The Electrolytic “Sintering” of Nickel Powder

Adherent and coherent deposits of nickel sponge similar to sintered nickel may be made from sulphate, chloride, fluoborate or sulphamate nickel plating solutions containing nickel powder in suspension, providing the concentration of free acid is maintained sufficiently high to inhibit co-depesition of Ni(OH) In nitrate solution, cathodic reduction of nitrate and deposition of Ni(OH)₂ predominates.     

An effort prediction framework for software defect correction

This article tackles the problem of predicting effort (in person–hours) required to fix a software defect posted on an Issue Tracking System. The proposed method is inspired by the Nearest Neighbour Approach presented by the pioneering work of Weiss et al. (2007) [1]. We propose four enhancements to Weiss et al. (2007) [1]: Data Enrichment, Majority Voting, Adaptive Threshold and Binary Clustering. Data Enrichment infuses additional issue information into the similarity-scoring procedure, aiming to increase the accuracy of similarity scores. Majority Voting exploits the fact that many of the similar historical issues have repeating effort values, which are close to the actual. Adaptive Threshold automatically adjusts the similarity threshold to ensure that we obtain only the most similar matches. We use Binary Clustering if the similarity scores are very low, which might result in misleading predictions. This uses common properties of issues to form clusters (independent of the similarity scores) which are then used to produce the predictions. Numerical results are presented showing a noticeable improvement over the method proposed in Weiss et al. (2007) [1].     

Towards a goal‐driven approach to action selection in self‐adaptive software

Self‐adaptive software is a closed‐loop system, since it continuously monitors its context (i.e. environment) and/or self (i.e. software entities) in order to adapt itself properly to changes. We believe that representing adaptation goals explicitly and tracing them at run‐time are helpful in decision making for adaptation. While goal‐driven models are used in requirements engineering, they have not been utilized systematically yet for run‐time adaptation. To address this research gap, this article focuses on the deciding process in self‐adaptive software, and proposes the Goal‐Action‐Attribute Model (GAAM). An action selection mechanism, based on cooperative decision making, is also proposed that uses GAAM to select the appropriate adaptation action(s). The emphasis is on building a light‐weight and scalable run‐time model which needs less design and tuning effort comparing with a typical rule‐based approach. The GAAM and action selection mechanism are evaluated using a set of experiments on a simulated multi‐tier enterprise application, and two sample ordinal and cardinal action preference lists. The evaluation is accomplished based on a systematic design of experiment and a detailed statistical analysis in order to investigate several research questions. The findings are promising, considering the obtained results, and other impacts of the approach on engineering self‐adaptive software. Although, one case study is not enough to generalize the findings, and the proposed mechanism does not always outperform a typical rule‐based approach, less effort, scalability, and flexibility of GAAM are remarkable. Copyright © 2011 John Wiley & Sons, Ltd.     

Achieving dynamic adaptation via management and interpretation of runtime models

In this article, we present a generic model-centric approach for realizing fine-grained dynamic adaptation in software systems by managing and interpreting graph-based models of software at runtime. We implemented this approach as the Graph-based Runtime Adaptation Framework (GRAF), which is particularly tailored to facilitate and simplify the process of evolving and adapting current software towards runtime adaptivity. As a proof of concept, we present case study results that show how to achieve runtime adaptivity with GRAF and sketch the framework's capabilities for facilitating the evolution of real-world applications towards self-adaptive software. The case studies also provide some details of the GRAF implementation and examine the usability and performance of the approach.     

Synthesis and Characterization of NiO Nano‐Spheres by Templating on Chitosan as a Green Precursor

In this study, nickel oxide was prepared through the calcination of extrusion dripped chitosan/nickel nitrate beads. The morphology and structural properties of the products were studied using various characterization techniques. Uniformly distributed nickel oxide was formed as observed from the studies of surface morphology where the processing parameters play a huge role on the resulting morphology. TEM results have shown that nickel oxide with crystallite sizes of 10–30 nm was obtained. The Fourier‐transform infrared spectra studies show an intense peak at 525 cm^?1, which is attributed to the vibration of Ni–O bond. Furthermore, the XRD results show NiO diffraction peaks correspond to (111), (200), (220), (311), and (222) which indicates that a bunsenite structure with a face‐centered cubic phase was produced in this study. The usage of 500°C as the lower limit in this study is justified due to the complete removal of the templating material as seen in the thermalgravimetric analysis studies. Furthermore, it was obtained that the largest surface area of nickel oxide synthesized using this technique is 48.024 m²/g with pore sizes of 19.843 nm. The usage of chitosan as a green template for the synthesis of nanoparticles has shown promising results which allows a more economical and sustainable approach for the fabrication of nanomaterials.     

Amine-functionalized and non-functionalized mesoporous silica nanoparticles as the delivery system for tertiary butylhydroquinone (TBHQ)

Journal of Porous Materials - The aim of this study was to encapsulate 2-tert-butylhydroquinone (TBHQ), as a common synthetic antioxidant in food industries, by mesoporous silica nanoparticles...     

Temporal Evolution of Normal Hot Spots in Current-Driven Superconducting Films

In addition to the critical current I_c (T), which generates Phase-Slip Centers (PSCs), thin superconducting films possess a well-defined second limiting current I_h, or current intensity able to maintain a preestablished hot spot. By pulsing step functions of the current and monitoring the voltage response on the nanosecond scale, we have determined (T I_c) and (T I_h). From a dynamic study of the two main modes of dissipation in YBCO and Nb films, it is concluded that PSCs are stable structures in current-biased bridges. In contrast, hot spots grow at a constant rate of a few tens of meters per second, determined by the thermal diffusivity of the material and by its bolometric response time. On reducing the current from I_h, the so-called healing length, or minimum normal length, was found, of the order of 0.2 m in YBCO and 2 m in Nb. In summary, the experiment provides three independent measurements (PSC nucleation time, velocity of growth, and minimum length) for only two parameters (D and ).     

Spontaneous and Light-Induced Resistive Transitions in Superconducting Thin Film Bridges

In order to study dynamically the resistive states which appear as jumps in the I–V curves of narrow bridges, we have submitted YBaCuO and Nb films to nanosecond current steps and laser pulses simultaneously. In constant current feed, the distinction between hot spots (HS) and phase-slip centers (PSCs) is unambiguous, since HS are compelled to grow or decay, at variance with the stable-in-time PSCs. Thanks to the transient method we show that, even if Joule dissipation associated to a current I is virtually sufficient to sustain the film above T_c, the zero resistance state remains metastable: a hot spot does not arise unless initiated by a PSC, which fact was not reported before. The domains of occurrence of HS and PSCs were then organized in a current–temperature plane. Finally, the theoretical problem of the HS velocity of growth is given an exact solution, in semiquantitative agreement with experiment.     

The applications of nanotechnology in food industry

Nanotechnology has the potential of application in the food industry and processing as new tools for pathogen detection, disease treatment delivery systems, food packaging, and delivery of bioactive compounds to target sites. The application of nanotechnology in food systems will provide new methods to improve safety and the nutritional value of food products. This article will review the current advances of applications of nanotechnology in food science and technology. Also, it describes new current food laws for nanofood and novel articles in the field of risk assessment of using nanotechnology in the food industry.