bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reducing Excavation Damage in the Natural Gas Industry Using Real-Time GIS and Sensors
Authors: Rezendez Aaron , Marros Robert J. , Farrag Khalid , Acharya Saurav 
Published: November 2018

Excavation damage is one of the top causes of incidents in both the transmission and distribution pipeline sectors. Damage caused from insufficient notification of one-call centers or careless digging near gas pipelines can potentially result in property damage, significant injury, and/or loss of life. Pacific Gas and Electric Company (PG&E) and the Gas Technology Institute (GTI) have developed the framework for an Excavation Encroachment Notification (EEN) system to support damage prevention efforts to reduce damage from excavation activity. The research was funded by the California Energy Commission (CEC) and Operations Technology Development (OTD).
The system utilizes real-time Geographic Information System (GIS) technology and cellular-connected location and motion sensors placed on excavation equipment. Controlled and field-based testing and training of machine learning algorithms were conducted to aid in characterization of excavation equipment. Additionally, a GIS system populated with pipeline information allowed operators of excavation equipment and utilities to receive an alarm and indication when equipment is adjacent to or excavating in the vicinity of a gas pipeline. More broadly, the utility stakeholder has increased situational awareness of excavation activities within its service territory with access to the real-time activity of excavation equipment through a mobile-compatible dashboard, reducing excavation damage risk and improving safety. Lastly, the project offers historical data archiving for data analysis and trend identification.
Application of Machine Learning to Distributed Temperature Sensing (DTS) Systems
Authors: Araujo Maria S. , Spidle Heath A. , Siebenaler Shane P. , Blaisdell Samantha G. , Vickers David W. 
Published: November 2018

The timely detection of small leaks from liquid pipelines poses a significant challenge for pipeline operations. One technology considered for continual monitoring is distributed temperature sensing (DTS), which utilizes a fiber-optic cable to provide distributed temperature measurements along a pipeline segment. This measurement technique allows for a high accuracy of temperature determination over long distances. Unexpected deviations in temperature at any given location can indicate various physical changes in the environment, including contact with a heated hydrocarbon due to a pipeline leak.
The signals stemming from pipeline leaks may not be significantly greater than the noise in the DTS measurements, so care must be taken to configure the system in a manner that can detect small leaks while rejecting non-leak temperature anomalies. There are many factors that influence the frequency and intensity of the backscattered optical signal. This can result in noise in the fine-grained temperature sensing data. Thus, the DTS system must be tuned to the nominal temperature profile along the pipe segment. This customization allows for significant sensitivity and can utilize different leak detection thresholds at various locations based on normal temperature patterns. However, this segment-specific tuning can require a significant amount of resources and time. Additionally, this configuration exercise may have to be repeated as pipeline operating conditions change over time. Thus, there is a significant need and interest in advancing existing DTS processing techniques to enable the detection of leaks that today go undetected by DTS due to their signal response being too close to the noise floor and/or requiring significant resources to achieve positive results.
This paper discusses the recent work focused on using machine learning (ML) techniques to detect leak signatures. Initial proof-of-concept results provide a more robust methodology for detecting leaks and allow for the detection of smaller leaks than are currently detectable by typical DTS systems, with low false alarm rates. A key use of ML approaches is that the system can “learn” about a given pipeline on its own without the need to utilize resources for pipeline segment-specific tuning. The potential to have a self-taught system is a powerful concept, and this paper discusses some key initial findings from applying ML-based techniques to optimize leak detection capabilities of an existing DTS system.
Evaluation of Crack Growth and Material Toughness Effects on Probability of Pipeline Failure
Authors: Riccardella Pete , Dedhia Dilip , Riccardella Scott , Manning Tyson 
Published: November 2018

