Multiple Linear Regression Model for Total Bed Material Load Prediction

A new total bed material load equation that is applicable for rivers in Malaysia was developed using multiple linear regression analyses. A total of 346 hydraulic and sediment data were collected from nine natural and channelized rivers having diverse catchment characteristics in Malaysia. The governing parameters were carefully selected based on literature survey and field experiments, examined and grouped into five categories namely mobility, transport, sediment, shape, and flow resistance parameters. The most influential parameters from each group were selected by using all possible regression model method. The suitable model selection criteria namely the R-square, adjusted R-square, mean square error, and Mallow’s Cp statistics were employed. The accuracy of the derived model is determined using the discrepancy ratio, which is a ratio of the calculated values to the measured values. The best performing models that give the highest percentage of prediction from the validation data were chosen. In general, the newly derived model is best suited for rivers with uniform sediment size distribution with a d50 value within the range of 0.37–4.0 mm and performs better than the commonly used Graf, Yang, and Ackers–White total bed material load equations.     

Void formation and morphology in NiAl

Void formation in stoichiometric NiAl was studied through controlled heat treatments and microstructural characterization through transmission electron microscopy. Voids were observed to form at temperatures as low as 400°C, but were noted to dissolve during annealing at 900°C. Two distinct void shapes, cuboidal and rhombic dodecahedral, were observed, often at the same annealing temperature. At higher temperatures (800°C) extensive dislocation climb, rather than void formation, was noted. The relative incidence of void formation and dislocation climb can be related to the mobility of vacancies at each annealing temperature. The shape of void type is described in terms of their relative surface energy and mode of nucleation.     

Prediction of scour below submerged pipeline crossing a river using ANN

The process involved in the local scour below pipelines is so complex that it makes it difficult to establish a general empirical model to provide accurate estimation for scour. This paper describes the use of artificial neural networks (ANN) to estimate the pipeline scour depth. The data sets of laboratory measurements were collected from published works and used to train the network or evolve the program. The developed networks were validated by using the observations that were not involved in training. The performance of ANN was found to be more effective when compared with the results of regression equations in predicting the scour depth around pipelines.     

\mathcal{C}oo\mathcal{PS} – Towards a method for coordinating personalized services

This paper presents oo which is a method for oordinating ersonalized Services. These services are primarily offered to mobile users. The concept of services is the object of intense investigations from both academia and industry. However, very little has been accomplished so far regarding first, personalizing services for the benefit of mobile users, and second, providing the appropriate methodological support for those (i.e., designers) who will be specifying the operations of personalization. Various obstacles still exist such as lack of techniques for modeling and specifying the integration of personalization into services, and existing approaches for service composition typically facilitate orchestration only, while neglecting contexts of users and services. ooconsists of several steps ranging from service definition and personalization to service deployment. Each step has some representation techniques, which aim at facilitating the specification and validation of the operations of coordinating personalized services. Zakaria Maamar is an associate professor in computer sciences at Zayed University, Dubai, United Arab Emirates. His research interests include Web services, software agents, and context-aware computing. Maamar has a PhD in computer sciences from Laval University. Djamal Benslimane is a full professor in computer sciences at Claude Bernard Lyon 1 University and a member of the Laboratoire d'InfoRmatique en Images et Systèmes d'information- Centre National De la Recherche Scientifique (LIRIS-CNRS), both in Lyon, France. His research interests include interoperability, Web services, and ontologies. Benslimane has a PhD in computer sciences from Blaise Pascal University. Michael Mrissa is a Ph.D. candidate in computer sciences at Claude Bernard Lyon 1 University and a member of the Laboratoire d'InfoRmatique en Images et Systèmes d'information - Centre National De la Recherche Scientifique (LIRIS-CNRS), both in Lyon, France. His research interests include semantic Web services, interoperability and peer-to-peer networks. Chirine Ghedira is an associate professor in computer sciences at Claude Bernard Lyon 1 University and a member of the Laboratoire d'InfoRmatique en Images et Systèmes d'information- Centre National De la Recherche Scientifique (LIRIS-CNRS), both in Lyon, France. Her research interests include Web services and context-aware computing. Ghedira has a PhD in computer sciences from the National Institute for Applied Sciences (INSA).     

Improvement of thermal conductivity and dielectric constant of graphene-filled epoxy nanocomposites using colloidal polymerization approach

Polymer Bulletin - The effect of the polymeric cross-link density on the thermal conductivity of an oxidized graphene (OG)-filled epoxy nanocomposite was investigated by two different fabrication...     

Low‐Energy Room‐Temperature Healing of Cellular Metals

Healing metallic materials involves high temperatures and large energy inputs. This work demonstrates rapid, effective, low‐energy, and room‐temperature healing of metallic materials by using electrochemistry and polymer‐coated cellular nickel to mimic the transport‐mediated healing of bone. The polymer coating enables selective healing only at the fracture site, electrochemical reactions transport metal ions from a metal source to fractured areas, and the cellular structure of the metal allows facile ion transport to healing sites and effective recovery of strength and toughness when the cellular metal is subjected to three types of damage (scission fracture, tensile failure, and plastic deformation). Using this strategy, samples fractured in tension and by scission recover 100% of their tensile strength in as little as 10 and 4 h of healing. The healing process is stochastic, thus a statistical method is used to quantify and predict the likelihood of achieving target healing strengths based on energy input. This electrochemistry‐based approach enables the first demonstration of room‐temperature healing of structural metallic materials and requires several orders of magnitude less energy than many previously reported metal healing techniques.     

