bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hepatic dysfunction and adverse outcomes after total arch repair of acute type A aortic dissection: Application of the MELD-XI score
Authors: Lin Xinfan , Jiang Debin , Xie Linfeng , Wu Qingsong , He Jian , Chen Liangwan 
Published: July 2022

Abstract
Background
This study was aimed to investigate the incidence and outcomes of patients with postoperative hepatic dysfunction (PHD) after total arch repair of acute type A aortic dissection, and further explore the risk factors for severe adverse outcomes.
Methods
The clinical data of 227 patients with AAAD treated by modified triple-branched stent graft implantation from January 2020 to January 2021 were collected retrospectively. Including preoperative, surgical and postoperative data. Logistics regression was used to determine the independent risk factors of severe adverse outcomes.
Results
In the early stage after operation, a total of 153 patients were complicated with PHD, accounting for 67.4%. The incidence of severe adverse outcomes in patients with PHD was 43.1%. We found that preoperative moderate/severe pericardial effusion [odds ratio (OR): 11.645, 95% confidence interval (CI): 1.144, 143.617, P = 0.045], preoperative imaging data suggest the celiac trunk involvement [OR: 6.136, 95% CI 1.019, 36.930, P = 0.048], CPB time > 180min [OR: 4.855, 95% CI 1.218, 15.761, P = 0.034], early postoperative serum albumin [OR: 0.935, 95% CI 0.856, 0.985, P = 0.026] were independent risk factors for severe adverse outcomes in patients with PHD.
Conclusions
PHD was associated with increased early mortality and morbidity. Preoperative moderate/severe pericardial effusion, preoperative celiac trunk involvement, Cardiopulmonary bypass (CPB) time > 180 min and early postoperative serum albumin were identified as independent risk factors for severe adverse outcomes in patients with PHD.
Investigation of optimal gestational weight gain for twin pregnancy in Southwest China: a retrospective study
Authors: Gao Li , Lei Cuirong , Zhou Shuwei , Liao Qianqian , Mei Lingwei , Zhong Qimei , Lan Xia , Chen Ya , Wang Lan 
Published: July 2022

Abstract
There is a lack of data on gestational weight gain (GWG) in twin pregnancies. We divided all the participants into two subgroups: the excellent outcome subgroup and the adverse outcome subgroup. They were also stratified according to prepregnancy body mass index (BMI): underweight (< 18.5 kg/m2), normal weight (18.5–23.9 kg/m2), overweight (24–27.9 kg/m2), and obese (≥ 28 kg/m2). We used 2 methods to confirm the optimal range of GWG. The first method was a statistical-based method (the interquartile range of GWG in the excellent outcome subgroup). The second method was an outcome-based method that compared the incidence of pregnancy complications in the population below or above the optimal GWG and analysed the relationship between weekly GWG and pregnancy complications to justify the rationality of optimal weekly GWG through logistic regression. The optimal GWG calculated in our study was lower than that recommended by the Institute of Medicine (IOM). Except for the obese group, in the other 3 BMI groups, the overall disease incidence within the recommendation was lower than that outside the recommendation. Insufficient weekly GWG increased the risk of gestational diabetes mellitus, premature rupture of membranes, preterm birth and fetal growth restriction. Excessive weekly GWG increased the risk of gestational hypertension and preeclampsia. The association varied with prepregnancy BMI. We provide preliminary Chinese recommendations for optimal GWG (16-21.5 kg for underweight, 15-21.1 kg for normal weight, 13–20 kg for overweight), except for obesity, due to the limited sample size.
A Comprehensive Investigation on Application of Machine Learning for Optimization of Process Parameters of Laser Powder Bed Fusion Processed 316L Stainless Steel
Authors: Eshkabilov Sulaymon , Ara Ismat , Azarmi Fardad 
Published: July 2022

