Parton Labeling without Matching: Unveiling Emergent Labelling Capabilities in Regression Models

Parton labeling methods are widely used when reconstructing collider events with top quarks or other massive particles. State-of-the-art techniques are based on machine learning and require training data with events that have been matched using simulations with truth information. In nature, there is no unique matching between partons and final state objects due to the properties of the strong force and due to acceptance effects. We propose a new approach to parton labeling that circumvents these challenges by recycling regression models. The final state objects that are most relevant for a regression model to predict the properties of a particular top quark are assigned to said parent particle without having any parton-matched training data. This approach is demonstrated using simulated events with top quarks and outperforms the widely-used $\chi^2$ method.Comment: 6 pages, 4 figure

Fast and Accurate Recognition of Chinese Clinical Named Entities with Residual Dilated Convolutions

Clinical Named Entity Recognition (CNER) aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task for clinical and translation research. In recent years, deep learning methods have achieved significant success in CNER tasks. However, these methods depend greatly on Recurrent Neural Networks (RNNs), which maintain a vector of hidden activations that are propagated through time, thus causing too much time to train models. In this paper, we propose a Residual Dilated Convolutional Neural Network with Conditional Random Field (RD-CNN-CRF) to solve it. Specifically, Chinese characters and dictionary features are first projected into dense vector representations, then they are fed into the residual dilated convolutional neural network to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags. Computational results on the CCKS-2017 Task 2 benchmark dataset show that our proposed RD-CNN-CRF method competes favorably with state-of-the-art RNN-based methods both in terms of computational performance and training time.Comment: 8 pages, 3 figures. Accepted as regular paper by 2018 IEEE International Conference on Bioinformatics and Biomedicine. arXiv admin note: text overlap with arXiv:1804.0501

Exploring Regulation Genes Involved in the Expression of L-Amino Acid Oxidase in Pseudoalteromonas sp. Rf-1

Bacterial L-amino acid oxidase (LAAO) is believed to play important biological and ecological roles in marine niches, thus attracting increasing attention to understand the regulation mechanisms underlying its production. In this study, we investigated genes involved in LAAO production in marine bacterium Pseudoalteromonas sp. Rf-1 using transposon mutagenesis. Of more than 4,000 mutants screened, 15 mutants showed significant changes in LAAO activity. Desired transposon insertion was confirmed in 12 mutants, in which disrupted genes and corresponding functionswere identified. Analysis of LAAO activity and lao gene expression revealed that GntR family transcriptional regulator, methylase, non-ribosomal peptide synthetase, TonB-dependent heme-receptor family, Na⁺/H⁺ antiporter and related arsenite permease, N-acetyltransferase GCN5, Ketol-acid reductoisomerase and SAM-dependent methytransferase, and their coding genes may be involved in either upregulation or downregulation pathway at transcriptional, posttranscriptional, translational and/or posttranslational level. The nhaD and sdmT genes were separately complemented into the corresponding mutants with abolished LAAO-activity. The complementation of either gene can restore LAAO activity and lao gene expression, demonstrating their regulatory role in LAAO biosynthesis. This study provides, for the first time, insights into the molecular mechanisms regulating LAAO production in Pseudoalteromonas sp. Rf-1, which is important to better understand biological and ecological roles of LAAO

Isolation and characterization of multidrug-resistant side population cells in prostate carcinoma

Purpose: To isolate and characterize cancer stem-like side population (SP) cells from prostate cancer tissues using Hoechst 33342 dye exclusion.Methods: The presence of SP cells was analyzed in tumor samples by fluorescence activated cell sorting. The cell survival rate and ability for cell self-renewal using the sphere formation assay were evaluated after treatment with multiple drugs.Results: SP cells in the prostate cancer samples constituted 2.8 %, but fell to 0.6 % after treatment with verapamil. The SP cells showed high resistance to drugs such as 5-fluorouracil, cisplatin, paclitaxel (2 μmol/L) and oxaliplatin. The survival rate of SP cells after treatment with these drugs was significantly higher (p < 0.01) than that of non-SP cells. Furthermore, the number of spheres generated in serumfree medium was significantly higher in prostate cancer SP cells than in non-SP cells.Conclusion: The presence of SP cells is responsible for prostate treatment failure and tumor recurrence. Therefore, isolation and characterization of SP cells may provide new insights into the development of novel therapeutic agents targeting cancer stem cells for complete eradication of the tumor.Keywords: Side population cells, ABC transporters, Cancer stem cells, Chemotherapy, Prostate treatment failure, Tumor recurrence, Drug resistanc

