bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Empirical Correlation to Predict the Dew Point Pressure using Intelligent Algorithms
Authors: Khan Mohammad Rasheed , Kalam Shams , Tariq Zeeshan , Abdulraheem Abdulazeez 
Published: November 2019

Abstract
Dew point is an important thermodynamic parameter for a gas condensate reservoir and has a very complicated nature due to its reliance on the composition of the mixture. For accurate prediction of this property, it is imperative to develop accurate models that are not computationally expensive. Currently, there exists various methodologies to estimate dew point pressure at various temperatures and hydrocarbon compositions. These methods include equation of states (EOS), analytical methods, and empirical correlations. These methods, however, have limitations in terms of accuracy or computational expense. This paper proposes a new empirical correlation to predict the dew point pressure for gas condensate reservoirs utilizing computational intelligence algorithms, namely Artificial Neural Networks (ANN), Functional Networks (FN), and Support Vector Machines (SVM).
The available data set comprises of dew-point pressure, temperature, component mole fractions (C7+, CH4, N2, CO2, and H2S). This data is divided into two parts to allow for the training and development of the new model and testing/validation phase. For ANN model the weights and bias as well as the neurons in the hidden layer are tuned to result in an optimized model. In the FN model, a number of learning algorithms were tested to reach to the optimum model to get accurate results. For SVM, three main parameters were explored to develop the intelligent model which includes epsilon, kernel parameters and ‘C’.
This study has resulted in the development of an empirical equation that is able to predict the dew point pressure accurately consuming the least amount of computation time. The proposed equation can be applied for a variable range of composition and temperature/ pressure conditions. This is done by incorporating the effect of composition through two equations for normal-boiling point condition as well as the critical-temperature of the mixture. Model accuracy has been validated through a comparative analysis incorporating actual experimental data from various gas-condensate reservoir samples. These data-set includes various published sources and the results of Wilson, Whitson, and EOS.
This work showcases the effectiveness of intelligent models in providing answers with the least amount of error. A comparative analysis for the various computational models is done to come up with a correlation proving accurate results for the dew point pressure. The proposed correlation can predict the output with relatively small errors.
Deterministic Pipe Network Modelling for Fractured Rocks
Authors: Jing Yu , Armstrong Ryan , Mostaghimi Peyman 
Published: November 2019

Abstract
The fracture network plays a critical role in controlling flow pathways in fractured rock. Thus, transmissibility study of fracture networks via different flow modelling methods is of importance. Compared with direct flow simulation, the pipe network model is an effective means of modelling fluid flow in fracture network due to its computational efficiency. However, the characterisation of the fracture network topology as well as the equivalent conductivity of the pipes are still challenging to credibly predict the permeability. Also, pipe network models are commonly constructed based on stochastic Discrete Fracture Network (DFN) models with more uncertainties, which also requires a number of stochastic DFN realisations to be created. In this paper, we develop a novel Pipe Network Modelling (PNM) framework for fractured media, where the PNM is constructed based on deterministic DFN models that are directly derived from micro-CT images. By comparing permeability values obtained from PNMs and results from micro-CT images and voxelised DFNs, we conclude that PNM modelling can effectively estimate the permeability of original fracture networks, while requiring significantly less computational cost. In addition to the advantage of computational efficiency, PNM is more preferable for the challenging multi-phase flow simulation.
Emerging pesticides responsible for suicide in rural Sri Lanka following the 2008-2014 pesticide bans
Authors: Weerasinghe Manjula , Pearson Melissa , Konradsen Flemming , Agampodi Suneth , Sumith J.A. , Jayamanne Shaluka , Senanayake S.M.H.M.K. , Rajapaksha Sandamali , Eddleston Michael 
Published: November 2019

Abstract
BackgroundSri Lanka has reduced its overall suicide rate by 70% over the last two decades through means restriction, through means restriction, through a series of government regulations and bans removing highly hazardous pesticides from agriculture. We aimed to identify the key pesticide(s) now responsible for suicides in rural Sri Lanka to provide data for further pesticide regulation.MethodsWe performed a secondary analysis of data collected prospectively during a cluster randomized controlled trial in the Anuradhapura district of Sri Lanka from 2011-16. The identity of pesticides responsible for suicides were sought from medical or judicial medical notes, coroners’ records, and the person’s family. Trend analysis was done using a regression analysis with curve estimation to identify relative importance of key pesticides. ResultsWe identified 337 suicidal deaths. Among them, the majority 193 (57.3%) were due to ingestion of pesticides while 82 (24.3%) were due to hanging. A specific pesticide was identified in 105 (54.4%) of the pesticide suicides. Ingestion of carbosulfan or profenofos was responsible for 59 (56.2%) of the suicides with a known pesticide and 17.5% of all suicides. The increasing trend of suicides due to carbosulfan and profenofos over time was statistically significant (R square 0.846, F 16.541, p 0.027). ConclusionIngestion of pesticides remains the most important means of suicides in rural Sri Lanka. The pesticides that were once responsible for most pesticide suicides have now been replaced by carbosulfan and profenofos. Their regulation and replacement in agriculture with less hazardous pesticides will further reduce the incidence of both pesticide and overall suicides in rural Sri Lanka.
Towards Developing a Model for the Evaluation of Hospital Disaster Resilience: A Systematic Review
Authors: Aliabadi Saeed Fallah , Ostadtaghizadeh Abbas , Ardalan Ali , Fatemi Farin , Khazaei Bijan , Mirjalili Mohammad Reza 
Published: November 2019

