bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigations on the Directional Propagation of Hydraulic Fracture in Hard Roof of Mine: Utilizing a Set of Fractures and the Stress Disturbance of Hydraulic Fracture
Authors: Xing Yuekun , Huang Bingxiang , Li Binghong , Liu Jiangfeng , Cai Qingwang , Hou Mingxiao 
Published: December 2021

Abstract
Directional fracturing is fundamental to weakening the hard roof in the mine. However, due to the significant stress disturbance in the mine, principal stresses present complicated and unmeasurable. Consequently, the designed hydraulic fracture (HF) extension path is always oblique to principal stresses. Then, the HF will present deflecting propagation, which will restrict the weakness of the hard roof. In this work, we proposed an approach to drive the HF to propagate directionally in the hard roof, utilizing a set of hydraulic fractures and their stress disturbance. In this approach, directional fracturing in the hard roof is conducted via the sequential fracturing of three linear distribution slots. The disturbed stresses produced by the first fracturing (in the middle) are utilized to restrict the HF deflecting extension of the subsequent fracturing. Then, the combined hydraulic fractures constitute a roughly directional fracturing trajectory in rock, i.e., the directional fracturing. To validate the directional fracturing approach, the cohesive crack (representing rock fracture process zone (FPZ)) model coupled with the extended finite element method (XFEM) was employed to simulate the 2D hydraulic fracturing process. The benchmark of the above fracturing simulation method was firstly conducted, which presents the high consistency between simulation results and the fracturing experiments. Then, the published geological data of the hard roof in Datong coal mine (in Shanxi, China) was employed in the fracturing simulation model, with various principal stress differences (2~6 MPa) and designed fracturing directions (30°~60°). The simulation results show that the disturbing stress of the first fracturing significantly inhibits the deflecting propagation of the subsequent fractures. More specifically, along the direction parallel to the initial minimum principal stress, the extension distance of the subsequent hydraulic fractures is 2~3 times higher than that of the deflecting HF in the first fracturing. The fracturing trajectory of the proposed direction fracturing method deviates from the designed fracturing path by only 2°~14°, reduced by 76%~93% compared with the traditional fracturing method utilizing a single hydraulic fracture. This newly proposed method can enhance the HF directional propagation ability more effectively and conveniently in the complex and unmeasurable stress field. Besides, this directional fracturing method can also provide references for the directional fracturing in the oil-gas and geothermal reservoir.
Complete Equation of State Thermal Formulation for Simulation of CO2 Storage
Authors: Moncorgé Arthur , Petitfrère Martin , Thibeau Sylvain 
Published: December 2021

Summary
Storage of carbon dioxide (CO2) in depleted gas reservoirs or large aquifers is one of the available solutions to reduce anthropogenic greenhouse gas emissions. Numerical modeling of these processes requires the use of large geological models with several orders of magnitude of variations in the porous media properties. Moreover, modeling the injection of highly concentrated and cold CO2 in large reservoirs with the correct physics introduces numerical challenges that conventional reservoir simulators cannot handle. We propose a thermal formulation based on a full equation of state (EoS) formalism to model pure CO2 and CO2 mixtures with the residual gas of depleted reservoirs. Most of the reservoir simulators model the phase equilibriums with a pressure-temperature-based formulation. With this usual framework, it is not possible to exhibit two phases with pure CO2 contents. Moreover, in this classical framework, the crossing of the phase envelope is associated with a large discontinuity in the enthalpy computation, which can prevent the convergence of the energy conservation equation. In this work, accurate and continuous phase properties are obtained, basing our formulation on enthalpy as a primary variable. We first implement a new phase-split algorithm with input variables as pressure and enthalpy instead of the usual pressure and temperature, and we validate it on several test cases. This algorithm can model situations in which the mixture can change rapidly from one phase to the other at constant pressure and temperature. Then, treating enthalpy instead of temperature as a primary variable in both the reservoir and the well modeling algorithms, our reservoir simulator can model situations with pure or near pure components, as well as crossing of the phase envelope that usual formulations implemented in reservoir simulators cannot handle. We first validate our new formulation against the usual formulation on a problem in which both formulations can correctly represent the physics. Then, we show situations in which the usual formulations fail to represent the correct physics and that are simulated well with our new formulation. Finally, we apply our new model for the simulation of pure and cold CO2 injection in a real depleted gas reservoir from the Netherlands.
Deep learning based multi-batch calibration for classification in various omics
Authors: Wang Qian , Niu Jingyang , Xu Wei , Wei Dongming , Qian Kun 
Published: December 2021

