The ability of earnings management models to detect and predict public discovery of accounting-fraud

The purpose of this study is to analyze and compare: 1) the ability of competing aggregate accrual and frequency distribution models to detect extreme earnings management, i.e. accounting-fraud, and 2) the ability of a composite model to predict accounting-fraud using only prior period information. Studies have used various models to detect earnings management in circumstances in which, a priori, some management is likely to exist. Events with incentives to manage earnings analyzed include issuing securities, maintaining positive earnings or an upward earnings trend, increasing an earnings-based bonus, increasing subsidies during import relief investigations, or decreasing penalties during antitrust investigations. However, few studies have tested such models when there existed a virtual certainty about which firms managed earnings. Using the Securities and Exchange Commission\u27s (SEC) Accounting and Auditing Enforcement Releases (AAERs) to denote accounting-fraud firms, I establish a format of analysis in which relative certainty exists. Using that format, I test various aggregate accrual, frequency distribution, and composite earnings management models\u27 ability to distinguish between accounting fraud and non-accounting-fraud matched firms. Aggregate accrual model results show that total accruals, the simplest model, performs best in detecting accounting-fraud. Also, those models calculated from the statement of cash flows always outperforms those calculated from the balance sheet. Frequency distribution models show a surprising lack of ability to detect accounting-fraud. The power of the test is adversely affected by an apparent targeting bias for the SEC to investigate firms that miss earnings thresholds. As expected, the data intensive composite model shows the greatest ability to identify accounting-fraud firms from ex ante data. The composite model only uses prior period variables to represent financial condition of the firm, income-increasing accounting choices, and potentially opportunistic behavior to distinguish an accounting-fraud firm-year from a matched non-fraud firm-year. Significant variables include total accruals, sales growth, cash sales growth, a proxy for age of firm, inventory valuation method, straight-line depreciation, and merger/acquisition activity. Overall, aggregate accrual models calculated from the balance sheet and frequency distribution models appear to have minimal ability to detect extreme earnings management. Aggregate accrual models calculated from the statement of cash flows appear to be more useful to distinguish accounting-fraud firms, although they exhibit relatively low explanatory power. Composite model results represent a particularly useful contribution since only prior period information is used to predict future accounting-fraud firms. Additionally, the significance of certain variables representing managerial behavior and incentives provide strong insight for accountants and regulators concerning the prediction/detection of accounting-fraud

X-ray Lightcurves from Realistic Polar Cap Models: Inclined Pulsar Magnetospheres and Multipole Fields

Thermal X-ray emission from rotation-powered pulsars is believed to originate from localized "hotspots" on the stellar surface occurring where large-scale currents from the magnetosphere return to heat the atmosphere. Lightcurve modeling has primarily been limited to simple models, such as circular antipodal emitting regions with constant temperature. We calculate more realistic temperature distributions within the polar caps, taking advantage of recent advances in magnetospheric theory, and we consider their effect on the predicted lightcurves. The emitting regions are non-circular even for a pure dipole magnetic field, and the inclusion of an aligned magnetic quadrupole moment introduces a north-south asymmetry. As the aligned quadrupole moment is increased, one hotspot grows in size before becoming a thin ring surrounding the star. For the pure dipole case, moving to the more realistic model changes the lightcurves by $5-10\%$ for millisecond pulsars, helping to quantify the systematic uncertainty present in current dipolar models. Including the quadrupole gives considerable freedom in generating more complex lightcurves. We explore whether these simple dipole+quadrupole models can account for the qualitative features of the lightcurve of PSR J0437$-$4715.Comment: 12 pages, 9 figure

How narrow is the M87* ring? II. A new geometric model

The 2017 Event Horizon Telescope (EHT) observations of M87* detected a ring-shaped feature $\sim40\mu$as in diameter, consistent with the event horizon scale of a black hole of the expected mass. The thickness of this ring, however, proved difficult to measure, despite being an important parameter for constraining the observational appearance. In the first paper of this series we asked whether the width of the ring was sensitive to the choice of likelihood function used to compare observed closure phases and closure amplitudes to model predictions. In this paper we investigate whether the ring width is robust to changes in the model itself. We construct a more realistic geometric model with two new features: an adjustable radial falloff in brightness, and a secondary "photon ring" component in addition to the primary annulus. This thin, secondary ring is predicted by gravitational lensing for any black hole with an optically thin accretion flow. Analyzing the data using the new model, we find that the primary annulus remains narrow (fractional width $\leq0.25$) even with the added model freedom. This provides further evidence in favor of a narrow ring for the true sky appearance of M87*, a surprising feature that, if confirmed, would demand theoretical explanation. Comparing the Bayesian evidence for models with and without a secondary ring, we find no evidence for the presence of a lensed photon ring in the 2017 observations. However, the techniques we introduce may prove useful for future observations with a larger and more sensitive array

GDF15: A Hormone Conveying Somatic Distress to the Brain.

