Verification of the Wavelet-Based HIF Detecting Algorithm Performance in Solidly Grounded MV Networks

The application of the wavelet-based algorithm for arcing high-impedance fault detection medium-voltage (MV) distribution networks is presented in this paper. This paper describes continuation of research on HIF detection with particular reference to algorithm application in solidly grounded MV networks. The results obtained by use of the improved version of the algorithm are presented. The algorithm performance was tested using data obtained from staged HIGFET in a real MV network as well as from EMTP-ATP simulations. Satisfactory results of the algorithm performance were observed for all examined HIF cases in which the ground fault current was greater than 3 A root mean square. The improved algorithm also proved to be more immune to transients generated during switching operations in protected feeders and to capacitor bank switching.     

Continuous activity recognition in a maintenance scenario: combining motion sensors and ultrasonic hands tracking

We describe the design and evaluation of pattern analysis methods for the recognition of maintenance-related activities. The presented work focuses on the spotting of subtle hand actions in a continuous stream of data based on a combination of body-mounted motion sensors and ultrasonic positioning. The spotting and recognition approach is based on three core ideas: (1) the use of location information to compensate for the ambiguity of hand motions, (2) the use of motion data to compensate for the slow sampling rate and unreliable signal of the low cost ultrasonic positioning system, and (3) an incremental, multistage spotting methodology. The proposed methods are evaluated in an elaborate bicycle repair experiment containing nearly 10 h of data from six subjects. The evaluation compares different strategies and system variants and shows that precision and recall rates around 90% can be achieved.     

Rare-earth ion doped up-conversion materials for photovoltaic applications

With the aim of utilizing the infrared region of solar radiation to improve solar cell performance, significant progress, including theoretical analysis and experimental achievement, has been made in the field of up-conversion for photovoltaic applications. This Research News article reviews recent progress in the development of rear-earth (RE) ion doped up-conversion materials for solar cell applications. In addition, new trends for RE-ion-doped phosphors are briefly discussed, among them trivalent RE-ion-doped up-conversion materials for organic solar cell applications.     

Effective Ligand Engineering of the Cu2ZnSnS4 Nanocrystal Surface for Increasing Hole Transport Efficiency in Perovskite Solar Cells

Effective engineering of surface ligands in semiconductor nanocrystals can facilitate the electronic interaction between the individual nanocrystals, making them promising for low‐cost optoelectronic applications. Here, the use of high purity Cu₂ZnSnS₄ (CZTS) nanocrystals as the photoactive layer and hole‐transporting material is reported in low‐temperature solution‐processed solar cells. The high purity CZTS nanocrystals are prepared by engineering the surface ligands of CZTS nanocrystals, capped originally with the long‐chain organic ligand oleylamine. After ligand removal, CZTS nanocrystals show substantial improvement in photoconductivity and mobility, displaying also an appreciable photoresponse in a simple heterojunction solar cell architecture. More notably, CZTS nanocrystals exhibit excellent hole‐transporting properties as interface layer in perovskite solar cells, yielding power conversion efficiency (PCE) of 15.4% with excellent fill factor (FF) of 81%. These findings underscore the importance of removing undesired surface ligands in nanocrystalline optoelectronic devices, and demonstrate the great potential of CZTS nanocrystals as both active and passive material for the realization of low‐cost efficient solar cells.     

Preparation and properties of protein concentrate from broiler chicken heads

The object of this work was to establish the optimal technological conditions for the production of protein concentrate from the heads of broiler chickens by enzymic hydrolysis with papain. It was discovered that hydrolysis is most effective at a temperature of 60°C and a pH of about 7, with 2g of enzyme added per kilogramme of raw material. Under these conditions, 100 kg of heads yielded 7 kg of concentrate and 19.2 kg of waste for feed meal. The concentrate obtained contained about 85% protein and demonstrated good organoleptic and physicochemical properties.     

Recovery of lanthanides from kola apatite in phosphoric acid manufacture

The paper presents the results of bench-scale studies for the recovery of lanthanides from Kola apatite in the phosphoric acid production by a two-stage hemihydrate-dihydrate wet-process. The second stage of the process (hydration of hemihydrate) provides the best conditions for the recovery of lanthanides. In the postulated recovery process use is made of solvent extraction for the removal of lanthanides during hydration of hemihydrate, and precipitation-stripping for the removal of lanthanides from the solvent. Lanthanides are recovered in the form of Ln-enriched concentrates with an efficiency of 80–85%. The process does not disturb the phosphoric acid production, and additionally purifies the by-product gypsum, so that it can be utilized.     