Multivariate High-Order Attacks of Shuffled Tables Recomputation

Masking schemes based on tables recomputation are classical countermeasures against high-order side-channel attacks. Still, they are known to be attackable at order d in the case the masking involves d shares. In this work, we mathematically show that an attack of order strictly greater than d can be more successful than an attack at order d. To do so, we leverage the idea presented by Tunstall, Whitnall and Oswald at FSE 2013: We exhibit attacks which exploit the multiple leakages linked to one mask during the recomputation of tables. Specifically, regarding first-order table recomputation, improved by a shuffled execution, we show that there is a window of opportunity, in terms of noise variance, where a novel highly multivariate third-order attack is more efficient than a classical bivariate second-order attack. Moreover, we show on the example of the high-order secure table computation presented by Coron at EUROCRYPT 2014 that the window of opportunity enlarges linearly with the security order d. These results extend that of the CHES ’15 eponymous paper. Here, we also investigate the case of degree one leakage models and formally show that the Hamming weight model is the less favorable to the attacker. Eventually, we validate our attack on a real ATMEL smartcard.     

Far-infrared spectroscopy of protein higher-order structures

Far-infrared (FIR) spectroscopy in the spectral region of 50-450 cm(-1) was used to study a series of protein higher-order structures constructed using β-lactoglobulin and polyomavirus capsid protein VP1. There were marked differences in the spectra for β-lactoglobulin monomer and dimer and between untreated β-lactoglobulin and heat-induced gels formed at neutral pH. Untreated β-lactoglobulin and heat-induced gels formed at acidic pH exhibited little difference in their spectra. Assembly of the quaternary structure of polyomavirus virus-like particles also caused large changes in the FIR spectra. These findings suggest that FIR spectroscopy may prove useful in studying some protein quaternary and higher-order structures. There was evidence of detection of β-lactoglobulin dimerization, intermolecular disulfide bonding in heat-induced neutral gels, and polyomavirus virus-like particle assembly but no evidence that FIR could detect β-lactoglobulin fibrils with their polymeric structure and hydrogen-bonded intermolecular β-pleated sheeting.     

Surface modification of ZnO nanorods with CdS quantum dots for application in inverted organic solar cells: effect of deposition duration

Incorporating cadmium sulfide quantum dots (CdS QDs) onto ZnO nanorod (ZNRs) has been investigated to be an efficient approach to enhance the photovoltaic performance of the inverted organic solar cell (IOSC) devices based on ZNRs/poly (3-hexylthiophene) (P3HT). To synthesize CdS/ZNRs, different durations of deposition per cycle from 1 to 9 min were used to deposit CdS via SILAR technique onto ZNRs surface grown via hydrothermal method at low temperature on FTO substrate. In typical procedures, P3HT as donor polymer were spun-coating onto CdS/ZNRs to fabricate IOSC devices, followed by Ag deposition as anode by magnetron sputtering technique. Incorporation of CdS QDs has modified the morphological, structural, and optical properties of ZNRs. Incorporation of CdS QDs onto ZNRs also led to higher open circuit voltage (V_oc) and short circuit current density (J_sc) of optimum ZNRs/CdS QDs devices due to the increased interfacial area between ZNRs and P3HT for more efficient exciton dissociation, reduced interfacial charge carrier recombination as a result of lower number of oxygen defects which act as electron traps in ZnO and prolonged carrier recombination lifetime. Therefore, the ZNRs/CdS QDs/P3HT device exhibited threefold higher PCE (0.55%) at 5 min in comparison to pristine ZNR constructed device (0.16%). Overall, our study highlights the potential of ZNRs/CdS QDs to be excellent electron acceptors for high efficiency hybrid optoelectronic devices.     

Latex-coated polymeric monolithic ion-exchange stationary phases. 2. Micro-ion chromatography

Latex-coated monolithic polymeric stationary phases are used for micro-ion chromatography (mu-IC) of inorganic anions. Monolithic columns were prepared by the in situ polymerization of butyl methacrylate, ethylene dimethacrylate, and 2-acrylamido-2-methyl-1-propanesulfonic acid within fused-silica capillaries of varying internal diameters. Introduction of ion-exchange sites was achieved by coating the anionic polymeric monolith with either Dionex AS10 or Dionex AS18 quaternary ammonium functionalized latex particles to give total ion-exchange capacities in the range 9-24 nequiv for a 30-cm column. The resultant mu-IC columns were used for the separation of anionic analytes using chloride or acetate as the eluent-competing ion and direct UV spectrophotometric detection at 195 nm or using hydroxide as the eluent-competing ion and suppressed or nonsuppressed contactless conductivity detection. Separation efficiencies of 13,000 plates/m were observed (for iodate), and separation efficiency was maintained for large increases in flow rate (up to 42 microL/min, corresponding to a linear flow velocity of 18.5 mm/s), enabling highly reproducible, rapid separations to be achieved (seven analyte anions in less than 2 min). Use of a hollow fiber micromembrane suppressor enabled effective suppression of hydroxide eluents over the range 0.5-5.0 mM, thereby permitting suppressed conductivity detection to be performed. However, the relatively large size of the suppressor resulted in reduced separation efficiencies (e.g., 5400 plates/m for iodate). Detection limits obtained with suppressed conductivity detection were in the range 0.4-1.2 microM.