Abstract
Metal 3D printing has gained a lot of attention among industries since it offers a practical solution to problems rising during manufacturing of parts and components with complex geometry. This is an additive technology that eliminated several fabrication steps and at the same time reduces material waste during manufacturing process. However, in all additive manufacturing technologies, the final properties of the parts are determined by the operational process parameters. In this study, several machine learning algorithms were examined to characterize the effects of the printing process parameters on relative density, hardness, yield strength, and tensile strength in manufactured parts. It was possible by using “Big Data” collected from a large number of previously published articles on application of Laser Powder Bed Fusion (LPBF) for 3D printing of 316L stainless steel samples. Among different process parameters, laser power, laser energy density, and scanning speed were proven to have the largest effects directly on physical and mechanical properties of LPBF processed parts. Six different classification models and five support vector machine regression-based models were tested to find the most accurate prediction algorithm. To validate the obtained results from the applied machine learning models, a set of 316L specimens were produced using LPBF technology using a random set of process parameters. The physical and mechanical properties of 3D printed samples were tested and compared to the ones those predicted from the optimum models from machine learning analysis. The results were in great agreement, which shows the high accuracy of the developed machine learning algorithms in this study.
A novel defined N7-methylguanosine-related LncRNAs signature for predicting the prognosis of Hepatocellular carcinoma
Authors: Luo Yijiang , Zhang Xueyong , Yang Hao 
Published: July 2022

Abstract
Background. Hepatocellular carcinoma (HCC) is a highly heterogeneous disease with poor prognosis, making the prediction of the prognosis much challenges. N7-methylguanosine (m7G) is a common modification with roles in eukaryotes. However, the value of m7G-related LncRNAs in predicting prognosis of HCC still remains to be further elucidated. This study aimed to find new potential biomarkers for predicting prognosis and precision medication. Methods. To build reliable predictive models,we obtained transcriptome and clinical data of HCC from The Cancer Genome Atlas (TCGA). M7G-related prognostic lncRNAs were selected by coexpression analysis and univariate Cox regression. The least absolute shrinkage and selection operator (LASSO) was utilized to construct the m7G related lncRNA model. Patients in TCGA cohort were divided into train group and test group. Applying the muti-lncRNA model,the patients were divided into high risk group and low risk group .The Kaplan–Meier analysis,time-dependent receiver operating characteristics (ROC), univariate Cox (uni-Cox) regression, multivariate Cox (multi-Cox) regression, nomogram, clinical characteristics and calibration curves were made to verify and evaluated the model. Furthermore ,we used principal component analysis (PCA), t-distributed stochastic-neighbor embedding (tSNE), immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) to verify the signature in two risk groups .Results. A model with 4 m7G-related lncRNAs was constructed. The HCC patients were divided into two risk groups according to the model.Patients in the low-risk group showed significantly better outcome compared with patients in the high-risk group both in the train group and the test group (P < 0.001 in the TCGA train cohort and P = 0.001 in the test cohort). The risk score was an independent predictor for prognosis in multivariate Cox regression analyses (HR> 1, P< 0.01). Receiver operating characteristic (ROC) curve analysis show predictive capacity. Analysis of clinical characteristics and tumor microenvironment (TME) between risk groups showed significant difference (p=0.038). Functional analysis revealed different immune-related pathways were enriched, and immune status were different between two risk groups. Mediation analysis with IC50 revealed that the two risk group were significantly different, which could be a guidance of systemic treatment. Conclusion. A novel m7G-related LncRNAs signature can be used for prognostic prediction in HCC. Targeting m7G may be a therapeutic alternative for HCC.
Research on yield strength estimation and lift-off elimination method based on incremental permeability features
Authors: Li Kaiyu , Liu Yiran , Wang Pin , Zhang Zhengda , Jia Yinliang , Zeng Jie 
Published: July 2022