Robust and conventional neuropsychological norms: Diagnosis and prediction of age-related cognitive decline.

The aim of the study was to compare the performance of Robust and Conventional neuropsychological norms in predicting clinical decline among healthy adults and in mild cognitive impairment (MCI). The authors developed Robust baseline cross sectional and longitudinal change norms from 113 healthy participants retaining a normal diagnosis for at least 4 years. Baseline Conventional norms were separately created for 256 similar healthy participants without follow-up. Conventional and Robust norms were tested in an independent cohort of longitudinally studied healthy (n=223), MCI (n=136), and Alzheimer's disease (AD, n=162) participants; 84 healthy participants declined to MCI or AD (NL→DEC), and 44 MCI declined to AD (MCI→AD). Compared to Conventional norms, baseline Robust norms correctly identified a higher proportion of NL→DEC with impairment in delayed memory and attention-language domains. Both norms predicted decline from MCI→AD. Change norms for delayed memory and attention-language significantly incremented baseline classification accuracies. These findings indicate that Robust norms improve identification of healthy individuals who will decline and may be useful for selecting at-risk participants for research studies and early interventions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

System Dynamics (SD) -based concession pricing model for PPP highway projects

The design of concession price is essential to financial viability of Public–Private Partnership (PPP) highway projects. It is one of the most important variables that need to be determined during the negotiation period. However, there are few methods available for calculating the value of this variable. Research described in this paper aims to develop a reliable, objective, and systematic model for determining a rational concession price for PPP highway projects based on pro forma financial statements developed during the feasibility study period. The pricing parameters and price risk factors of PPP highway project were first identified and compiled through a comprehensive literature review. A concession pricing model using System Dynamics technique was then developed based on concession pricing parameters and the effectiveness of the proposed SD-based concession pricing model was verified by a real toll tunnel project located in China. The test result shows that the proposed model is reliable, accurate, and suitable for the application by practitioners for concession price determination. To overcome the effect of risk factors on concession price, a pricing adjustment model using Case-base Reasoning (CBR) technique was proposed to consider the unquantifiable risk factors. It is believed that a rational and practical concession pricing model can create a ‘win–win’ situation for both the private investor and the host government. This research framework can also be used as a reference to study other facilities' pricing models.     

Viscoelastic properties of highly concentrated maize starch solutions in DMSO

Rheological measurements of highly concentrated dimethylsulfoxide (DMSO) starch solutions were performed. For all experiments commercial maize starch with different AM content was used. The research covered a wide range of polymer concentrations depending on linear fraction contribution and allowed to obtain a starch content up to 40% w/w. The analysis covered the time – concentration superposition method and fitting the continuous Maxwell model to the experimental data using Tikhonov regularization method. The results allowed statements about the viscoelastic behavior of non‐aqueous starch solutions, depending on their molecular structure. If the linear AM is the predominant component of the starch, the system behaves more elastic compared to those composed of branched AP. The effect of variation in molecular constitution is stronger than the effect of concentration of the dispersion. Additionally, the molecular masses of both fractions seems not to be the crucial factor for rheological properties as well as biopolymer solubility in DMSO. Relaxation spectra obtained from Maxwell model show the drift of the main peak to shorter relaxation times when the concentration of biopolymer is rising. The phenomenon testifies about the influence of starch concentration on elastic response of the system.     

Immigration and Construction: Analysis of the Impact of Immigration on Construction Project Costs

There are an estimated 11 million illegal immigrants currently residing in the United States. Of this population, research shows that approximately 19% work in the construction industry, comprising around 14% of all construction workforces. The main objectives of this research are to (1) to predict possible effects of immigration and immigration reform legislation on worker wages and (2) to assess the likely wage increase due to decreased supply of immigrant labor. In the Washington, D.C. metropolitan region, the construction workforces for low-skilled trades such as concrete, masonry, drywall, painting, flooring, and roofing are comprised of approximately 55% illegal immigrant. Based on four factors evaluated in this research (1) prevailing wage provision in legislation; (2) forced tax compliance of the workforce; (3) market correction from currently depressed wages due to immigrant penetration into the workforce; and (4) a labor shortage resulting from a depleted supply of immigrant labor, proposed legislation could increase the cost of trade labor up to almost 70% in the Washington, D.C. metropolitan area. Overall labor costs for projects could increase by almost 18%, and total project costs could rise almost 12% in the Washington, D.C. metropolitan region.