Earnings Management and Measurement Error

In this paper I consider the impact of a noisy indicator regarding a manager’s manipulative behavior on optimal effort incentives and the extent of earnings management. The analysis in this paper extends a twotask, single performance measure LEN model by including a binary random variable. I show that contracting on the noisy indicator variable is not always useful. More specifically, the principal uses the indicator variable to prevent earnings management only under conditions where manipulative behavior is not excessive. Thus, under conditions of excessive earnings management, accounting adjustments that yield a more congruent overall performance measure can be more effective than an appraisal of the existence of earnings management to mitigate the earnings management problem.

A Cooperative and Adaptive Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.

Hating the neighbors: The role of hate crime in the perpetuation of black residential segregation

Grounded in group conflict theory and the defended neighborhoods thesis, this nationwide empirical study of cities and their residential segregation levels, examines the occurrence of hate crime using data on for all U.S. cities with populations over 95,000, and data compiled from the Uniform Crime Report for hate crime, in conjunction with 2000 census data. Hate crime is any illegal act motivated by pre-formed bias against, in this case, a person’s real or perceived race. This research asks: Do hate crime levels predict white/black segregation levels? How does hate crime predict different measures of white/black segregation? I use the dissimilarity index measure of segregation operationalized as a continuous, binary and ordinal variable, to explore whether hate crime predicts segregation of blacks from whites. In cities with higher rates of hate crime there was higher dissimilarity between whites and blacks, controlling for other factors. The segregation level was more likely to be “high” in a city where hate crime occurred. Blacks are continually multiply disadvantaged and distinctly affected by hate crime and residential segregation. Prior studies of residential segregation have focused almost exclusively on individual choice, residents’ lack of finances, or discriminatory actions that prevent racial minorities from moving, to explore the correlates of segregation. Notably absent from these studies are measures reflecting the level of hate crime occurring in cities. This study demonstrates the importance of considering hate crime and neighborhood conflict when contemplating the causes of residential segregation.

Expression Analysis of the Theileria parva Subtelomere-Encoded Variable Secreted Protein Gene Family

Background The intracellular protozoan parasite Theileria parva transforms bovine lymphocytes inducing uncontrolled proliferation. Proteins released from the parasite are assumed to contribute to phenotypic changes of the host cell and parasite persistence. With 85 members, genes encoding subtelomeric variable secreted proteins (SVSPs) form the largest gene family in T. parva. The majority of SVSPs contain predicted signal peptides, suggesting secretion into the host cell cytoplasm. Methodology/Principal Findings We analysed SVSP expression in T. parva-transformed cell lines established in vitro by infection of T or B lymphocytes with cloned T. parva parasites. Microarray and quantitative real-time PCR analysis revealed mRNA expression for a wide range of SVSP genes. The pattern of mRNA expression was largely defined by the parasite genotype and not by host background or cell type, and found to be relatively stable in vitro over a period of two months. Interestingly, immunofluorescence analysis carried out on cell lines established from a cloned parasite showed that expression of a single SVSP encoded by TP03_0882 is limited to only a small percentage of parasites. Epitope-tagged TP03_0882 expressed in mammalian cells was found to translocate into the nucleus, a process that could be attributed to two different nuclear localisation signals. Conclusions Our analysis reveals a complex pattern of Theileria SVSP mRNA expression, which depends on the parasite genotype. Whereas in cell lines established from a cloned parasite transcripts can be found corresponding to a wide range of SVSP genes, only a minority of parasites appear to express a particular SVSP protein. The fact that a number of SVSPs contain functional nuclear localisation signals suggests that proteins released from the parasite could contribute to phenotypic changes of the host cell. This initial characterisation will facilitate future studies on the regulation of SVSP gene expression and the potential biological role of these enigmatic proteins.

Splitting of a prevalent Mycobacterium bovis spoligotype by variable-number tandem-repeat typing reveals high heterogeneity in an evolving clonal group

Mycobacterium bovis populations in countries with persistent bovine tuberculosis usually show a prevalent spoligotype with a wide geographical distribution. This study applied mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing to a random panel of 115 M. bovis isolates that are representative of the most frequent spoligotype in the Iberian Peninsula, SB0121. VNTR typing targeted nine loci: ETR-A (alias VNTR2165), ETR-B (VNTR2461), ETR-D (MIRU4, VNTR580), ETR-E (MIRU31, VNTR3192), MIRU26 (VNTR2996), QUB11a (VNTR2163a), QUB11b (VNTR2163b), QUB26 (VNTR4052), and QUB3232 (VNTR3232). We found a high degree of diversity among the studied isolates (discriminatory index [D] = 0.9856), which were split into 65 different MIRU-VNTR types. An alternative short-format MIRU-VNTR typing targeting only the four loci with the highest variability values was found to offer an equivalent discriminatory index. Minimum spanning trees using the MIRU-VNTR data showed the hypothetical evolution of an apparent clonal group. MIRU-VNTR analysis was also applied to the isolates of 176 animals from 15 farms infected by M. bovis SB0121; in 10 farms, the analysis revealed the coexistence of two to five different MIRU types differing in one to six loci, which highlights the frequency of undetected heterogeneity.