Abstract
The incremental permeability(IP) is related to the reversible domain movements of ferromagnetic materials during the period of dynamic magnetization. The IP signal generated by reversible domain motion is weak, during the experiment, the vibration of the platform and the uneven surface of the sample will affect the lift-off value of the probe, resulting in the distortion of the IP signal. In order to solve this problem, the change of IP feature γ reflecting the average grain size of the material under different lift-off conditions is studied, and the corresponding relationship between this feature and lift-off is quantitatively analyzed. In this paper, the fitting method of γ curve is revised to reduce its fitting under different lifting conditions. Two parameters aγ and bγ are proposed to modify the γ curve when lift-off changes. Finally, the yield strength of the material is estimated under different lift-off conditions, and the estimation error is less than 10%.
Colonic TRPV4 overexpression is related to constipation severity
Authors: Mihara Hiroshi , Uchida Kunitoshi , Watanabe Yoshiyuki , Nanjo Sohachi , Sakumura Miho , Motoo Iori , Ando Takayuki , Minemura Masami , Muhammad Jibran Sualeh , Yamamoto Hiroyuki , Itoh Fumio , Yasuda Ichiro 
Published: July 2022

Abstract
BackgroundChronic constipation is prevalent and involves both colon sensitivity and various changes in intestinal bacteria, particularly mucosa-associated microflora. Here we examined regulatory mechanisms of TRPV4 expression by co-culturing colon epithelial cell lines with intestinal bacteria and their derivatives. We also investigated TRPV4 expression in colon epithelium from patients with constipation. MethodsColon epithelial cell lines were co-cultured with various enterobacteria (bacterial components and supernatant), folate, LPS, or short chain fatty acids (SCFAs). TRPV4 expression levels and promoter DNA methylation were assessed using pyrosequencing, and microarray network analysis. For human samples, correlation coefficients were calculated and multiple regression analyses were used to examine the association between clinical background, rectal TRPV4 expression level and mucosa-associated microbiota.ResultsCo-culture of CCD841 cells with P. acnes, C. perfringens, or S. aureus transiently decreased TRPV4 expression but did not induce methylation. Co-culture with clinical isolates and standard strains of K. oxytoca, E. faecalis, or E. coli increased TRPV4 expression in CCD841 cells, and TRPV4 and TNF-alpha expression were increased by E. coli culture supernatants but not bacterial components. Although folate, LPS, IL-6, TNF-alpha, or SCFAs alone did not alter TRPV4 expression, TRPV4 expression following exposure to E. coli culture supernatants was inhibited by butyric acid or TNF-alphaR1 inhibitor and increased by p38 inhibitor. Microarray network analysis showed activation of TNF-alpha, cytokines, and NOD signaling. TRPV4 expression was higher in constipated patients from the terminal ileum to the colorectum, and multiple regression analyses showed that low stool frequency, frequency of defecation aids, and duration were associated with TRPV4 expression. Meanwhile, incomplete defecation, time required to defecate, and number of defecation failures per 24 hours were associated with increased E. faecalis frequency.ConclusionsColon epithelium cells had increased TRPV4 expression upon co-culture with K. oxytoca, E. faecalis, or E. coli supernatants, as well as TNFα-stimulated TNFαR1 expression via a pathway other than p38. Butyrate treatment suppressed this increase. Epithelial TRPV4 expression was increased in constipated patients, suggesting that TRPV4 together with increased frequency of E. faecalis may be involved in the pathogenesis of various constipation symptoms.
Landslide Susceptibility Mapping in Three Gorges Reservoir Area Based on GIS and Boosting Decision Tree Model
Authors: Miao Fasheng , Zhao Fancheng , Wu Yiping , Li Linwei , Török Ákos 
Published: July 2022