Abstract
Background: The amount of available biological data has exploded since the emergence of high-throughput technologies, which is not only revolting the way we recognize molecules and diseases but also bringing novel analytical challenges to bioinformatics analysis. In the last decade, deep learning has become a dominant technique in data science. However, classification accuracy is plagued with domain discrepancy. Notably, in the presence of multiple batches, domain discrepancy typically happens between individual batches. The recently proposed pair-wise adaptation approach may be suboptimal as it fails to eliminate the external factors across multiple batches and takes the classification task into account simultaneously. Results: We propose a joint deep learning framework for integrating batch effect removal and classification upon various omics data. To this end, we validate it on two private metabolomics (MALDI MS) datasets and one public transcriptomics (scRNA-seq) dataset. Especially for the former, we have achieved the highest diagnostic accuracy (ACC), with notable ~10% improvement than over state-of-the-art methods. Overall, these results indicate that our approach removes batch effect more effectively than conventional methods and yields more accurate classification results for smart diagnosis.
Preparation of Modified PVA Copolymer by DAAM/ADH and Cross-Linking Mechanism for Paper
Authors: Li Kaibin , Li Xiaorui , Wang Dan , Yang Baoping , Liu Yihe , Wang Haihua , Shen Yiding 
Published: December 2021

Abstract
Herein, a novel modified polyvinyl alcohol(DA-IPVA) used as sizing agent was prepared by using diacetone acrylamide(DAAM) as graft monomer and N-(isobutoxymethyl)acrylamide(IBMA) as self-cross-linking monomer. The effect of the amount of DAAM on the properties of emulsion, film and sizing paper was discussed. The surface micro-structure of the sizing paper was characterized by SEM and AFM. The addition of DAAM/ADH and IBMA endowed DA-IPVA with cross-linked active group and increased cross-linking density and hydrophobicity after ADH was added into the emulsion and the cross-linking structure was formed. The enhancing mechanism of surface sizing agent for paper was revealed. The DA-IPVA can be cross-linked on the surface and inside of the paper to form a dense network structure, which improves the bonding force between the fibers. When the mole fraction of DAAM of the cross-linking monomer is 8%, the surface sizing performance of the paper is obviously improved compared with the base paper. The dry and wet strength is increased by 266.5% and 334.3% respectively, and the folding resistance is increased 2946.67%. This study can have a profound impact on the development of the technology of cross-linking surface sizing agent for paper.
The Cytotoxicity of PM2.5 and its Effect on the Secretome of Normal Human Bronchial Epithelial Cells
Authors: Sui Zhigang , Song Xiaoyao , Wu Yujie , Hou Rui , Liu Jianhui , Zhao Baofeng , Liang Zhen , Chen Jiping , Zhang Lihua , Zhang Yukui 
Published: December 2021

