Analysis of insulin-like growth factors (IGF)-I, and -II, type II IGF receptor and IGF-binding protein-2 mRNA and peptide levels in normal and nephrectomized rat kidney

Immunocytochemistry, in situ hybridization, and radioimmunoassay were employed to examine the cellular distribution of mRNAs and proteins for IGF-I, II, IGF-II/M6P receptor, IGFBP2 as well as the levels of IGF-I and II in normal and unilaterally nephrectomized (Nx) adult rat kidneys. A similar distribution of immunoreactive IGF-I, and -II as well as IGF-II/M6P receptor was found in the principal cells of the cortical collecting duct and in all cells of the inner medullary collecting duct. In addition, immunostainable IGF-I and IGF-II/M6P receptor were noted in some inner medullary loops of Henle, while IGFBP2 was seen in the collecting ducts and loops of Henle of the inner medullar and the renal vasculature of all animals. By comparison, in situ hybridization revealed IGF-I mRNA only in the medullary thick ascending limbs while IGF-II mRNA was localized to the wall of the renal microvasculature in all kidneys. IGFBP2 mRNA was localized to the renal corpuscle and to inner medullary interstitial cells of all kidneys. These data suggest that renal IGF-I and IGFBP2 are synthesized at upstream sites along the nephron and then transported downstream for interaction with IGF receptors. Following nephrectomy, the renal levels of IGF-I peptide and mRNA were elevated at both 5 and 33 days post-nephrectomy, supporting a potential functional role for IGF-I in stimulating the structural and functional recovery in compensatory hypertrophy.     

Design and Management of Subsurface Horizontal Drainage to Reduce Salt Loads

Many irrigated areas have shallow water tables creating waterlogging and salinization problems. This has often been controlled by installation of subsurface horizontal pipe drainage; however, these systems export large amounts of salt off farm in the drainage effluent. Improved design and management of subsurface drainage systems to reduce drainage salt loads were tested in a replicated field experiment. Deep, widely spaced drains allowed to flow without control were compared to drains with management to reduce drain flow. These were also compared with shallow, closely spaced drains that protected the root zone only and an undrained control. The deep drains flowed continuously during the two irrigation seasons with an electrical conductivity of around 11 dS∕m resulting in a drainage salt load of 5,867 kg∕ha. The management measures reduced drainage volume and salinity resulting in a 50% reduction in salt load. The shallow drains only flowed directly after an irrigation or rainfall event with low salinity, around 2 dS∕m, resulting in a 95% reduction in salt load. This showed that by management there is great potential for reducing salt mobilization in existing drainage systems, and for new systems shallower drains will minimize salt loads.     

Silica based polishing of {100} and {111} single crystal diamond

Diamond is one of the hardest and most difficult to polish materials. In this paper, the polishing of {111} and {100} single crystal diamond surfaces by standard chemical mechanical polishing, as used in the silicon industry, is demonstrated. A Logitech Tribo Chemical Mechanical Polishing system with Logitech SF1 Syton and a polyurethane/polyester polishing pad was used. A reduction in roughness from 0.92 to 0.23 nm root mean square and 0.31 to 0.09 nm rms for {100} and {111} samples respectively was observed.     

Force‐Driven Single‐Atom Manipulation on a Low‐Reactive Si Surface for Tip Sharpening

A single atomic manipulation on the delta‐doped B:Si(111)‐()R30° surface using a low temperature dynamic atomic force microscopy based on the Kolibri sensor is investigated. Through a controlled vertical displacement of the probe, a single Si adatom in order to open a vacancy is removed. It is shown that this process is completely reversible, by accurately placing a Si atom back into the vacancy site. In addition, density functional theory simulations are carried out to understand the underlying mechanism of the atomic manipulation in detail. This process also rearranges the atoms at the tip apex, which can be effectively sharpened in this way. Such sharper tips allow for a deeper look into the Si adatom vacancy site. Namely, high‐resolution images of the vacancy showing subsurface Si dangling bond triplets, which surround the substitutional B dopant atom in the first bilayer, are achieved.     