A test of genetic association among male nuptial coloration, female mating preference, and male aggression bias within a polymorphic population of cichlid fish

Both inter- and intrasexual selection have been implicated in the origin and maintenance of species-rich taxa with diverse sexual traits. Simultaneous disruptive selection by female mate choice and male-male competition can, in theory, lead to speciation without geographical isolation if both act on the same male trait. Female mate choice can generate discontinuities in gene flow, while male-male competition can generate negative frequency-dependent selection stabilizing the male trait polymorphism. Speciation may be facilitated when mating preference and/or aggression bias are physically linked to the trait they operate on. We tested for genetic associations among female mating preference, male aggression bias and male coloration in the Lake Victoria cichlid Pundamilia. We crossed females from a phenotypically variable population with males from both extreme ends of the phenotype distribution in the same population (blue or red). Male offspring of a red sire were significantly redder than males of a blue sire, indicating that intra-population variation in male coloration is heritable. We tested mating preferences of female offspring and aggression biases of male offspring using binary choice tests. There was no evidence for associations at the family level between female mating preferences and coloration of sires, but dam identity had a significant effect on female mate preference. Sons of the red sire directed significantly more aggression to red than blue males, whereas sons of the blue sire did not show any bias. There was a positive correlation among individuals between male aggression bias and body coloration, possibly due to pleiotropy or physical linkage, which could facilitate the maintenance of color polymorphism.

Crystal chemistry and hydrogen bonding of rustumite Ca10(Si2O7)2(SiO4)(OH)2Cl2 with variable OH, Cl, F

Three samples of the skarn mineral rustumite Ca10(Si2O7)2(SiO4)(OH)2Cl2, space group C2/c, a ≈7.6, b ≈ 18.5, c ≈ 15.5 Å, β ≈ 104°, with variable OH, Cl, F content were investigated by electron microprobe, single-crystal X-ray structure refinements, and Raman spectroscopy. “Rust1LCl” is a low chlorine rustumite Ca10(Si2O7)2(SiO4)(OH1.88F0.12)(Cl1.28,OH0.72) from skarns associated with the Rize batholith near Ikizedere, Turkey. “Rust2F” is a F-bearing rustumite Ca10(Si2O7)2(SiO4)(OH1.13F0.87) (Cl1 96OH0.04) from xenoliths in ignimbrites of the Upper Chegem Caldera, Northern Caucasus, Russia. “Rust3LClF” represents a low-Cl, F-bearing rustumite Ca10(Si2O7)2(SiO4)0.87(H4O4)0.13(OH1.01F0.99) (Cl1.00 OH1.00) from altered merwinite skarns of the Birkhin massif, Baikal Lake area, Eastern Siberia, Russia. Rustumite from Birkhin massif is characterized by a significant hydrogarnet-like or fluorine substitution at the apices of the orthosilicate group, leading to specific atomic displacements. The crystal structures including hydrogen positions have been refined from single-crystal X-ray data to R1 = 0.0205 (Rust1_LCl), R1 = 0.0295 (Rust2_F), and R1 = 0.0243 (Rust3_LCl_F), respectively. Depletion in Cl and replacement by OH is associated with smaller unit-cell dimensions. The substitution of OH by F leads to shorter hydrogen bonds O-H⋯F instead of O-H⋯OH. Raman spectra for all samples have been measured and confirm slight strengthening of the hydrogen bonds with uptake of F.This study discusses the complex crystal chemistry of the skarn mineral rustumite and may provide a wider understanding of the chemical reactions related to contact metamorphism of limestones.

Time-variable gravity signal in Greenland revealed by high-low satellite-to-satellite tracking

[1] In the event of a termination of the Gravity Recovery and Climate Experiment (GRACE) mission before the launch of GRACE Follow-On (due for launch in 2017), high-low satellite-to-satellite tracking (hl-SST) will be the only dedicated observing system with global coverage available to measure the time-variable gravity field (TVG) on a monthly or even shorter time scale. Until recently, hl-SST TVG observations were of poor quality and hardly improved the performance of Satellite Laser Ranging observations. To date, they have been of only very limited usefulness to geophysical or environmental investigations. In this paper, we apply a thorough reprocessing strategy and a dedicated Kalman filter to Challenging Minisatellite Payload (CHAMP) data to demonstrate that it is possible to derive the very long-wavelength TVG features down to spatial scales of approximately 2000 km at the annual frequency and for multi-year trends. The results are validated against GRACE data and surface height changes from long-term GPS ground stations in Greenland. We find that the quality of the CHAMP solutions is sufficient to derive long-term trends and annual amplitudes of mass change over Greenland. We conclude that hl-SST is a viable source of information for TVG and can serve to some extent to bridge a possible gap between the end-of-life of GRACE and the availability of GRACE Follow-On.