Abstract
Exposure to airborne fine particulate matter (PM2.5) induced various adverse health effects, such as metabolic syndrome, systemic inflammation and respiratory infection. Many works have studied the influence of PM2.5 exposure to intracellular proteome and the underlying mechanism. But the extracellular proteome changes under PM2.5 exposure, and the correlation between secretome changes and PM2.5-induced cytotoxicity remains confusing. Herein, the cytotoxicity of PM2.5 on normal human bronchial epithelia cells (BEAS-2B) was evaluated and the secretome profile of BEAS-2B cells before and after PM2.5 exposure was investigated. The secretion of 83 proteins (58 up-regulated and 25 down-regulated) was differentially expressed upon PM2.5 treatment. In addition to apoptosis, extracellular matrix (ECM) organization, complement activation and RNA splicing were also found to be involved in PM2.5 mediated cytotoxicity. These results provide an insight into the underlying mechanism of respiratory injury caused by PM2.5.
Maternal Antibiotic Use and Infections During Pregnancy and Offspring Asthma: The Norwegian Mother, Father and Child Cohort Study and a Nationwide Register Cohort
Authors: Rantala Aino K. , Tapia German , Magnus Maria C , Stene Lars Christian , Jaakkola Jouni JK , Stordal Ketil , Karlstad Oystein , Nystad Wenche 
Published: December 2021

Abstract
Maternal antibiotic use during pregnancy has been linked to asthma risk in children, but the role of underlying infections remains unclear. We investigated the association of maternal antibiotic use and infections during pregnancy with offspring risk of asthma. We used two population-based cohorts: the Norwegian Mother, Father and Child Cohort Study (MoBa) (n=53 417) and a register cohort (n=417 548). Asthma was defined based on dispensed asthma medications at 7 and 13 years from the Norwegian Prescription Database. Self-reported information on antibiotic use and infections during pregnancy was available in MoBa, while registrations of dispensed prescriptions was used to classify use of antibiotics in the register-based cohort. Maternal antibiotic use during pregnancy was associated with asthma at 7 years in both cohorts (aRR 1.23, 95% CI 1.11 - 1.37 in MoBa and aRR 1.21, 95% CI 1.16 - 1.25 in the register-based cohort) and asthma at 13 years in the register cohort (aRR 1.13, 95% CI 1.03-1.23) after adjusting for maternal characteristics. In MoBa, the estimate was attenuated after adjusting for infections during pregnancy. Maternal lower and upper respiratory tract infections (aRR 1.30, 95% CI 1.07 - 1.57 and aRR 1.19, 95% CI 1.09 - 1.30, respectively) and urinary tract infections (aRR 1.26, 95% CI 1.11 - 1.42) showed associations with asthma at 7 after adjusting for confounders, but estimates decreased after adjustment for antibiotics during pregnancy. Our findings suggest that both maternal antibiotic use and infections during pregnancy might be associated with an increased risk of asthma in childhood.
KiESEL - The Children’s Nutrition Survey to Record Food Consumption for the Youngest in Germany
Authors: Diouf Friederike , Golsong Nadine , Höpfner Tobias , Nowak Nicole , Lindtner Oliver 
Published: December 2021

Abstract
BackgroundWith KiESEL, the Children’s Nutrition Survey to Record Food Consumption, the German Federal Institute for Risk Assessment (BfR) collected representative food consumption data for children aged six months up to five years. KiESEL was one of five modules of KiGGS Wave2 (German Health Interview and Examination Survey for Children and Adolescents) conducted by the Robert Koch-Institute (RKI). The objective was to update the consumption data for children in Germany and to fill a data gap for the age group of five-year-old children. The study provides an up-to-date and comprehensive database that will be used for exposure assessment, as part of risk assessment of Germany’s youngest consumers. MethodsIn the years 2014 to 2017, more than 1000 children from all over Germany participated in KiESEL. During home visits, survey staff conducted a questionnaire-based interview including a food propensity questionnaire (FPQ) on seldom eaten foods and questions concerning consumption outside home, dietary habits and diet during first year. The interviewer measured the children’s height and weight. Families and childcare workers filled out a food record, covering three consecutive days and one independent day. Data are based on the FPQ and present consumption frequencies. Depending on the question, socioeconomic status (SES) and migration background were considered.Results 1104 participants had an interview and filled out the questionnaire on usual food intake, seldom eaten foods and consumption away from home. They were included in sample1. 1008 of these participants additionally reported food consumption of at least three days (sample2). 91.2 % of the children follow no special diet and 0.8 % are vegetarians. 7 % of the older children consuming soya-drink. For some foods differences in consumption across SES or migration status were noted. Children from families with higher SES consume more often soya-based substitute milk as families with lower SES (p<0.00005).ConclusionsKiESEL gathered up-to-date consumption data for more than 1000 children living in Germany, aged six month up to including five years. The data will be used for risk assessments of the BfR and provided to national and international partners.
Rice Root-Associated Endophytic Microbiome in Correspondence To Different Levels of Salinity At Indian Sundarban Areas
Authors: Das Gargi , Dhal Paltu Kumar 
Published: December 2021