Probabilistic fracture mechanics (PFM) analysis can provide insights into the relative benefits of various pipeline integrity management options in reducing the probability of a pipeline failure. For example, a prior analysis (1) showed that In-Line Inspection (ILI) technology can achieve a greater level of safety, at longer reassessment intervals, than other integrity management techniques such as Hydrostatic Pressure Testing in a line subject to an aggressive Stress Corrosion Cracking (SCC) environment in relatively high toughness pipe base material.
This paper extends that study to evaluate the effects of different crack growth mechanisms, such as fatigue crack growth (FCG) in gas and liquid pipelines as well as materials with differing fracture toughness levels (i.e. Seam Welds vs. Base Metal). PFM analysis can address these growth mechanisms and toughness distributions and serve as a valuable tool for weighing the effects of different assessment techniques, repair criteria and reassessment intervals on pipeline integrity. The analysis can also be used to study the effects of probability of detection (POD) of the ILI techniques as well as enhanced repair (dig) criteria. This paper presents a series of case studies to illustrate the utility of the PFM approach for comparing integrity management options for pipelines subject to different crack growth mechanisms and fracture toughness properties.
Improving Fitness-for-Purpose Methodology and Safety Target Definitions on Geohazard Related Pipe Deformation
Authors: Yoosef-Ghodsi Nader , Baraniecki Kurt , Hill Mike , Hubert Yvan 
Published: November 2018

Previous practices at Enbridge Pipelines Inc. regarding allowable deformation and/or strain in pipelines were closely mirrored to current North American standards and did not effectively manage the time dependent aspect of active slope movement and other similar progressive external force phenomena applied to a pipeline. In addition, variability in soil spring values and/or soil displacements utilized in FEA assessments can lead to significant variability between predicted pipeline strain demand and actual conditions. Furthermore, the risk tolerance of a potential and significant deformation that could impact the serviceability of one pipeline in a Right of Way (ROW) including multiple pipelines was not well defined. Shutting down several pipelines in a ROW until it could be proven that they are fit-for-service is time consuming. In addition, it requires a good amount of engineering work to address the significant uncertainty in confirming if a pipeline has not deformed beyond a safe limit when the latest deformation in-line inspection predates significant soil movement.
A better tool was required to allow a more precise assessment. A better fitness-for-purpose approach has been developed and used to both predict when a timely repair would be required and conservatively set the In-line Inspection (ILI) re-inspection interval to monitor the condition of the pipe. This approach allowed to step away from the greater uncertainty associated with understanding the impact of soil movement on the pipe integrity. This paper presents the methodology used by Enbridge to redefine its fitness-for-purpose methodology using proven strain-deformation correlation models and strain rates estimated through multiple arrays of strain gauges. The discussion will include how the safety targets were re-engineered to account for multiple pipelines in a ROW.
Tracking Batches Accurately in a Multi-Product Pipeline With Large Elevation Changes and Prominent Slack Flow
Authors: Milano Giancarlo , Goyal Nitesh , Basnett David 
Published: November 2018

When transporting multiple products in a pipeline, it is important to always understand the location of the head and tail of each batch. The operator will know where batch interfaces are in real-time and be ready to swing the valve at the exact time a batch arrives at a station to deliver product to the right storage tank or an end-customer with minimal contamination. It is relatively easy to track multiple batches in a pipeline with no elevation changes, and a fixed internal diameter. However, it is far more complex to track multiple batches in a pipeline with drastic elevation changes and different sizes in diameter. Column separation of the liquid, also known as slack, occurs when the pipeline pressure drops below the vapor pressure calculated at the liquid temperature in a specific area of the pipeline. This effect reduces the amount of liquid volume contained within the pipeline region, changing the actual physical position of the batch head and tail interfaces, and reducing the accuracy of the volume within the region and the corresponding Estimated Times of Arrival at stations. Draining or filling a pipeline section by delivering product at a different rate from what injected causes the same effect.
A scientific approach to calculate the areas of slack and volume contained within a pipeline should provide sufficient information to track batches with a high degree of accuracy. However, it is neither simple nor straightforward to simulate this phenomenon offline, and it is much more challenging in an online, real-time environment. Online, additional complexities affect how batches and their interfaces are tracked, causing a big discrepancy between Estimated and Actual Time of Arrivals. This paper discusses an empirical approach developed to calculate the volume contained within a pipeline region by tracking the volume entering and leaving the region.
Estimated and Actual Times of Arrival are within a 15-minute time window after a batch has traveled a total distance of 1,200km with drastic elevation changes along the route. This method has proven that batch tracking can be highly accurate and reliable with less of the theoretical assumptions used in a hydraulic simulation package, with no need to model every single characteristic of the pipeline in detail. This removed the uncertainties that attend those assumptions and allowed this system to perform well on a pipeline with severe slack flow and draining/filling operations.
Development of Large Diameter Heavy Wall Seamless Tee Fitting of WPHY-80 Grade for Low Temperature Pipeline Station Application
Authors: Liu Yu , Han Tao , Li Yezheng , Yin Zhanghua , Zhu Peng , Yan Lijun , Li Qiang 
Published: November 2018

