Hadronic physics from extensive air showers

Although cosmic rays were discovered exactly one century ago, the most fundamental questions about them are still not answered, especially the origin and composition of ultra-high energy cosmic rays (UHECR). The Pierre Auger Observatory (PAO) is constructed with the goal of solving these mysteries. The PAO uses hybrid design and take advantage of both the air fluorescence and surface array technique. Since its debut in 2004, PAO has published several important scientific results. The most probable candidate for UHECR composition is proton or iron nucleus. The two candidates do show differences in both fluorescence detector (FD) signal and in the surface detector (SD) signal. PAO has utilized the statistical depth of shower maximum information of FD signal to study the composition and suggests that the nuclear mass is getting heavier from 1 EeV to 10 EeV and beyond. The result does not come without argument. The Telescope Array (TA)\u27s result consists with a pure proton primary. One other possible solution to check these results is to study the SD signal since SD has a lot more statistics. According to Matthews\u27 Heitler model, the proton and iron primary air showers show significant differences in the muon production, thus muon number is very sensitive to the cosmic ray primary composition. Leading particle physics - where one of the many particles emerging from a collision carries a significant portion of the energy - is a well-known and studied concept in high energy physics. It gives a lot of information about the hadronic interaction and yet to be studied in highest energies levels. It has two observables, a double bump longitude profile in FD and a double shell geometrical structure in SD. In this dissertation, I will describe new methods to identify leading particles and to count muons in air showers. These observations are then compared to simulations using several hadronic physics modeling schemes

NANOCOMPOSITES OF POLY(LACTIC ACID) REINFORCED WITH CELLULOSE NANOFIBRILS

A chemo-mechanical method was used to prepare cellulose nanofibrils dispersed uniformly in an organic solvent. Poly(ethylene glycol) (PEG 1000) was added to the matrix as a compatibilizer to improve the interfacial interaction between the hydrophobic poly(lactic acid) (PLA) and the hydrophilic cellulose nanofibrils. The composites obtained by solvent casting methods from N,N-Dimethylacetamide (DMAc) were characterized by tensile testing machine, atomic force microscope (AFM), scanning electron microscope (SEM), and Fourier transform infrared spectroscopy (FT-IR). The tensile test results indicated that, by adding PEG to the PLA and the cellulose nanofibrils matrix, the tensile strength and the elongation rate increased by 56.7% and 60%, respectively, compared with the PLA/cellulose nanofibrils composites. The FT-IR analysis successfully showed that PEG improved the intermolecular interaction, which is based on the existence of inter-molecular hydrogen bonding among PLA, PEG, and cellulose nanofibrils

Design principles of integrated information platform for emergency responses: The case of 2008 Beijing Olympic Games

This paper investigates the challenges faced in designing an integrated information platform for emergency response management and uses the Beijing Olympic Games as a case study. The research methods are grounded in action research, participatory design, and situation-awareness oriented design. The completion of a more than two-year industrial secondment and six-month field studies ensured that a full understanding of user requirements had been obtained. A service-centered architecture was proposed to satisfy these user requirements. The proposed architecture consists mainly of information gathering, database management, and decision support services. The decision support services include situational overview, instant risk assessment, emergency response preplan, and disaster development prediction. Abstracting from the experience obtained while building this system, we outline a set of design principles in the general domain of information systems (IS) development for emergency management. These design principles form a contribution to the information systems literature because they provide guidance to developers who are aiming to support emergency response and the development of such systems that have not yet been adequately met by any existing types of IS. We are proud that the information platform developed was deployed in the real world and used in the 2008 Beijing Olympic Games. © 2012 INFORMS

Improved Synchronous Machine Rotor Design for the Easy Assembly of Excitation Coils Based on Surrogate Optimization

This paper introduces a new rotor design for the easy insertion and removal of rotor windings. The shape of the rotor is optimized based on a surrogate method in order to achieve low power loss under the maximum power output. The synchronous machine with the new rotor is evaluated in 2-D finite element software and validated by experiments. This rotor shows great potential for reducing the maintenance and repair costs of synchronous machines, making it particularly suited for low-cost mass production markets including gen-sets, steam turbines, wind power generators, and hybrid electric vehicles

Identification of key genes and pathways in human clear cell renal cell carcinoma (ccRCC) by co-expression analysis

Human clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In our study, we screened differential expressed genes, and constructed protein-protein interaction (PPI) network and a weighted gene co-expression network to identify key genes and pathways associated with the progression of ccRCC (n = 56). Functional and pathway enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were significantly enriched in response to wounding, positive regulation of immune system process, leukocyte activation, immune response and cell activation. Downregulated DEGs were significantly enriched in oxidation reduction, monovalent inorganic cation transport, ion transport, excretion and anion transport. In the PPI network, top 10 hub genes were identified (TOP2A, MYC, ALB, CDK1, VEGFA, MMP9, PTPRC, CASR, EGFR and PTGS2). In co-expression network, 6 ccRCC-related modules were identified. They were associated with immune response, metabolic process, cell cycle regulation, angiogenesis and ion transport. In conclusion, our study illustrated the hub genes and pathways involved in the progress of ccRCC, and further molecular biological experiments are needed to confirm the function of the candidate biomarkers in human ccRCC

Fast recognition of single molecules based on single event photon statistics

Mandel Q-parameter, which is determined from single event photon statistics, provides an alternative to differentiate single-molecule with fluorescence detection. In this work, by using the Q-parameter of the sample fluorescence compared to that of an ideal double-molecule system with the same average photon number, we present a novel and fast approach for identifying single molecules based on single event photon statistics analyses, compared with commonly used two-time correlation measurements. The error estimates for critical values of photon statistics are also presented for single-molecule determination.Comment: 13 pages, 4figure