Abstract
Recognized as one of the most destructive geological disasters, a myriad of landslides has revived and developed in the Three Gorges Reservoir area under the combined action of various detrimental factors, becoming a nightmare for the residents over vicinity. Therefore, the pertinently regional landslide susceptibility mapping (LSM) is of great significance for disaster prevention and mitigation. In this study, LSM was prepared by using a boosting-C5.0 decision tree model. Under the landslide verification of on-site investigations, the study area was divided into accumulation and rock areas, and a total of 12 impact factors including triggering factors and causing factors were skillfully selected as model inputs to felicitously explore spatial characteristics related to the landslide. TOL and VIF were employed to determine the multicollinearity among the impact factors. The independent training (80%) and validation (20%) datasets were constructed by random sampling for LSM. ANN, C5.0, and SVM were selected for comparative analysis. In addition, uncertainty analysis was appositely performed for boosting-C5.0 model. The results show that there is no rigorous multicollinearity among the impact factors proposed in this paper. The landslide susceptibility in the study area is divided into low, moderate, high, and very high. The highest susceptibility area distributes along the riverside and farmland where the landslide ratio is 37.05% in boosting-C5.0 model. Then the ROCs were expropriated to infer the accuracy of each model. The boosting-C5.0 performed the best with the largest area under the curve (AUC) in both accumulation and rock areas, reaching at 0.991 and 0.990 in the validation sets, respectively. Finally, the composite modification of the 5 validation sets shows that the uncertainty of boosting-C5.0 is concentrated in the intermediate probability areas of susceptibility. This research reveals that the machine learning model can be used to evaluate the susceptibility of regional landslides, which could provide a basis for the risk management and control of geological disasters.
Climatic control on the location of continental volcanic arcs
Authors: Muller Veleda A. P. , Sternai Pietro , Sue Christian , Simon-Labric Thibaud , Valla Pierre G. 
Published: July 2022

Abstract
Orogens and volcanic arcs at continental plate margins are primary surface expressions of convergent plate tectonics. Although it is established that climate affects the shape, size, and architecture of orogens via orographic erosion gradients, the crustal upwelling of magmas and location of volcanic arcs have been considered insensitive to erosion. However, available data reveal westward migration of late-Cenozoic volcanic activity in the Southern Andes and Cascade Range where orography drives an eastward migration of the topographic water divide by increased precipitation and erosion along west-facing slopes. Here we use thermomechanical numerical modeling to show that orographic erosion and leeward topographic shift may entail asymmetric crustal structures, driving magma upwelling toward the region of enhanced erosion. Considering the different tectonic histories between the Southern Andes and the Cascade Range, the orographic erosion gradient is a plausible shared causal mechanism behind the late-Cenozoic westward migration of the regional volcanic arcs.
Uni-variate and Bi-variate Inverted Exponential-Teissier Distribution in Bayesian and Non-Bayesian framework to Model Stochastic Dynamic Variation of Climate data
Authors: THAKUR DEBJOY , Bhattacharya Sumangal , Das Ishapathik 
Published: July 2022

Abstract
This article provides a new Inverted Exponential Teissier (IET) distribution to model an extreme value data set and explain temporal dependence in environmental statistics employing Bi-variate probability distribution. We deduce its various statistical properties, including descriptive statistics, characterization, and different measurements of reliability. The model parameters are estimated using Bayesian and Non-Bayesian frameworks. For exploring the dependency structures between two geographical Random Variables (RV), we extend the IET to Bivariate IET distribution, (BIET). We introduce a novel time-series forecasting algorithm based upon copula assuming stationarity of the data set. We validate the proposed method using extensive simulation studies with different possible combinations of parameter values. This method is applied to the seasonal rainfall data of Kerala from 1901 to 2017. We estimate the monsoon rainfall using median regression derived from BIET, where summer rainfall data is used as an important covariate. We found the Mean Absolute Percentage Error (MAPE) is 19.242% on the test data set.
Governing the Green Economy in the Arctic
Authors: Garbis Zoe , McCarthy Erin , Orttung Robert Wilson , Poelzer Gregory , Shaiman Melissa , Tafrate Jacob 
Published: July 2022