Abstract
Background: Hospitals play a vital role in disaster stricken regions. The resilient hospitals will be able to provide essential services to affected people and it can mitigate the risk of injuries during and after disasters. This study aimed to obtain the indicators required for the evaluation of hospital resilience. Methods: This systematic review was conducted in 2018. Through this systematic review, international electronic databases were investigated for the research studies published in English. The exclusion and inclusion criteria were determined to extract the hospital resilience indicators. These indicators will be used in order to develop a model to keep the system performance at an acceptable level during disasters. Results: Out of 1794 research studies published until September 2018, 89 articles and guidelines with full text were surveyed. Thirty-two articles and guidelines were then selected and analyzed to collect the indicators related to hospital disaster resilience (HDR). The domains and the indicators were extracted from these selected research studies. The authors collected and categorized them into three domains and twenty seven subdomains. The three domains included constructive, infrastructural, and administrative resilience. The relevant indicators were designed for each subdomain to assess HDR. Conclusion : Since diverse indicators affect hospital resilience, other studies should be conducted to propose some models or tools to quantify the hospital resilience in different countries and scopes with an all hazards approach. Key words : Disaster; Hospital; Resilience; Structural and Non-structural Systems; Indicators
Susceptibility of BAFF-var allele carriers to severe SLE with occurrence of lupus nephritis
Authors: Friebus-Kardash Justa , Trendelenburg Marten , Eisenberger Ute , Ribi Camillo , Chizzolini Carlo , Huynh-Do Uyen , Lang Karl Sebastian , Wilde Benjamin , Kribben Andreas , Witzke Oliver , Dolff Sebastian , Hardt Cornelia 
Published: November 2019

Abstract
Background: Dysregulation of the B-cell activating factor (BAFF) system is involved in the pathogenesis of systemic lupus erythematosus (SLE). Increased serum concentrations of BAFF are related to lupus nephritis and disease activity among SLE patients. Recently, a variant of the BAFF-encoding gene, BAFF-var, was identified to be associated with autoimmune diseases, in particular SLE, and to promote the production of soluble BAFF. The present study aimed to assess the prevalence of BAFF-var in a cohort of 195 SLE patients and to analyze the association of the BAFF-var genotype (TNSF13B) with various manifestations of SLE. Methods: A cohort of 195 SLE patients from Central Europe, including 153 patients from the Swiss SLE Cohort Study and 42 patients from the University Hospital Essen, Germany, underwent genotyping for detection of BAFF-var allele. Results: Of the 195 patients, 18 (9.2%) tested positive for BAFF-var variant according to the minor allele frequency of 4.6%. The presence of BAFF-var was associated with the occurrence of lupus nephritis (p=0.038) (p=0.03 and p=0.003). Among various organ manifestations of SLE, the presence of BAFF-var was associated with the occurrence of lupus nephritis (p=0.038; odds ratio [OR], 2.4; 95% confidence interval [CI], 0.89-6.34) and renal activity markers such as proteinuria and hematuria (p=0.03; OR, 2.4; 95% CI, 0.9-6.4 for proteinuria; p=0.003; OR, 3.9; 95% CI, 1.43-10.76 for hematuria). SLE patients carrying the BAFF-var allele exhibited increased disease activity at study entry, as determined by the physician's global assessment (PGA: p=0.002; OR, 4.8; 95% CI, 1.54-14.93) and the SLE Disease Activity Index (p=0.012; OR, 3.5; 95% CI, 1.12-11.18). Consistent with that, the percentage of patients treated with immunosuppressive agents at study entry was higher among those carrying the BAFF-var allele than among those tested negative for BAFF-var (p=0.006; OR, 3.7; 95% CI, 1.27-10.84). Conclusions: Our results indicate an association between the BAFF-var genotype and increased severity of SLE. Determining the BAFF-var status of SLE patients may improve the risk stratification of patients for whom the development of lupus nephritis is more likely and thus may be helpful in the follow-up care and treatment of SLE patients.
Prediction of perioperative outcome after hepatic resection for pediatric patients
Authors: Liu Jianxia , Zhang Yunfei , Zhu Hai , Qiu Lin , guo chunbao 
Published: November 2019

