Probabilistic fracture finite elements

The Probabilistic Fracture Mechanics (PFM) is a promising method for estimating the fatigue life and inspection cycles for mechanical and structural components. The Probability Finite Element Method (PFEM), which is based on second moment analysis, has proved to be a promising, practical approach to handle problems with uncertainties. As the PFEM provides a powerful computational tool to determine first and second moment of random parameters, the second moment reliability method can be easily combined with PFEM to obtain measures of the reliability of the structural system. The method is also being applied to fatigue crack growth. Uncertainties in the material properties of advanced materials such as polycrystalline alloys, ceramics, and composites are commonly observed from experimental tests. This is mainly attributed to intrinsic microcracks, which are randomly distributed as a result of the applied load and the residual stress

Estimating and controlling the traffic Impact of a collaborative P2P system

Nowadays, P2P applications are commonly used in the Internet being an important paradigm for the development of distinct services. However, the dissemination of P2P applications also entails some important challenges that should be carefully addressed. In particular, some of the important coexistence problems existing between P2P applications and Internet Service Providers (ISPs) are mainly motivated by the inherent P2P dynamics which cause traffic to scatter across the network links in an unforeseeable way. In this context, this work proposes a collaborative framework of a Bit- Torrent like system. Using the proposed framework and based on the exchange of valuable information between the application and network levels, some novel techniques are proposed allowing to estimate and control the traffic impact that the P2P system will have on the links of the underlying network infrastructure. Both the framework and the presented techniques were tested resorting to simulation. The results clearly corroborate the viability and effectiveness of the formulated methods

Student Loans and their effect on Parental Views of Education Financing

Using the 2012 wave National Longitudinal Survey of Youth 1979, this study examines the effect that parents\u27 student debt have on their decision to use tax advantage education vehicles to save for their children\u27s college. We also examine parental decisions on obtaining student loans on behalf of their children. The results show that parents who report having student loans are 61% less likely than those that report no student loan debt to use tax-advantaged education saving vehicles. However, we find no difference in the effect of having student loans on the decision to obtain debt to fund their children\u27s college education

The prognostic role of the non-canonical nuclear factor-kappa B pathway in renal cell carcinoma patients

Background: In the United Kingdom, 8,000 cases of renal cancer are diagnosed each year, with a 5-year survival rate of 50%. Treatment options are limited; a potential therapeutic target is the non-canonical nuclear factor-kappa B (NF-κB) pathway. This pathway plays a role in multiple oncogenic processes in solid tumors. The aim of this study was to investigate the non-canonical nuclear factor pathway in renal cell carcinoma (RCC). Materials and Methods: NIK, IKKα, and RelB were investigated via immunohistochemistry in a cohort of 192 patients with clear cell renal cancer. Results: High cytoplasmic NIK was associated with poorer cancer-specific survival (p = 0.006) and 10-year survival stratified from 85% (low) to 65% (high, p = 0.005). Similarly, high cytoplasmic RelB was associated with poorer cancer-specific survival (p = 0.041) and 10-year survival stratified from 88% (low) to 73% (high, p = 0.030). When clinicopathological characteristics were assessed, cytoplasmic NIK was associated with survival (p = 0.014), whereas cytoplasmic RelB was associated with increased tumor grade (p = 0.020) and decreased inflammation (p = 0.019). Upon multivariate analysis, it was found that cytoplasmic NIK was independently associated with cancerspecific survival (p = 0.009). Conclusions: The non-canonical NF-κB pathway is associated with poorer cancer-specific survival in RCC patients, making it a viable target for therapeutic intervention. Furthermore, cytoplasmic NIK is a potential prognostic biomarker for this disease

Non-Carrier Nanoparticles Adjuvant ModularProtein Vaccine in a Particle-Dependent Manner