Validation of a simple dynamic thermal performance characterization model based on the piston flow concept for flat-plate solar collectors

A simple dynamic characterization model of flat-plate solar collectors based on the piston flow concept is used both to identify the collector characteristic parameters and to predict the dynamic thermal performance. The heat transport time originally defined as (1 − e−1)−1τC by Amrizal et al. (2012) for the model turns out to be the collector static response time constant τC by analytical derivation. The nonlinear least squares method is applied to determine the characteristic parameters of a flat-plate solar air collector previously tested by the authors. Then the obtained parameters are used to predict the dynamic behavior of the collector outlet temperature. The model coefficients particularly c3 in the simple dynamic characterization model are examined by the collector dynamic prediction under variable meteorological conditions. Meanwhile, the prediction accuracy of the simple dynamic model based on the first-order difference method is compared to that of the numerical solution of the collector ordinary differential equation (ODE) model using the fourth-order Runge-Kutta method. The improved thermal inertia model (TIM) on the basis of closed-form solution presented by Deng et al. (2016a) is also considered. The results show that the prediction performance of the simple dynamic model is nearly as accurate as the ODE numerical solution and the TIM by Deng et al. (2016a) except some special conditions such as sharply changed solar irradiance and collector inlet temperature

Co-immobilization of multiple enzymes by metal coordinated nucleotide hydrogel nanofibers: improved stability and an enzyme cascade for glucose detection

Preserving enzyme activity and promoting synergistic activity via co-localization of multiple enzymes are key topics in bionanotechnology, materials science, and analytical chemistry. This study reports a facile method for co-immobilizing multiple enzymes in metal coordinated hydrogel nanofibers. Specifically, four types of protein enzymes, including glucose oxidase, Candida rugosa lipase, a-amylase, and horseradish peroxidase, were respectively encapsulated in a gel nanofiber made of Zn2+ and adenosine monophosphate (AMP) with a simple mixing step. Most enzymes achieved quantitative loading and retained full activity. At the same time, the entrapped enzymes were more stable against temperature variation (by 7.5 degrees C), protease attack, extreme pH (by 2-fold), and organic solvents. After storing for 15 days, the entrapped enzyme still retained 70% activity while the free enzyme nearly completely lost its activity. Compared to nanoparticles formed with AMP and lanthanide ions, the nanofiber gels allowed much higher enzyme activity. Finally, a highly sensitive and selective biosensor for glucose was prepared using the gel nanofiber to co-immobilize glucose oxidase and horseradish peroxidase for an enzyme cascade system. A detection limit of 0.3 mu M glucose with excellent selectivity was achieved. This work indicates that metal coordinated materials using nucleotides are highly useful for interfacing with biomolecules.Beijing Higher Education Young Elite Teacher Project [YETP0520]; Fundamental Research Funds for the Central Universities [YS1407]; Beijing Natural Science Foundation [2162030]; China Scholarship Council; Natural Sciences and Engineering Research Council of Canada (NSERC

Identification of Biomarkers Associated With Pathological Stage and Prognosis of Clear Cell Renal Cell Carcinoma by Co-expression Network Analysis

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer whose prognostic is affected by the tumor progression associated with complex gene interactions. However, there is currently no available molecular markers associated with ccRCC progression and used or clinical application. In our study, microarray data of 101 ccRCC samples and 95 normal kidney samples were analyzed and 2,425 differentially expressed genes (DEGs) were screened. Weighted gene co-expression network analysis (WGCNA) was then conducted and 11 co-expressed gene modules were identified. Module preservation analysis revealed that two modules (red and black) were found to be most stable. In addition, Pearson's correlation analysis identified the module most relevant to pathological stage(patho-module) (r = 0.44, p = 3e-07). Functional enrichment analysis showed that biological processes of the patho-module focused on cell cycle and cell division related biological process and pathway. In addition, 29 network hub genes highly related to ccRCC progression were identified from the stage module. These 29 hub genes were subsequently validated using 2 other independent datasets including GSE53757 (n = 72) and TCGA (n = 530), and the results indicated that all hub genes were significantly positive correlated with the 4 stages of ccRCC progression. Kaplan-Meier survival curve showed that patients with higher expression of each hub gene had significantly lower overall survival rate and disease-free survival rate, indicating that all hub genes could act as prognosis and recurrence/progression biomarkers of ccRCC. In summary, we identified 29 molecular markers correlated with different pathological stages of ccRCC. They may have important clinical implications for improving risk stratification, therapeutic decision and prognosis prediction in ccRCC patients

Co-expression network analysis identified six hub genes in association with progression and prognosis in human clear cell renal cell carcinoma (ccRCC)

Human clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumors. We constructed a weighted gene co-expression network to identify gene modules associated with clinical features of ccRCC (n = 97). Six hub genes (CCNB2, CDC20, CEP55, KIF20A, TOP2A and UBE2C) were identified in both co-expression and protein-protein interaction (PPI) networks, which were highly correlated with pathologic stage. The significance of expression of the hub genes in ccRCC was ranked top 4 among all cancers and correlated with poor prognosis. Functional analysis revealed that the hub genes were significantly enriched in cell cycle regulation and cell division. Gene set enrichment analysis suggested that the samples with highly expressed hub gene were correlated with cell cycle and p53 signaling pathway. Taken together, six hub genes were identified to be associated with progression and prognosis of ccRCC, and they might lead to poor prognosis by regulating p53 signaling pathway