Abstract
The present study attempted to analyse rice root endogenous microbial diversity and their relationship with soil salinity and physicochemical factors in the salt stressed region of Sundarbans, India using amplicon metagenomics approaches. Our investigation indicates, the unique microbiome at slightly acidic nutrient enriched non-saline zone characterized by microbial genera that reported either having plant growth promotion (Flavobacterium, Novosphingobium and Kocuria) or biocontrol abilities (Leptotrichia) whereas high ionic alkaline saline stressed zone dominated with either salt-tolerant microbes or less characterized endophytes (Arcobacter and Vogesella). The number of genera represented by significantly abundant OTUs was higher at the non-saline zone compared to that of the saline stressed zone probably due to higher nutrient concentrations and the absence of abiotic stress factors including salinity. Physicochemical parameters like nitrogen, phosphorus and potassium were found significantly positively correlated with Muribaculaceae highly enriched at the non-saline zone. However, relative dissolved oxygen was found significantly negatively correlated with Rikenellaceae and Desulfovibrionaceae, enriched in the non-saline soil. This study gives a well resolved picture of microbial community composition impacted by salinity and other rhizospheric soil factors.
Visualization of Hidden Structure and Shape in Ct Image via Non-Linear Perspective Foreground and Back Ground Projection
Authors: pan parthee , Perinbam Raja Paul , Murthy Krishna , Nagalingam Shanker Rajendiran , s krishna kumari , B chinthamani 
Published: December 2021

Abstract
The neurologist analyse the brain images to diagnose the disease via structure and shape of the part in the scanned Medical images such as CT, MRI, and PET.The Medical image segmentation perform less in the regions where no or little contrast,artefacts over the different boundary regions. The manual process of segmentation show poor boundary differentiation dueto discernibility in shape and location, intra and inter observer reliability. In this paper, we propose a dyadic Cat optimization (DCO) algorithm to segment the regions in the brain from CT and MRI image via Non- linear perspective Foreground and Back Ground projection. The DCO algorithm remove the artefacts in the boundary regions and provide the exact structure and shape of the brain regions. The DCO algorithm show the region boundary such as plerygomaxillary fissure, occipital lobe, vaginal process zygomatic arch, maxilla and piriform aperture with high visibility in the regions of inadequately visible boundary and distinguish the deformable shape. The DCO algorithm show the increased SSIM and 90 percent accuracy.
BRCA1 Interactors - Rad50 and BRIP1: As Prognostic and Predictive Molecules for the Severity of Triple-Negative Breast Cancer
Authors: Laha Suparna , Katheeja Muhseena N , Das Shankar , Das Ranajit 
Published: December 2021