This paper describes the development of large diameter heavy wall seamless tee fitting of WPHY-80 grade for low temperature pipeline station application. Steel tees with thicker wall generally tend to have low fracture toughness either in pipe body or in weld joint and low weldability. Therefore, improvement of fracture toughness and weldability are particularly important with respect to development of higher strength and thicker wall seamless tee fittings.
For the requirement of the China-Russia Eastern Gas Pipeline Project, WPHY-80 large diameter, seamless heavy wall reducing outlet tees were developed, with DN1400 × DN1200 and 57mm wall thickness. The billet steel production process was electroslag remelting (ESR), and the tee fitting production process used a forging and hot extrusion combination. Finally, quenching and tempering were carried out.
In this paper, the mechanical properties and microstructure of WPHY-80 seamless tee were studied. The results of mechanical testing showed that the tensile yield strength of the tee body was more than 590 MPa and also provided excellent low temperature toughness (CVN > 200 J at −45°C), which met the requirements of the specification for fittings applied in the China-Russia Eastern Gas Pipeline Project. In addition, the results of welding procedure qualification showed that the welding performance of the WPHY-80 seamless tee was excellent.
Tensile and Compressive Strain Capacity in the Presence of Corrosion Anomalies
Authors: Zhou Honggang , Wang Yong-Yi , Stephens Mark , Bergman Jason , Nanney Steve 
Published: November 2018

Over the past 15 years, extensive studies have been conducted on the tensile strain capacity (TSC) and compressive strain capacity (CSC) of pipelines. The existing studies were mainly targeted at the design and construction of new pipelines. However, the impact of anomalies (e.g., corrosion anomalies) on the TSC and CSC has not been explicitly and adequately considered.
This paper summarizes work performed as part of a major effort funded by the US Department of Transportation Pipeline and Hazardous Materials Safety Administration (DOT PHMSA) aimed at examining the impact of corrosion anomalies on the TSC and CSC of pipelines. In this work, the strain capacities were examined analytically, and the analytical work was compared to results from selected full-scale tests.
Based on the summarized work, guidelines were developed for assessing the TSC and the CSC of corroded pipes. The guidelines are applicable to different types of corrosion anomalies, including circumferential grooves, longitudinal grooves and general corrosion. The strain capacities can be calculated using the key material properties and dimensions of pipe and corrosion anomalies as inputs.
Development and prospective external validation of a tool to predict poor recovery at 9 months after acute ankle sprain in UK emergency departments: the SPRAINED prognostic model
Authors: Schlussel Michael M , Keene David J , Collins Gary S , Bostock Jennifer , Byrne Christopher , Goodacre Steve , Gwilym Stephen , Hagan Daryl A , Haywood Kirstie , Thompson Jacqueline , Williams Mark A , Lamb Sarah E 
Published: November 2018