An examination of the Gonorrhea Cases & Places Study: An analysis of the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory as it relates to risky sexual behavior in African American adults

Objective. The purpose of the study is to provide a holistic depiction of behavioral & environmental factors contributing to risky sexual behaviors among predominantly high school educated, low-income African Americans residing in urban areas of Houston, TX utilizing the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory. Methods. A cross-sectional study was conducted via questionnaires among 215 Houston area residents, 149 were women and 66 were male. Measures used to assess behaviors of the population included a history of homelessness, use of crack/cocaine among several other illicit drugs, the type of sexual partner, age of participant, age of most recent sex partner, whether or not participants sought health care in the last 12 months, knowledge of partner's other sexual activities, symptoms of depression, and places where partner's were met. In an effort to determine risk of sexual encounters, a risk index employing the variables used to assess condom use was created categorizing sexual encounters as unsafe or safe. Results. Variables meeting the significance level of p<.15 for the bivariate analysis of each theory were entered into a binary logistic regression analysis. The block for each theory was significant, suggesting that the grouping assignments of each variable by theory were significantly associated with unsafe sexual behaviors. Within the regression analysis, variables such as sex for drugs/money, low income, and crack use demonstrated an effect size of ≥ ± 1, indicating that these variables had a significant effect on unsafe sexual behavioral practices. Conclusions. Variables assessing behavior and environment demonstrated a significant effect when categorized by relation to designated theories.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

Transcriptional regulation of the Borrelia burgdorferi antigenically variable VlsE surface protein.

The Lyme disease agent Borrelia burgdorferi can persistently infect humans and other animals despite host active immune responses. This is facilitated, in part, by the vls locus, a complex system consisting of the vlsE expression site and an adjacent set of 11 to 15 silent vls cassettes. Segments of nonexpressed cassettes recombine with the vlsE region during infection of mammalian hosts, resulting in combinatorial antigenic variation of the VlsE outer surface protein. We now demonstrate that synthesis of VlsE is regulated during the natural mammal-tick infectious cycle, being activated in mammals but repressed during tick colonization. Examination of cultured B. burgdorferi cells indicated that the spirochete controls vlsE transcription levels in response to environmental cues. Analysis of PvlsE::gfp fusions in B. burgdorferi indicated that VlsE production is controlled at the level of transcriptional initiation, and regions of 5' DNA involved in the regulation were identified. Electrophoretic mobility shift assays detected qualitative and quantitative changes in patterns of protein-DNA complexes formed between the vlsE promoter and cytoplasmic proteins, suggesting the involvement of DNA-binding proteins in the regulation of vlsE, with at least one protein acting as a transcriptional activator.

Effects of variable Gs expression on $\beta\sb2$-adrenergic receptor stimulated adenylyl cyclase response

An exact knowledge of the kinetic nature of the interaction between the stimulatory G protein (G$\sb{\rm s}$) and the adenylyl cyclase catalytic unit (C) is essential for interpreting the effects of Gs mutations and expression levels on cellular response to a wide variety of hormones, drugs, and neurotransmitters. In particular, insight as to the association of these proteins could lead to progress in tumor biology where single spontaneous mutations in G proteins have been associated with the formation of tumors (118). The question this work attempts to answer is whether the adenylyl cyclase activation by epinephrine stimulated $\beta\sb2$-adrenergic receptors occurs via G$\sb{\rm s}$ proteins by a G$\sb{\rm s}$ to C shuttle or G$\sb{\rm s}$-C precoupled mechanism. The two forms of activation are distinguishable by the effect of G$\sb{\rm s}$ levels on epinephrine stimulated EC50 values for cyclase activation.^ We have made stable transfectants of S49 cyc$\sp-$ cells with the gene for the $\alpha$ protein of G$\sb{\rm s}$ $(\alpha\sb{\rm s})$ which is under the control of the mouse mammary tumor virus LTR promoter (110). Expression of G$\sb{\rm s}\alpha$ was then controlled by incubation of the cells for various times with 5 $\mu$M dexamethasone. Expression of G$\sb{\rm s}\alpha$ led to the appearance of GTP shifts in the competitive binding of epinephrine with $\sp{125}$ICYP to the $\beta$-adrenergic receptors and to agonist dependent adenylyl cyclase activity. High expression of G$\sb{\rm s}\alpha$ resulted in lower EC50's for the adenylyl cyclase activity in response to epinephrine than did low expression. By kinetic modelling, this result is consistent with the existence of a shuttle mechanism for adenylyl cyclase activation by hormones.^ One item of concern that remains to be addressed is the extent to which activation of adenylyl cyclase occurs by a "pure" shuttle mechanism. Kinetic and biochemical experiments by other investigators have revealed that adenylyl cyclase activation, by hormones, may occur via a Gs-C precoupled mechanism (80, 94, 97). Activation of adenylyl cyclase, therefore, probably does not occur by either a pure "'Shuttle" or "Gs-C Precoupled" mechanism, but rather by a "Hybrid" mechanism. The extent to which either the shuttle or precoupled mechanism contributes to hormone stimulated adenylyl cyclase activity is the subject of on-going research. ^

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^