: June 2022

Abstract
Generalized frequency division multiplexing (GFDM) is non orthogonal multicarrier modulation scheme which is suitable for the fifth generation (5G) of wireless network. Pulse shaping filter design in GFDM system have effects on symbol error rate performance due to inter symbol interference (ISI). In this paper Contribute to symbol error rate (SER) performance in GFDM system with additive white Gaussian noise channel (AWGN), zero forcing channel (ZF) rayleigh fading has been analyzed for pulse shaping filter namely raised cosine (RC) and root raised cosine filter (RRC) and also Simulation is done and results are reported in terms of symbol error rate (SER), signal to noise ratio (SNR), different value of roll off factor and different modulation technique. Comparison of simulation results of this method with existing methods is done and improvements in result are obtained as compared to existing.
Hydropower development in the Himalaya: Identifying critical river stretches
Authors: Bartwal Tanuja , Nautiyal Prakash 
Published: June 2022

Abstract
Two hydroelectric projects are operational in the upper and lower stretches of the river Alaknanda near Lambagarh and Srinagar that are respectively ~ 140 km apart. The health of the river ecosystem in the flowing stretches between and below these projects was bio-assessed, based on widely used diatom indices and van Dam ecologic values computed by OMNIDIA software. Samples were collected from Birahi, the semi-natural stretch - 53 km downstream of power-house, Narkota, the impacted stretch 27 km upstream Srinagar dam and Bagwan, the highly regulated stretch 22 km downstream Srinagar. IPS and IBD revealed mild pollution in upper and lower stretch compared to relatively elevate at Narkota. However TDI indicates moderate organic pollution at Birahi and Narkota, whereas the IDSE indicates low degradation at all stations. The prevalence of tolerant N-autotroph, β-mesosprobe, mesotrophic and aquatic to aerophilic categories of van Dam environmental variables indicate that a certain level of impact already persists due to organic-cum-nutrient load and perturbed flow-regime. The prevalence of eutrophic and moderate O2 categories shows that the ecosystem is in critical state at Narkota, causing a disrupted continuum.
Understanding the dynamic of POMS infection and the role of microbiota composition in the survival of Pacific oysters, Crassostrea gigas.
Authors: Delisle Lizenn , Laroche Olivier , Hilton Zoë , Burguin Jean-François , Rolton Anne , Berry Jolene , Pochon Xavier , Boudry Pierre , Vignier Julien 
Published: June 2022

Abstract
Background:In recent years, the aquaculture industry of Crassostrea gigas has been severely impacted by geographically widespread outbreaks of a polymicrobial disease, the Pacific Oyster Mortality Syndrome (POMS). The aetiology of these recurring summer mortality events and the disease progression have notably been recently described in France, revealing a combined development of viral (namely the Ostreid Herpesvirus, OsHV-1 µVar) and bacterial infections. In New Zealand (NZ), mass mortality episodes associated with OsHV-1 have been recorded in juvenile C. gigas since 2010 and selective breeding to improve resistance to OsHV-1 has been effectively used to mitigate the impact of the disease. However, POMS infection process and the role of the host-microbiota during infection have still not been well established in NZ. Results:Using a laboratory-based experimental infection approach, we challenged ten biparental oyster families with previously established contrasted genetically based ability to survive POMS in the field. Molecular analyses (viral load quantification, viral gene expression and 16S rRNA gene sequencing) were combined with histopathological observations to describe the temporal kinetics of infection to POMS and to characterize the role of microbiota during infection. Our main findings showed (1) a delay in viral infection resulting in a late onset of mortality in oysters compared to previous observations from France, and (2) a lack of evidence of major fatal bacteraemia in infected oysters. Bacterial profiling associated the microbiota composition with mortality rate, viral load, and viral replication, allowing the identification of potentially deleterious and beneficial bacterial taxa that can influence the outcome of the disease. Mycoplasma ASV-1 was identified as a significant predictor of mortality in oysters. Conclusion:Collectively, these results could improve current disease management and aquaculture practices and help understanding the mechanisms behind genetic resistance to POMS. Ultimately, microbiome composition could be used to predict oyster mortality following exposure to OsHV-1 and be used as a complementary screening tool in selective breeding and/or a diagnostic tool to determine shellfish health.
miR-4653-3p overexpression is associated with a poor prognosis of pancreatic ductal adenocarcinoma via HIPK2 downregulation
Authors: Hirabayashi Kenichi , Miyazawa Masaki , Takanashi Yumi , Morimachi Masashi , Kawanishi Aya , Saika Tsubasa , Nakagohri Toshio , Nakamura Naoya 
Published: June 2022

Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignant tumor. Several upregulated or downregulated microRNAs (miRNAs) are associated with invasiveness, tumorigenesis, and prognosis of PDAC. This study evaluated miR-4653-3p expression and pancreatic intraepithelial neoplasia (PanIN) using in situ hybridization and the association between miR-4653-3p expression and clinicopathological factors in patients with PDAC. The miR-4653-3p target was also identified. Ninety PDAC cases, including 30 normal pancreatic ducts, 30 low-grade PanINs, and 30 high-grade PanINs were evaluated. miR-4653-3p expression was absent in normal pancreatic ducts and increased in the following order: normal pancreatic duct, low-grade PanIN, high-grade PanIN, and PDAC. High miR-4653-3p expression significantly correlated with advanced pathological T stage, lymph node metastasis, advanced UICC stage, perineural invasion, venous involvement, and shorter overall survival. Homeodomain Interacting Protein Kinase 2 (HIPK2) was identified as a miR-4653-3p target based on mRNA microarray analysis and database screening. In vitro analysis using pancreatic cancer cells showed that miR-4653-3p significantly downregulated HIPK2 expression. Immunohistochemical analysis showed that HIPK2 expression inversely correlated with miR-4653-3p expression in PDAC surgical specimens. In contrast to miR-4653-3p, HIPK2 expression decreased gradually from the normal pancreatic duct to low-grade PanIN, high-grade PanIN, and PDAC. Additionally, low HIPK2 expression was associated with shorter overall survival in patients with PDAC. These results indicate that miR-4653-3p is associated with tumorigenesis and a worse prognosis, partly by reducing HIPK2 expression.