ObjectivesTo develop and externally validate a prognostic model for poor recovery after ankle sprain.Setting and participantsModel development used secondary data analysis of 584 participants from a UK multicentre randomised clinical trial. External validation used data from 682 participants recruited in 10 UK emergency departments for a prospective observational cohort.Outcome and analysisPoor recovery was defined as presence of pain, functional difficulty or lack of confidence in the ankle at 9 months after injury. Twenty-three baseline candidate predictors were included together in a multivariable logistic regression model to identify the best predictors of poor recovery. Relationships between continuous variables and the outcome were modelled using fractional polynomials. Regression parameters were combined over 50 imputed data sets using Rubin’s rule. To minimise overfitting, regression coefficients were multiplied by a heuristic shrinkage factor and the intercept re-estimated. Incremental value of candidate predictors assessed at 4 weeks after injury was explored using decision curve analysis and the baseline model updated. The final models included predictors selected based on the Akaike information criterion (p<0.157). Model performance was assessed by calibration and discrimination.ResultsOutcome rate was lower in the development (6.7%) than in the external validation data set (19.9%). Mean age (29.9 and 33.6 years), body mass index (BMI; 26.3 and 27.1 kg/m2), pain when resting (37.8 and 38.5 points) or bearing weight on the ankle (75.4 and 71.3 points) were similar in both data sets. Age, BMI, pain when resting, pain bearing weight, ability to bear weight, days from injury until assessment and injury recurrence were the selected predictors. The baseline model had fair discriminatory ability (C-statistic 0.72; 95% CI 0.66 to 0.79) but poor calibration. The updated model presented better discrimination (C-statistic 0.78; 95% CI 0.72 to 0.84), but equivalent calibration.ConclusionsThe models include predictors easy to assess clinically and show benefit when compared with not using any model.Trial registration numberISRCTN12726986; Results.
M2 Macrophage-Derived Exosomes Promote Cell Migration and Invasion in Colon Cancer
Authors: Lan Jingqin , Sun Li , Xu Feng , Liu Lu , Hu Fuqing , Song Da , Hou Zhenlin , Wu Wei , Luo Xuelai , Wang Jing , Yuan Xianglin , Hu Junbo , Wang Guihua 
Published: November 2018

Abstract

Clinical and experimental evidence has shown that tumor-associated macrophages promote cancer initiation and progression. However, the macrophage-derived molecular determinants that regulate colorectal cancer metastasis have not been fully characterized. Here, we demonstrate that M2 macrophage–regulated colorectal cancer cells' migration and invasion is dependent upon M2 macrophage–derived exosomes (MDE). MDE displayed a high expression level of miR-21-5p and miR-155-5p, and MDE-mediated colorectal cancer cells' migration and invasion depended on these two miRNAs. Mechanistically, miR-21-5p and miR-155-5p were transferred to colorectal cancer cells by MDE and bound to the BRG1 coding sequence, downregulating expression of BRG1, which has been identified as a key factor promoting the colorectal cancer metastasis, yet is downregulated in metastatic colorectal cancer cells. Collectively, these findings show that M2 macrophages induce colorectal cancer cells' migration and invasion and provide significant plasticity of BRG1 expression in response to tumor microenvironments during malignant progression. This dynamic and reciprocal cross-talk between colorectal cancer cells and M2 macrophages provides a new opportunity for the treatment of metastatic colorectal cancer.

Significance:
These findings report a functional role for miRNA-containing exosomes derived from M2 macrophages in regulating migration and invasion of colorectal cancer cells.
Circulating Tumor Cells with Stemness and Epithelial-to-Mesenchymal Transition Features Are Chemoresistant and Predictive of Poor Outcome in Metastatic Breast Cancer
Authors: Papadaki Maria A. , Stoupis Giannis , Theodoropoulos Panayiotis A. , Mavroudis Dimitris , Georgoulias Vassilis , Agelaki Sofia 
Published: November 2018

Abstract
Circulating tumor cells (CTCs) bearing phenotypes related to cancer stem cells (CSCs) and epithelial-to-mesenchymal transition (EMT) have been identified in breast cancer; however, their clinical significance is not clear. In the current study, we investigated the prognostic relevance of single CSC+/partial-EMT+ CTCs in patients with metastatic breast cancer and the effect of first-line chemotherapy on their incidence. For this purpose, triple immunofluorescence against cytokeratin, ALDH1, and TWIST1 was performed in peripheral blood mononuclear cell (PBMC) cytospins from 130 patients before and after first-line chemotherapy. CSC+/partial-EMT+ CTCs were characterized as cells co-expressing cytokeratin, high levels of ALDH1, and nuclear TWIST1. CSC+/partial-EMT+ CTCs were evident in 27.7% of patients at baseline and were correlated to lung metastases (P = 0.010) and decreased progression-free survival [PFS; median 10.2 (8.9–11.6) vs. 13.5 (11.3–15.7) months; P = 0.024]. Their detection was an independent factor predicting for increased risk of relapse [multivariate analysis; HR (95% confidence interval (CI)): 1.785 (1.171–2.720); P = 0.007]. In HER-2–negative patients, CSC+/partial-EMT+ CTCs were additionally associated with reduced overall survival (OS) [median 39 (26.2–51.9) vs. 51 (15.7–86.4) months; P = 0.020] and increased risk of death [multivariate analysis; HR (95% CI): 2.228 (1.066–4.655); P = 0.033]. Chemotherapy resulted in a significant increase in the incidence of CSC+/partial-EMT+ CTCs (mean CTC% per patient: 59.4% post vs. 39.5% pre; P = 0.018), which was subsequently confirmed only in HER2-negative patients (P = 0.040) and in non-responders at the end of treatment (P = 0.020). In conclusion, CSC+/partial-EMT+ CTCs represent a chemoresistant subpopulation, which independently predicts for unfavorable outcome in metastatic breast cancer. Efficient targeting of these CTCs could potentially increase patient survival.
PARP1 Suppresses the Transcription of PD-L1 by Poly(ADP-Ribosyl)ating STAT3
Authors: Ding Ling , Chen Xi , Xu Xiaqing , Qian Yuli , Liang Guikai , Yao Fengqi , Yao Zhangting , Wu Honghai , Zhang Jieqiong , He Qiaojun , Yang Bo 
Published: November 2018