Abstract
Background Hepatic resection is associated with significant risk of morbidity and mortality. Optimising the surgical techniques and perioperative management may improve in operative morbidity and mortality. However, perioperative variables involved in the improvement for postoperative outcomes in pediatric hepatectomy have not been defined.Methods We retrospectively reviewed 156 consecutive pediatric patients who underwent hepatectomy at our center (an academic tertiary care hospital) between 2006 and 2016. Baseline demographic variables, intraoperative variables, complications, and hospital stay were explored. The patients were further investigated using univariate and multivariate analysis for the factors involved in the postoperative outcomes.Results Of the conditions requiring resections, malignant and benign liver diseases accounted for 47.4% (74/156) and 52.6% (82/156), respectively. The overall hospital mortality was 1.9% (3/156) and the overall postoperative complication rate was 44.2% (69/156). Anatomical resections were performed in 128 patients (82.1%), including 14(9.0%) extended hepatectomies. Eighty percent of patients had three or more segments resected. The median operative time was 167.7 (65-600) minutes and median estimated blood loss was 320.1(10-1600) mL. On multivariate analysis, the estimated blood loss (EBL) (mL) (OR, 2.19; 95CI, 1.18-3.13; p=0.016), extent of hepatectomy (OR, 1.81; 95CI, 1.06-2.69; p=0.001) and pringle maneuver (OR, 1.38; 95CI, 1.02-1.88; p=0.038) were the independent predictors of postoperative complications.Conclusions Extent of hepatectomy and estimated blood loss are largely responsible for the perioperative complications. with the surgical devices and management amelioration, like pringle maneuver, the treatment planning may be optimize in pediatric liver resection.
Biomedical Science Knowledge Contributes to the Development of Adaptive Expertise and Formation of a Professional Identity: An Applied Thematic Analysis of Medical Students' Essays
Authors: Dickinson Bonny Lynn , Gibson Kristine , VanDerKolk Kristi , Greene Jeffrey , Rosu Claudia A , Navedo Deborah D , Porter-Stransky Kirsten A , Graves Lisa E 
Published: November 2019

Abstract
Background
Intensive study of the biomedical sciences remains a core component of undergraduate medical education with medical students often completing up to two years of biomedical science training prior to entering clerkships. While it is generally accepted that biomedical science knowledge is essential for clinical practice because it forms the basis of clinical reasoning and decision-making, whether medical students perceive an expanded role for their biomedical science knowledge remains to be examined.

Methods
We conducted an applied thematic analysis to explore how medical students in the first clerkship year perceived the relevance of biomedical science knowledge to clinical medicine during this pivotal time as they begin their transition from students to physicians. To identify previously unidentified perspectives and insights, we asked students to write brief essays in response to the prompt: How is biomedical science knowledge relevant to clinical medicine?

Results
Applied thematic analysis of students’ essays revealed ten codes from which four themes emerged. The analysis revealed novel perspectives previously unidentified by survey studies and focus groups. Specifically, students perceived their biomedical science knowledge as contributory to the development of adaptive expertise and professional identity formation, both viewed as essential developmental milestones for medical students.

Conclusions
The results of this study suggest that biomedical science knowledge contributes to medical students’ acquisition of adaptive expertise and their development of a professional identity. These findings have important implications in the setting of accelerated medical school programs in which training in the biomedical sciences are compressed or truncated. Thus, the contextual factors of the learning environment, including both explicit and tacit elements of the formal, informal, and hidden curriculum, that enable biomedical science knowledge to contribute to these developmental processes need to be identified and studied so that they are leveraged rather than lost during curricular reform.
Effect of Diabetes Mellitus on short-term prognosis of 227 pyogenic liver abscess patients after hospitalization
Authors: Du Zhaoqing , Zhou Xinchen , Zhao Junzhou , Bi Jianbin , Ren Yifan , Zhang Jia , Lin Yuxin , Wu Zheng , lV Yi , Zhang XuFeng , Wu Rongqian 
Published: November 2019