Abstract
BRIP1 is one of the major interacting partner of BRCA1 which plays an important role in repair by homologous recombination (HR). This gene is mutated in around 4% cases of breast cancer, however, its mechanism of action is unclear. In this study, we presented the fundamental role of BRCA1 interactors BRIP1 and RAD50 in the development of differential severity in Triple-Negative Breast Cancer(TNBC) among various affected individuals. We showed that in some TNBC lines like MDA-MB-231 the functioning of both BRCA1/TP53 is compromised. Furthermore, the sensing of DNA damage is affected, depicted through the low expression of damage sensing molecule Rad50 and reduced formation of H2AX foci. Due to less damage sensing capability and low availability of BRCA1 at the damage sites, the repair by HR becomes inefficient leading to more damage. Accumulation of damage sends a signal for over activation of NHEJ repair pathways. Over expressed NHEJ molecules with compromised HR and checkpoint conditions lead to higher proliferation and error-prone repair, which increases the mutation rate and corresponding tumor severity. The severity phenotypes were more in cells having compromised BRCA1-BRIP1 functioning. The in silico analysis of the TCGA-UCSC xena datasets with genes expression in deceased population shows a significant correlation of BRCA1 expression with OS in TNBCs (0.0272). The association of BRCA1 with OS becomes stronger with the addition of BRIP1expression (0.000876**). Since the overall survival(OS) is directly proportional to the extent of severity, the data analysis hints at the role of BRIP1 in controlling the severity of TNBC.
Do High-mobility Group Box 1 Gene Polymorphisms Affect the Incidence of Differentiation Syndrome in Acute Promyelocytic Leukemia?
Authors: Hoseinzadeh Ghazaleh , Mohammadzadeh Zahra , Chahardouli Bahram , Moghaddam Kamran Ali , Mousavi Seyed Asadollah , Omidkhoda Azadeh , Rostami Shahrbano 
Published: December 2021

Abstract
Differentiation syndrome (DS) is an inflammatory complication seen in some patients with acute promyelocytic leukemia (APL) undergoing differentiation therapy with all-trans retinoic acid (ATRA) and/or arsenic trioxide (ATO). It is unknown how DS occurs, but it is believed that it is caused by inflammatory cytokines release from differentiating leukemic cells. High mobility group box-1 (HMGB1) is a DNA-binding protein that acts as a cytokine outside of cells and may play a role in inflammation. This study was conducted to determine whether HMGB1 polymorphisms (rs1360485, rs2249825 and rs1060348) are associated with the incidence of differentiation syndrome in acute promyelocytic leukemia patients treated with all-trans retinoic acid and arsenic trioxide. One hundred and thirty APL patients and 100 healthy controls were included. Seventeen patients with differentiation syndrome were selected according to the PETHEMA criteria. Tetra-primer ARMS polymerase chain reaction (tetra-ARMS PCR) was used to determine the genotype distribution of polymorphisms. DNA sequencing was done to validate the results. In both healthy and APL patients, AA was the most frequent genotype in rs1360485 followed by AG and GG. CC, CG, and GG were the most frequent genotypes in rs2249825 polymorphism in the order mentioned. CC was more frequent than CT, and CT was more frequent than TT in rs1060348. There was no correlation between HMGB1 polymorphisms and the incidence of differentiation syndrome based on genetic models (p-value > 0.05). As a result, HMGB1 polymorphisms are not probably associated with DS development in APL patients treated with ATRA and ATO.
Atomistic Evidence of Nucleation Mechanism for the Direct Graphite-to-Diamond Transformation
Authors: Luo Duan , Yang Liuxiang , xie hongxian , Sriniva Srilok , Tian Jinshou , Sankaranarayanan Subramanian , Arslan Ilke , Yang Wenge , Mao Ho-Kwang , Wen Jianguo 
Published: December 2021

Abstract
The direct graphite-to-diamond transformation mechanism has been a subject of intense study and remains debated concerning the initial stages of the conversion, the intermediate phases, and their transformation pathways. Here, we successfully recover samples at early conversion stage by tuning high-pressure/high-temperature conditions and reveal direct evidence supporting the nucleation-growth mechanism. Atomistic observations show that intermediate orthorhombic graphite phase mediates the growth of diamond nuclei. Furthermore, we observe that quenchable orthorhombic and rhombohedra graphite are stabilized in buckled graphite at lower temperatures. These intermediate phases are further converted into hexagonal and cubic diamond at higher temperatures following energetically favorable pathways in the order: graphite -> orthorhombic graphite -> hexagonal diamond, graphite -> orthorhombic graphite -> cubic diamond, graphite -> rhombohedra graphite -> cubic diamond. These results significantly improve our understanding of the transformation mechanism, enabling the synthesis of different high-quality forms of diamond from graphite.