Abstract
Studies have pointed to a role of PARP1 in regulating gene expression through poly(ADP-ribosyl)ating, sequence-specific, DNA-binding transcription factors. However, few examples exist that link this role of PARP1 to the immunogenicity of cancer cells. Here, we report that PARP1 poly(ADP-ribosyl)ates STAT3 and subsequently promotes STAT3 dephosphorylation, resulting in reduced transcriptional activity of STAT3 and expression of PD-L1. In this study, we showed that PARP1 silencing or pharmacologic inhibition enhanced the transcription of PD-L1 in cancer cells, which was accompanied by the upregulation of PD-L1 protein expression, both in the cytoplasm and on the cell surface. This induction of PD-L1 was attenuated in the absence of the transcription factor STAT3. Cell-based studies indicated that PARP1 interacted directly with STAT3 and caused STAT3 poly(ADP-ribosyl)ation. STAT3′s activation of PD-L1 transcription was abolished by the overexpression of wild-type PARP1 but not mutant PARP1, which lacks catalytic activity. PARP1 downregulation or catalytic inhibition enhanced the phosphorylation of STAT3, which was reversed by the ectopic expression of wild-type PARP1 but not by mutated PARP1. An inverse correlation between PARP1 and PD-L1 was also observed in clinical ovarian cancer samples. Overall, our study revealed PARP1-mediated poly(ADP-ribosyl)ation of STAT3 as a key step in inhibiting the transcription of PD-L1, and this mechanism exists in a variety of cancer cells.
Calnexin Impairs the Antitumor Immunity of CD4+ and CD8+ T Cells
Authors: Chen Yichen , Ma Da , Wang Xi , Fang Juan , Liu Xiangqi , Song Jingjing , Li Xinye , Ren Xianyue , Li Qiusheng , Li Qunxing , Wen Shuqiong , Luo Liqun , Xia Juan , Cui Jun , Zeng Gucheng , Chen Lieping , Cheng Bin , Wang Zhi 
Published: November 2018

AbstractElucidation of the mechanisms of T-cell–mediated antitumor responses will provide information for the rational design and development of cancer immunotherapies. Here, we found that calnexin, an endoplasmic reticulum (ER) chaperone protein, is significantly upregulated in oral squamous cell carcinoma (OSCC). Upregulation of its membranous expression on OSCC cells is associated with inhibited T-cell infiltration in tumor tissues and correlates with poor survival of patients with OSCC. We found that calnexin inhibits the proliferation of CD4+ and CD8+ T cells isolated from the whole blood of healthy donors and patients with OSCC and inhibits the secretion of IFNγ, TNFα, and IL2 from these cells. Furthermore, in a melanoma model, knockdown of calnexin enhanced the infiltration and effector functions of T cells in the tumor microenvironment and conferred better control of tumor growth, whereas treatment with a recombinant calnexin protein impaired the infiltration and effector functions of T cells and promoted tumor growth. We also found that calnexin enhanced the expression of PD-1 on CD4+ and CD8+ T cells by restraining the DNA methylation status of a CpG island in the PD-1 promoter. Thus, this work uncovers a mechanism by which T-cell antitumor responses are regulated by calnexin in tumor cells and suggests that calnexin might serve as a potential target for the improvement of antitumor immunotherapy.