From volatility to value: analysing and managing financial and performance risk in energy savings projects

Many energy-related investments are made without a clear financial understanding of their values, risks, and volatilities. In the face of this uncertainty, the investor—such as a building owner or an energy service company—will often choose to implement only the most certain and thus limited energy-efficiency measures. Conversely, commodities traders and other sophisticated investors accustomed to evaluating investments on a value, risk, and volatility basis often overlook energy-efficiency investments because risk and volatility information are not provided. Fortunately, energy-efficiency investments easily lend themselves to such analysis using tools similar to those applied to supply side risk management. Accurate and robust analysis demands a high level of understanding of the physical aspects of energy-efficiency, which enables the translation of physical performance data into the language of investment. With a risk management analysis framework in place, the two groups—energy-efficiency experts and investment decision-makers—can exchange the information they need to expand investment in demand-side energy projects. In this article, we first present the case for financial risk analysis in energy efficiency in the buildings sector. We then describe techniques and examples of how to identify, quantify, and manage risk. Finally, we describe emerging market-based opportunities in risk management for energy efficiency.     

Boron-doped diamond anodic treatment of landfill leachate: evaluation of operating variables and formation of oxidation by-products

Landfill leachate with a low BOD/COD ratio was electrochemically oxidized by means of a boron-doped diamond anode. In addition to organic matter removal, this study addressed the issue of formation of both chlorinated organic compounds and nitrate ions as a result of organic matter and ammonia and/or organic nitrogen electro-oxidation in the presence of chloride ions. A factorial design methodology was implemented to evaluate the statistically important operating variables: treatment time (1-4 h), pH (5-8), current intensity (6.3-8.4 A) and addition of chloride (2500-4500 mg L⁻¹). The process was evaluated on COD, total nitrogen (TN) and colour removal, as well as on the formation of nitrate, nitrite and chlorinated organics. Of the four variables studied, treatment time and pH had a considerable influence on COD and colour removal. On the contrary, none of the variables had a significant effect on the elimination of TN for which an average removal of 61 mg L⁻¹ was obtained. The studied variables exhibited different effects on the four groups of organo-chlorinated compounds considered in this study, namely trihalomethanes (THMs), haloacetonitriles (HANs), haloketons (HKs) and 1,2-dichloroethane (DCA). Further analysis at more intense conditions, i.e. current intensity up to 18 A and reaction time up to 8 h revealed that high levels of decolourization (84%) could be achieved followed by low COD (51%) and ammonia (32%) removals. Apart from DCA, the concentration of chlorinated organics increased continuously with treatment time reaching values as high as 1.9 mg L⁻¹, 753 μg L⁻¹ and 431 μg L⁻¹ of THMs, HANs and HKs, respectively.     

Black applicants' reactions to affirmative action plans: Effects of plan content and previous experience with discrimination.

This study examined the effects of plan content and previous experience with discrimination on Black respondents' reactions to affirmative action plans. Black engineering students (N=1,173) were randomly assigned to 1 of 6 plans implemented by a hypothetical organization and were asked to provide ratings of perceived fairness and intention to pursue a position at the organization. There were significant effects of plan content on perceived fairness and job pursuit intentions, Perceived fairness mediated the effect of content on intentions. Furthermore, previous experience with discrimination interacted with content to affect intentions. Individuals who had experienced relatively more discrimination in the workplace reported stronger intentions to pursue a position at an organization whose plan specified special training opportunities for minorities. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

In-process regressions and adaptive multicriteria neural networks for monitoring and supervising machining operations

The authors develop a monitoring and supervising system for machining operations using in-process regressions (for monitoring) and adaptive feedforward artificial neural networks (for supervising). The system is designed for: (1) in-process tool life measurement and prediction; (2) supervision of machining operations in terms of the best machining setup; and (3) catastrophic tool failure monitoring. The monitoring system predicts tool life by using different sensors for gathering information based on a regression model that allows for the variations between tools and different machine setups. The regression model makes its prediction by using the history of other tools and combining it with the information obtained about the tool under consideration. The supervision system identifies the best parameters for the machine setup problem within the framework of multiple criteria decision making. The decision maker (operator) considers several criteria, such as cutting quality, production rate and tool life. To make the optimal decision with several criteria, an adaptive feedforward artificial neural network is used to assess the decision maker's preferences. The authors' neural network approach learns from the decision maker's complex behavior and hence, in automatic mode, can make decisions for the decision maker. The approach is not computationally demanding, and experiments demonstrate that its predictions are accurate.