Controlling Investment Decisions: Hurdle Rates and Intertemporal Cost Allocation

We examine alternative performance measures for a manager who has superior information about the profitability of an investment project and who contributes to periodic operating cash flows through his efforts. We find that residual income based on a suitably chosen depreciation schedule is an optimal performance measure. To address the underlying asymmetric information problem, the capital charge rate in the calculation of residual income should be equal to the firm's hurdle rate, which is the critical internal rate of return below which the principal would not want to fund the project. This hurdle rate includes the compensation cost for the better informed manager and therefore exceeds the principal's cost of capital. We also show that residual income remains an optimal performance measure in settings where multiple divisions compete for scarce investment funds. In order to solve the resource allocation problem, the capital charge rate must then be increased to a competitive hurdle rate.

Effect of processing on fracture toughness of silicon carbide as determined by Vickers indentations

Several alpha-SiC materials were processed by hot isostatic pressing (HIPing) and by sintering an alpha-SiC powder containing boron and carbon. Several beta-SiC materials were processed by HIPing a beta-SiC powder with boron and carbon additions. The fracture toughnesses K(sub 1c) of these beta- and alpha-SiC materials were estimated from measurements of Vickers indentations. The three formulas used to estimate K(sub 1c) from the indentation fracture patterns resulted in three ranges of K(sub 1c) estimates. Furthermore, each formula measured the effects of processing differently. All three estimates indicated that fine-grained HIPed alpha-SiC has a higher K(sub 1c) than coarsed-grained sintered alpha-SiC. Hot isostatically pressed beta-SiC, which had an ultrafine grain structure, exhibited a K(sub 1c) comparable to that of HIPed alpha-SiC

High-strength silicon carbides by hot isostatic pressing

Silicon carbide has strong potential for heat engine hardware and other high-temperature applications because of its low density, good strength, high oxidation resistance, and good high-temperature creep resistance. Hot isostatic pressing (HIP) was used for producing alpha and beta silicon carbide (SiC) bodies with near-theoretical density, ultrafine grain size, and high strength at processing temperatures of 1900 to 2000 C. The HIPed materials exhibited ultrafine grain size. Furthermore, no phase transformation from beta to alpha was observed in HIPed beta-SiC. Both materials exhibited very high average flexural strength. It was also shown that alpha-SiC bodies without any sintering aids, when HIPed to high final density, can exhibit very high strength. Fracture toughness K (sub C) values were determined to be 3.6 to 4.0 MPa m (sup 1/2) for HIPed alpha-SiC and 3.7 to 4.1 MPa m (sup 1/2) for HIPed beta-SiC. In the HIPed specimens strength-controlling flaws were typically surface related. In spite of improvements in material properties such as strength and fracture toughness by elimination of the larger strength-limiting flaws and by grain size refinement, HIPing has no effect on the Weibull modulus

HBCUs Research Conference agenda and abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Lewis Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Lewis technical monitors, and other Lewis researchers

HBCUs Research Conference Agenda and Abstracts

The purpose of this Historically Black Colleges and Universities (HBCUs) Research Conference was to provide an opportunity for principal investigators and their students to present research progress reports. The abstracts included in this report indicate the range and quality of research topics such as aeropropulsion, space propulsion, space power, fluid dynamics, designs, structures and materials being funded through grants from Lewis Research Center to HBCUs. The conference generated extensive networking between students, principal investigators, Lewis technical monitors, and other Lewis researchers

Effect of Iron/Folic Acid Supplementation on the Outcome of Malaria Episodes Treated with Sulfadoxine-Pyrimethamine

Folic acid supplementation may potentially alter the efficacy of sulfadoxine-pyrimethamine (SP) treatment in children with malaria. However, there is lack of evidence fromrandomized controlled trials and effects of folic acid supplementation on clinical efficacy of SP therapy remainmoderately understood among children. In a doublemasked, placebo-controlled trial among preschool children in Pemba Island (Tanzania), iron and folic acid supplementation (Fe/FA) showed an increased risk of hospitalizations and death. In the present paper, we evaluated if folic acid supplementation reduced the efficacy of malaria treatment and thereby contributed to observed adverse effects. During the study, 1648 children had confirmed malarial episodes and received either sulphadoxinepyrimethamine(SP) treatment and iron folic acid or SP treatment and placebo. These children were evaluated for recovery and incidence of hospitalization during the next 15, 30, and 140 days. Two groups did not differ in malarial episode or hospitalization rate on subsequent 15, 30, and 140 days. Altered efficacy of SP by folic acid was not observed and did not contribute to adverse events in the previous trial.This trial is registered with Controlled-trials.com ISRCTN59549825

Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance

Decision‐making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream‐flows in north‐eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.Crop Production/Industries, Risk and Uncertainty,

Capacity rights and full cost transfer pricing

This paper examines the theoretical properties of full cost transfer prices in multi-divisional firms. In our model, divisional managers are responsible for the initialacquisition of productive capacity and the utilization of that capacity in subsequentperiods, once operational uncertainty has been resolved. We examine alternativevariants of full cost transfer pricing with the property that the discounted sum oftransfer payments is equal to the initial capacity acquisition cost and the presentvalue of all subsequent variable costs of output supplied to a division. Our analysisidentifies environments where particular variants of full cost transfer pricing induceefficiency in both the initial investments and the subsequent output levels. Ourfindings highlight the need for a proper integration of intracompany pricing rules anddivisional control rights over capacity assets

F-box protein FBXO31 directs degradation of MDM2 to facilitate p53-mediated growth arrest following genotoxic stress

The tumor suppressor p53 plays a critical role in maintaining genomic stability. In response to genotoxic stress, p53 levels increase and induce cell-cycle arrest, senescence, or apoptosis, thereby preventing replication of damaged DNA. In unstressed cells, p53 is maintained at a low level. The major negative regulator of p53 is MDM2, an E3 ubiquitin ligase that directly interacts with p53 and promotes its polyubiquitination, leading to the subsequent destruction of p53 by the 26S proteasome. Following DNA damage, MDM2 is degraded rapidly, resulting in increased p53 stability. Because of the important role of MDM2 in modulating p53 function, it is critical to understand how MDM2 levels are regulated. Here we show that the F-box protein FBXO31, a candidate tumor suppressor encoded in 16q24.3 for which there is loss of heterozygosity in various solid tumors, is responsible for promoting MDM2 degradation. Following genotoxic stress, FBXO31 is phosphorylated by the DNA damage serine/threonine kinase ATM, resulting in increased levels of FBXO31. FBXO31 then interacts with and directs the degradation of MDM2, which is dependent on phosphorylation of MDM2 by ATM. FBXO31-mediated loss of MDM2 leads to elevated levels of p53, resulting in growth arrest. In cells depleted of FBXO31, MDM2 is not degraded and p53 levels do not increase following genotoxic stress. Thus, FBXO31 is essential for the classic robust increase in p53 levels following DNA damage

Ensemble Learning Based Malicious Node Detection in SDN-Based VANETs

Background: The architecture of Software Defined Networking (SDN) integrated with Vehicular Ad-hoc Networks (VANETs) is considered a practical method for handling large-scale, dynamic, heterogeneous vehicular networks, since it offers flexibility, programmability, scalability, and a global understanding. However, the integration with VANETs introduces additional security vulnerabilities due to the deployment of a logically centralized control mechanism. These security attacks are classified as internal and external based on the nature of the attacker. The method adopted in this work facilitated the detection of internal position falsification attacks. Objective: This study aimed to investigate the performance of k-NN, SVM, Naïve Bayes, Logistic Regression, and Random Forest machine learning (ML) algorithms in detecting position falsification attacks using the Vehicular Reference Misbehavior (VeReMi) dataset. It also aimed to conduct a comparative analysis of two ensemble classification models, namely voting and stacking for final decision-making. These ensemble classification methods used the ML algorithms cooperatively to achieve improved classification. Methods: The simulations and evaluations were conducted using the Python programming language. VeReMi dataset was selected since it was an application-specific dataset for VANETs environment. Performance evaluation metrics, such as accuracy, precision, recall, F-measure, and prediction time were also used in the comparative studies. Results: This experimental study showed that Random Forest ML algorithm provided the best performance in detecting attacks among the ML algorithms. Voting and stacking were both used to enhance classification accuracy and reduce time required to identify an attack through predictions generated by k-NN, SVM, Naïve Bayes, Logistic Regression, and Random Forest classifiers. Conclusion: In terms of attack detection accuracy, both methods (voting and stacking) achieved the same level of accuracy as Random Forest. However, the detection of attack using stacking could be achieved in roughly less than half the time required by voting ensemble. Keywords: Machine learning methods, Majority voting ensemble, SDN-based VANETs, Security attacks, Stacking ensemble classifiers, VANETs