Modelling Ice and Wax Formation in a Pipeline in the Arctic Environment

PresentationIn the Arctic environment, fluid temperature in pipeline can drop below the freezing point of water, which causes wax and ice to form on pipeline surface. Solid formation on pipeline surface can lead to flow assurance and process safety issues, such as blockage of pipeline, pipeline component failure, and the release of hazardous liquid. The blockage of pipeline can cause additional burden or failure to pumping system. Remediating the plugging requires shutdown of pipeline operation, which cause tremendous cost and delay to the entire production system. Ice and wax deposition in pipeline is a slow process. Pigging operation can be used to remove the deposits on pipeline surface. However, if deposition is too thick, pipeline blockage can still occur. In order to prevent pipeline blockage, ice and wax deposition rates are required to be estimated. This paper investigates ice and wax deposition rates in a 90 km pipeline. A fundamental model for both ice and wax deposition is proposed using first principles of heat and mass transfer. The interaction between water and wax is analysed

Neural Ranking Models with Weak Supervision

Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from queries and documents when no supervised signal is available. Hence, in this paper, we propose to train a neural ranking model using weak supervision, where labels are obtained automatically without human annotators or any external resources (e.g., click data). To this aim, we use the output of an unsupervised ranking model, such as BM25, as a weak supervision signal. We further train a set of simple yet effective ranking models based on feed-forward neural networks. We study their effectiveness under various learning scenarios (point-wise and pair-wise models) and using different input representations (i.e., from encoding query-document pairs into dense/sparse vectors to using word embedding representation). We train our networks using tens of millions of training instances and evaluate it on two standard collections: a homogeneous news collection(Robust) and a heterogeneous large-scale web collection (ClueWeb). Our experiments indicate that employing proper objective functions and letting the networks to learn the input representation based on weakly supervised data leads to impressive performance, with over 13% and 35% MAP improvements over the BM25 model on the Robust and the ClueWeb collections. Our findings also suggest that supervised neural ranking models can greatly benefit from pre-training on large amounts of weakly labeled data that can be easily obtained from unsupervised IR models.Comment: In proceedings of The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR2017

The Synthesis of Amphiphilic Luminescent Graphene Quantum Dot and Its Application in Miniemulsion Polymerization

Although emulsion applications of microscale graphene sheets have attracted much attention recently, nanoscale graphene platelets, namely, graphene quantum dots (GQDs), have been rarely explored in interface science. In this work, we study the interfacial behaviors and emulsion phase diagrams of hydrophobic-functionalized graphene quantum dots (C18-GQDs). Distinctive from pristine graphene quantum dots (p-GQDs), C18-GQDs show several interesting surface-active properties including high emulsification efficiency in stabilizing dodecane-in-water emulsions. We then utilize the C18-GQDs as surfactants in miniemulsion polymerization of styrene, achieving uniform and relatively small polystyrene nanospheres. The high emulsification efficiency, low production cost, uniform morphology, intriguing photoluminescence, and extraordinary stability render C18-GQDs an attractive alternative in surfactant applications

Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents

In vehicle–pedestrian accidents, the preimpact conditions of pedestrians and vehicles are frequently uncertain. The incident data for a crash, such as vehicle deformation, injury of the victim, distance of initial position and rest position of accident participants, are useful for verification in MAthematical DYnamic MOdels (MADYMO) simulations. The purpose of this study is to explore the use of an improved optimization algorithm combined with MADYMO multibody simulations and crash data to conduct accurate reconstructions of vehicle–pedestrian accidents. The objective function of the optimization problem was defined as the Euclidean distance between the known vehicle, human and ground contact points, and multiobjective optimization algorithms were employed to obtain the local minima of the objective function. Three common multiobjective optimization algorithms—nondominated sorting genetic algorithm-II (NSGA-II), neighbourhood cultivation genetic algorithm (NCGA), and multiobjective particle swarm optimization (MOPSO)—were compared. The effect of the number of objective functions, the choice of different objective functions and the optimal number of iterations were also considered. The final reconstructed results were compared with the process of a real accident. Based on the results of the reconstruction of a real-world accident, the present study indicated that NSGA-II had better convergence and generated more noninferior solutions and better final solutions than NCGA and MOPSO. In addition, when all vehicle-pedestrian-ground contacts were considered, the results showed a better match in terms of kinematic response. NSGA-II converged within 100 generations. This study indicated that multibody simulations coupled with optimization algorithms can be used to accurately reconstruct vehicle-pedestrian collisions

First-line treatment with chemotherapy plus cetuximab in Chinese patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck: Efficacy and safety results of the randomised, phase III CHANGE-2 trial.