Abstract
Background: Pyogenic liver abscess (PLA) is an inflammatory disease with increasing incidence. When it occurs with diabetes mellitus (DM), risk of recurrence and the mortality may increase. However, the effect of DM on short-term prognosis of PLA patients after hospitalization remained unknown.Methods: 227 PLA patients who received treatment at the First Affiliated Hospital of Xi’an Jiaotong University from January 2011 to January 2018 were retrospectively enrolled. They were divided into two groups as DM group (n=61) and Non-DM group (n=166). In the DM group, HbA1C level <7% was considered to be good-control of glycaemia (n=23). The clinical characteristics and overall short-term survivals were analyzed.Results: The proportion of PLA patients with DM was 26.87%. In the DM group, there was a higher incidence of hypertension and Candida spp. infection. Conservative administration and percutaneous drainage were mainly used in patients with good- (60.87%) and poor-control (60.53%) of glycaemia, respectively. During follow-up, 24 (10.57%) died due to uncontrolled systemic infections and other serious complications. Compared with PLA patients without DM, patients in the DM group had significantly increased 6-month mortality rate after discharge (Log-Rank test, P =0.021). Poor-control of glycaemia did not reduce the six-month survival, while the recurrence rate of PLA within three months showed an almost 3-fold increase (13.16% vs. 4.35%). Further multivariate analyses found that DM was the only independent risk factor for the PLA six-month survival (odd ratio [OR]: 0.097, 95% confidence interval [CI]: 0.018-0.526, P =0.007). However, the blood glucose level had no significant effect on the short-term survival of PLA patients with DM (Log-Rank test, P =0.218).Conclusions: In PLA patients, DM aggravated short-term mortality and blood glucose levels should be well controlled.
The Persistence of Child and Adolescence Mental Healthcare: Results from Registry Data
Authors: Dijk Hermien , Freriks Roel , Alessie Rob , Mierau Jochen 
Published: November 2019

Abstract
Background: Previous studies on the persistence of child and adolescent mental healthcare do not consider the role of time-invariant individual characteristics. Estimating persistence of healthcare using standard linear models yields biased estimates due to unobserved heterogeneity and the autoregressive structure of the model. This study provides estimates of the persistence of child and adolescent mental healthcare taking these statistical issues into account. Methods: We use registry data of more than 80,000 Dutch children and adolescents between 2000 and 2012 from the Psychiatric Case Registry Northern Netherlands (PCR-NN). In order to account for autocorrelation due to the presence of a lagged dependent variable and to distinguish between persistence caused by time-invariant individual characteristics and a direct care effect we use Arellano-Bond estimation. In further analyses we assess the robustness of our results to policy reforms, different definitions of care and diagnosis decomposition. Results: All estimation results for the direct care effect (true state-dependence) show a positive coefficient smaller than unity with a main effect of 0.215 ( p < 0.01), which indicates that the process is stable. Persistence of care is found to be 0.065 ( p < 0:05) higher for females. Additionally, the role of time-invariant characteristics in the persistence of care appears to be large. Further analyses indicate that (1) policy reforms only slightly affected persistence of care, (2) results are robust to different definitions of care and (3) persistence of care does not differ significantly across subgroups. Conclusions: The results indicate that a substantial part of persistence is due to time-invariant individuals characteristics. Additionally, we find that in the absence of further shocks a sudden increase of 10 care contacts in the present year is associated with approximately 3 additional care contacts at some point in the future. This result provides essential information about the necessity of budget increases for future years in the case of exogenous increases in healthcare use.
Identification of major depressive disorder disease-related genes and functional pathways based on system dynamic changes of network connectivity
Authors: Geng Ruijie , Huang Xiao 
Published: November 2019

Abstract
Objective : Major depressive disorder (MDD) is a neurologic disorder, involving complex abnormal biological functions and the neural network. In this study, we aimed to compare different network connectivity of pathological changes of brain tissues under different conditions, and dynamic analyze the biological pathways and genes significantly associated with disease progression, and further to predict potential drug targets.
Methods : Datasets of mRNA expression profiles of samples of postmortem anterior cingulate cortex (ACC) and prefrontal cortex (PFC) from patients with MDD were downloaded from GEO database. We used a method based on system network analysis. Correlation networks based on co-expression were constructed. Topological properties of the networks were analyzed and compared.
Results : Our results showed that the lesions of brain tissues in MDD patients were not synchronized and alterations of biological functions were not consistent either. ACC showed a greater degree of abnormality as compared to PFC suggesting a higher correlation with disease progression. We consequently analyzed the signaling pathways enriched by DEGs and further cross talk genes that bridge the multiple pathways were also identified. Through construction of the pathway-gene complex network, the genes and signaling pathways with top10 degrees were extracted, which are more likely to be the potential novel therapeutic targets. We also mined the drugbank database for the top10 cross talk genes to explore their drugable target potential. The results suggested that CACNA1A, PTDSS2 and CD19 differentially expressed in both ACC and PFC may correlate with depression progression or other cerebral nerve system related diseases, are more likely to become the new drug targets.
Conclusion : Co-expression network and tissue comparing analysis are capable to identify MDD disease related signaling pathways and cross talk genes with potential to be novel drug targets.