A Multigrid Multilevel Monte Carlo Method for Stokes–Darcy Model with Random Hydraulic Conductivity and Beavers–Joseph Condition

A multigrid multilevel Monte Carlo (MGMLMC) method is developed for the stochastic Stokes–Darcy interface model with random hydraulic conductivity both in the porous media domain and on the interface. Three interface conditions with randomness are considered on the interface between Stokes and Darcy equations, especially the Beavers–Joesph interface condition with random hydraulic conductivity. Because the randomness through the interface affects the flow in the Stokes domain, we investigate the coupled stochastic Stokes–Darcy model to improve the fidelity. Under suitable assumptions on the random coefficient, we prove the existence and uniqueness of the weak solution of the variational form. To construct the numerical method, we first adopt the Monte Carlo (MC) method and finite element method, for the discretization in the probability space and physical space, respectively. In order to improve the efficiency of the classical single-level Monte Carlo (SLMC) method, we adopt the multilevel Monte Carlo (MLMC) method to dramatically reduce the computational cost in the probability space. A strategy is developed to calculate the number of samples needed in MLMC method for the stochastic Stokes–Darcy model. In order to accomplish the strategy for MLMC method, we also present a practical method to determine the variance convergence rate for the stochastic Stokes–Darcy model with Beavers–Joseph interface condition. Furthermore, MLMC method naturally provides the hierarchical grids and sufficient information on these grids for multigrid (MG) method, which can in turn improve the efficiency of MLMC method. In order to fully make use of the dynamical interaction between these two methods, we propose a multigrid multilevel Monte Carlo (MGMLMC) method with finite element discretization for more efficiently solving the stochastic model, while additional attention is paid to the interface and the random Beavers–Joesph interface condition. The computational cost of the proposed MGMLMC method is rigorously analyzed and compared with the SLMC method. Numerical examples are provided to verify and illustrate the proposed method and the theoretical conclusions

catena-Poly[4,4′-bipyridinium [[diaqua­disulfatocadmium(II)]-μ-4,4′-bipyridine-κ2 N:N′] dihydrate]

The title compound, {(C10H10N2)[Cd(SO4)2(C10H8N2)(H2O)2]·2H2O}n, consists of anionic chains of the Cd complex, diprotonated 4,4′-bipyridinium cations and uncoordinated water mol­ecules. In the anionic chain, the Cd atom lies on a center of inversion in an octa­hedral geometry. The midpoint of the coordinated bipyridine also resides on a center of inversion, as does the non-coordinated bipyridinium counterion. O—H⋯O and N—H⋯O hydrogen bonding inter­actions and π–π stacking inter­actions in the structure are responsible for the supra­molecular assembly

Fluorescence Characteristics of Triazine-manufacturing Wastewater

Samples taken at different points in the wastewater treatment process of a triazine-manufacturing plant were scanned by fluorescence spectroscopy, in the wavelength range of 200-900 nm. Reproducibly, the fluorescence spectra revealed one single major peak at excitation and emission wavelengths of 258 and 370 nm respectively. Aqueous solutions of purified active compounds, including Atrazine, Propazine, Simazine, Terbuthylazine, Metolachlor, and Benoxacor, were also scanned. No significant fluorescence was observed in these standard solutions at concentrations up to 100 mg/L. Selected plant samples as well as standard solutions of Atrazine, Metolachlor, and toluene were further analyzed using high-performance liquid chromatography with absorbance and fluorescence detections. Pure Atrazine was found to be light-absorbing but nonfluorescent while Metolachlor, with a benzene ring in its structure, was weakly fluorescent. The plant wastewater samples exhibited a single strong fluorescence peak, which also appeared as the dominant peak in the fluorescence chromatogram of Atrazine standard (due to impurity). The findings strongly suggested that the responsible fluorescent compound in the plant\u27s wastewater was a byproduct of the synthesis processes. The fluorescent compound was found to be effectively removed by the carbon adsorption treatment (CAT) unit employed in the plant but not by the biological activated-sludge treatment process alone. The results indicated the feasibility of using online fluorescence measurements to effectively monitor the performance of the CAT unit