Abstract Background The EXTREME regimen (chemotherapy [CT; cisplatin/carboplatin and 5-fluorouracil]) plus cetuximab is a standard-of-care first-line (1L) treatment for patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck (R/M SCCHN), as supported by international guidelines. The phase III CHANGE-2 trial assessed the efficacy and safety of a modified CT regimen (with a reduced dose of both components) and cetuximab versus CT for the 1L treatment of Chinese patients with R/M SCCHN. Methods Patients were randomised to receive up to six cycles of CT plus cetuximab followed by cetuximab maintenance until progressive disease or CT alone. The primary end-point was the progression-free survival (PFS) time assessed by the independent review committee (IRC). Results Overall, 243 patients were randomised (164 to CT plus cetuximab; 79 to CT). The hazard ratios for PFS by IRC and overall survival (OS) were 0.57 (95% CI: 0.40–0.80; median: 5.5 versus 4.2 months) and 0.69 (95% CI: 0.50–0.93; median: 11.1 versus 8.9 months), respectively, in favour of CT plus cetuximab. The objective response rates (ORR) by IRC were 50.0% and 26.6% with CT plus cetuximab and CT treatment, respectively. Treatment-emergent adverse events of maximum grade 3 or 4 occurred in 61.3% (CT plus cetuximab) and 48.7% (CT) of patients. Conclusions CHANGE-2 showed an improved median PFS, median OS and ORR with the addition of cetuximab to a modified platinum/5-fluorouracil regimen, with no new or unexpected safety findings, thereby confirming CT plus cetuximab as an effective and safe 1L treatment for Chinese patients with R/M SCCHN. Clinical trial registration number NCT02383966

Associations of IL-4, IL-4R, and IL-13 Gene Polymorphisms in Coal Workers' Pneumoconiosis in China: A Case-Control Study

Background: The IL-4, IL-4 receptor (IL4R), and IL-13 genes are crucial immune factors and may influence the course of various diseases. In the present study, we investigated the association between the potential functional polymorphisms in IL-4, IL-4R, and IL-13 and coal workers ’ pneumoconiosis (CWP) risk in a Chinese population. Methods: Six polymorphisms (C-590T in IL-4, Ile50Val, Ser478Pro, and Gln551Arg in IL-4R, C-1055T and Arg130Gln in IL-13) were genotyped and analyzed in a case-control study of 556 CWP and 541 control subjects. Results: Our results revealed that the IL-4 CT/CC genotypes were associated with a significantly decreased risk of CWP (odd

Somatic loss of ATM is a late event in pancreatic tumorigenesis

Understanding the timing and spectrum of genetic alterations that contribute to the development of pancreatic cancer is essential for effective interventions and treatments. The aim of this study was to characterize somatic ATM alterations in noninvasive pancreatic precursor lesions and invasive pancreatic adenocarcinomas from patients with and without pathogenic germline ATM variants. DNA was isolated and sequenced from the invasive pancreatic ductal adenocarcinomas and precursor lesions of patients with a pathogenic germline ATM variant. Tumor and precursor lesions from these patients as well as colloid carcinoma from patients without a germline ATM variant were immunolabeled to assess ATM expression. Among patients with a pathogenic germline ATM variant, somatic ATM alterations, either mutations and/or loss of protein expression, were identified in 75.0% of invasive pancreatic adenocarcinomas but only 7.1% of pancreatic precursor lesions. Loss of ATM expression was also detected in 31.0% of colloid carcinomas from patients unselected for germline ATM status, significantly higher than in pancreatic precursor lesions [pancreatic intraepithelial neoplasms (p = 0.0013); intraductal papillary mucinous neoplasms, p = 0.0040] and pancreatic ductal adenocarcinoma (p = 0.0076) unselected for germline ATM status. These data are consistent with the second hit to ATM being a late event in pancreatic tumorigenesis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A hierarchical process for optimizing bus stop distribution

Transit stop spacing is an important indicator in deploying public transit services. This paper presents a hierarchical process for optimizing distribution of bus stops in the context of multi-modal transit development in large cities. Firstly, connection stops are generated manually to connect with other transit facilities. Secondly, key stops are identified based on a coverage model that minimizing total distance, using node centrality value as weight. Thirdly, ordinary bus stops are optimized with coverage model that maximizing potential transit demand. The analytical process is based on a combination of raster and vector data models in Geographical information system, which allows for flexible computing and effective evaluation