Nanoparticles are increasingly used to adjuvant vaccine formulations due to their biocompatibility, ease of manufacture and the opportunity to tailor their size, shape, and physicochemical properties. The efficacy of similarly-sized silica (Si-OH), poly (D,L-lactic-co-glycolic acid) (PLGA) and poly caprolactone (PCL) nanoparticles (nps) to adjuvant recombinant capsomere presenting antigenic M2e modular peptide from Influenza A virus (CapM2e) was investigated in vivo. Formulation of CapM2e with Si-OH or PLGA nps significantly boosted the immunogenicity of modular capsomeres, even though CapM2e was not actively attached to the nanoparticles prior to injection (i.e., formulation was by simple mixing). In contrast, PCL nps showed no significant adjuvant effect using this simple-mixing approach. The immune response induced by CapM2e alone or formulated with nps was antibody-biased with very high antigen-specific antibody titer and less than 20 cells per million splenocytes secreting interferon gamma. Modification of silica nanoparticle surface properties through amine functionalization and pegylation did not lead to significant changes in immune response. This study confirms that simple mixing-based formulation can lead to effective adjuvanting of antigenic protein, though with antibody titer dependent on nanoparticle physicochemical properties

A classification framework for drug relapse prediction

This paper proposes a framework for relapse prediction using Artificial Neural Networkalgorithms among drug addicts at Pusat Rawatan Inabah. The data collected will be miningthrough Artificial Neural Network algorithms to generate patterns and useful knowledge andthen automatically classifying the relapse possibility. This research collaborates with PusatRawatan Inabah, which is one of the rehabilitation centers that provide a specific treatment torehabilitate the drug addicts from addiction. We expect that among the classification datamining algorithms, Artificial Intelligence Neural Network (ANN) is one of the bestalgorithms to predict relapse among drug addicts. This may help the rehabilitation center topredict relapse individually and the prediction result is hoped to prevent drug addicts fromrelapse.Keywords: classification; artificial neural network; drug addiction; Inabah rehabilitation

Abundance of unknots in various models of polymer loops

A veritable zoo of different knots is seen in the ensemble of looped polymer chains, whether created computationally or observed in vitro. At short loop lengths, the spectrum of knots is dominated by the trivial knot (unknot). The fractional abundance of this topological state in the ensemble of all conformations of the loop of $N$ segments follows a decaying exponential form, $\sim \exp (-N/N_0)$, where $N_0$ marks the crossover from a mostly unknotted (ie topologically simple) to a mostly knotted (ie topologically complex) ensemble. In the present work we use computational simulation to look closer into the variation of $N_0$ for a variety of polymer models. Among models examined, $N_0$ is smallest (about 240) for the model with all segments of the same length, it is somewhat larger (305) for Gaussian distributed segments, and can be very large (up to many thousands) when the segment length distribution has a fat power law tail.Comment: 13 pages, 6 color figure

The High Pressure Dependence of X-Ray Induced Decomposition of Cadmium Oxalate

The high proclivity of x rays to destabilize and distort molecular structures has been previously utilized in the synthesis of novel compounds. Here, we show that x-ray induced decomposition of cadmium oxalate induces chemical and structural transformations only at 0.5 and 1 GPa. Using x-ray diffraction and Raman spectroscopy, the synthesized product is identified as cadmium carbonate with cadmium oxalate remnants, which is stable under ambient conditions. At ambient and \u3e1 GPa pressures, only degradation of the electronic density distribution is observed. The transformation kinetics are examined in terms of Avrami’s model, which demonstrates that despite the necessity of high pressure for efficient x-ray induced synthesis of cadmium carbonate, the rate and geometry of structural synthesis in the 0.5–1 GPa pressure range do not depend on the applied pressure. In addition, the possible role of intermolecular distance and molecular mobility in transformation yield is also discussed. Our experimental results indicate that x-ray induced photochemical synthetic pathways can be modulated and optimized by specific parameter selection such as high pressure

Residence Time Statistics for Normal and Fractional Diffusion in a Force Field

We investigate statistics of occupation times for an over-damped Brownian particle in an external force field. A backward Fokker-Planck equation introduced by Majumdar and Comtet describing the distribution of occupation times is solved. The solution gives a general relation between occupation time statistics and probability currents which are found from solutions of the corresponding problem of first passage time. This general relationship between occupation times and first passage times, is valid for normal Markovian diffusion and for non-Markovian sub-diffusion, the latter modeled using the fractional Fokker-Planck equation. For binding potential fields we find in the long time limit ergodic behavior for normal diffusion, while for the fractional framework weak ergodicity breaking is found, in agreement with previous results of Bel and Barkai on the continuous time random walk on a lattice. For non-binding potential rich physical behaviors are obtained, and classification of occupation time statistics is made possible according to whether or not the underlying random walk is recurrent and the averaged first return time to the origin is finite. Our work establishes a link between fractional calculus and ergodicity breaking.Comment: 12 page