Abstract
In Sweden’s Norrbotten County, a “green transition” driven by market demand and new normative structures is underway, creating a regional mega-project designed to put Sweden at the forefront of emerging green industries. These industries, such as carbon-neutral steel fabrication, battery production, and data center hosting, all require large amounts of energy, land, and minerals. This paper applies the regional environmental governance framework to Arctic data to examine which stakeholders have the capacity to impose their agenda on the Arctic environment and the points of conflict and collaboration during this period of accelerated growth. The paper tests the hypothesis that regional governance performs better than other levels in accommodating a plurality of interests. A case study on Norrbotten County’s industrial mega-project centered around Luleå, Sweden shows the dominance of EU norms for reducing greenhouse gas emissions in this region. However, the existing regional governance model does a poor job of integrating the local Indigenous Sami preferences for land use. At the core of the difference between actors advancing the green economy and the local reindeer herders are different conceptions of nature and sustainability.
Evaluation of ABCD Water Balance Conceptual Model Using Remote Sensing Data in Ungauged Watersheds (A Case Study: Zarandeh, Iran)
Authors: Baseri Masoud , Mahjoobi Emad , Rafiei Fatemeh , Baseri Moean 
Published: July 2022

Abstract
Water balance is one of the most important issues in water resources management and water consumption planning. ABCD water balance conceptual model is a very suitable simulation tool due to its simplicity, low requirement of input data, and providing various components of the water balance. As the lack of data is always a major challenge in many developing countries, remote sensing technology was used to collect the required data for the Zarandeh sub-basin in Neyshabur in the Northeastern Iran. To do so, IMERG precipitation satellite products and ERA5 temperature reanalysis data were used. Outputs were evaluated using five statistical indices including Pearson Correlation Coefficient (R), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency Coefficient (NSE), and BIAS Coefficient. The Results indicated that products are accurate, and there is a high correlation between outputs and observed data. To calculate the water balance, remote sensing products were applied in the form of the ABCD model. The uncertainties in the model parameters were assessed through Fuzzy numbers. In addition, the Monte Carlo method was employed to calibrate them with two different objective functions including NSE and Coefficient of Determination (R2). The results showed that the ABCD water balance model is an accurate tool for simulating the surface runoff of the Zarandeh sub-basin. Finally, the model was applied to the Sebi sub-basin located in Torbat-e-Heydariyeh, which had a moderate performance showing that the model parameters should be recalibrated in each region.
The Characteristics of Pseudophakic Retinal Detachment and Risk Factors of Recurrence in the North of Spain
Authors: Gibelalde Ane , Pinar-Sueiro Sergio , Ibarrondo Oliver , Martínez-Soroa Itziar , Mendicute Javier 
Published: July 2022

Abstract
Purpose: The present study was designed to gain knowledge about the prognostic factors and evolution of pseudophakic retinal detachment (PRD). To analyse the main characteristics of PRD, such as the mean time to retinal detachment following cataract surgery, as well as the clinical factors associated with the risk of recurrence, and with worse anatomical and functional outcomes.Methods: Retrospective study of 330 patients with PRD between 2012-2020.All patients are pseudophakic ,were referred for retinal detachment surgery at the Donostia University Hospital (Terciary Hospital, Spain). Results: The mean age of patients was 63.06 ± 10.8 at the time of phacoemulsification and 49.09% of them had moderate myopia ( axial length (AL) (23.5 26.5 mm). In our serie, macular detachment was evident in 69.09% of patients. The mean time that elapsed between phacoemulsification and RD surgery was 4.04 ± 4.17 years, being reduced by half in the event of surgical complications (2.24 ± 2.65). The rate of recurrence of RD was 28.79%. The anatomical results in terms of retinal reapplication have been better by combining vitrectomy with scleral buckle (83.1% vs 70.5%). The variables associated with a higher risk of recurrence were male gender (Hazard ratio -HR= 1.75), macular detachment (HR= 2.00) and the presence of proliferative vitreoretinopathy (PVR) (HR= 3.21) Conclusions :PRD usually occurs within 4 years of phacoemulsification, although it may occur significantly earlier in the event of surgical complications. The involvement of the macula, PVR, and male gender are all associated with a higher risk of PRD recurrence.