GDF15 has recently gained scientific and translational prominence with the discovery that its receptor is a GFRAL-RET heterodimer of which GFRAL is expressed solely in the hindbrain. Activation of this receptor results in reduced food intake and loss of body weight and is perceived and recalled by animals as aversive. This information encourages a revised interpretation of the large body of previous research on the protein. GDF15 can be secreted by a wide variety of cell types in response to a broad range of stressors. We propose that central sensing of GDF15 via GFRAL-RET activation results in behaviors that facilitate the reduction of exposure to a noxious stimulus. The human trophoblast appears to have hijacked this signal, producing large amounts of GDF15 from early pregnancy. We speculate that this encourages avoidance of potential teratogens in pregnancy. Circulating GDF15 levels are elevated in a range of human disease states, including various forms of cachexia, and GDF15-GFRAL antagonism is emerging as a therapeutic strategy for anorexia/cachexia syndromes. Metformin elevates circulating GDF15 chronically in humans and the weight loss caused by this drug appears to be dependent on the rise in GDF15. This supports the concept that chronic activation of the GDF15-GFRAL axis has efficacy as an antiobesity agent. In this review, we examine the science of GDF15 since its identification in 1997 with our interpretation of this body of work now being assisted by a clear understanding of its highly selective central site of action

Solving Common-Payoff Games with Approximate Policy Iteration

For artificially intelligent learning systems to have widespread applicability in real-world settings, it is important that they be able to operate decentrally. Unfortunately, decentralized control is difficult -- computing even an epsilon-optimal joint policy is a NEXP complete problem. Nevertheless, a recently rediscovered insight -- that a team of agents can coordinate via common knowledge -- has given rise to algorithms capable of finding optimal joint policies in small common-payoff games. The Bayesian action decoder (BAD) leverages this insight and deep reinforcement learning to scale to games as large as two-player Hanabi. However, the approximations it uses to do so prevent it from discovering optimal joint policies even in games small enough to brute force optimal solutions. This work proposes CAPI, a novel algorithm which, like BAD, combines common knowledge with deep reinforcement learning. However, unlike BAD, CAPI prioritizes the propensity to discover optimal joint policies over scalability. While this choice precludes CAPI from scaling to games as large as Hanabi, empirical results demonstrate that, on the games to which CAPI does scale, it is capable of discovering optimal joint policies even when other modern multi-agent reinforcement learning algorithms are unable to do so. Code is available at https://github.com/ssokota/capi .Comment: AAAI 202

Episodic memory function is associated with multiple measures of white matter integrity in cognitive aging

Previous neuroimaging research indicates that white matter injury and integrity, measured respectively by white matter hyperintensities (WMH) and fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI), differ with aging and cerebrovascular disease (CVD) and are associated with episodic memory deficits in cognitively normal older adults. However, knowledge about tract-specific relationships between WMH, FA, and episodic memory in aging remains limited. We hypothesized that white matter connections between frontal cortex and subcortical structures as well as connections between frontal and temporo-parietal cortex would be most affected. In the current study, we examined relationships between WMH, FA and episodic memory in 15 young adults, 13 elders with minimal WMH and 15 elders with extensive WMH, using an episodic recognition memory test for object-color associations. Voxel-based statistics were used to identify voxel clusters where white matter measures were specifically associated with variations in episodic memory performance, and white matter tracts intersecting these clusters were analyzed to examine white matter-memory relationships. White matter injury and integrity measures were significantly associated with episodic memory in extensive regions of white matter, located predominantly in frontal, parietal, and subcortical regions. Template based tractography indicated that white matter injury, as measured by WMH, in the uncinate and inferior longitudinal fasciculi were significantly negatively associated with episodic memory performance. Other tracts such as thalamo-frontal projections, superior longitudinal fasciculus, and dorsal cingulum bundle demonstrated strong negative associations as well. The results suggest that white matter injury to multiple pathways, including connections of frontal and temporal cortex and frontal-subcortical white matter tracts, plays a critical role in memory differences seen in older individuals

The Thread of Ariadne: A Collection of Essays by the Faculty of the Cooperative Research Center in the Humanities Dominican College of San Rafael

This volume is a Festschrift with a difference: a collection of essays written by colleagues to honor students -- past, present, future -- rather than an aged academic kindred spirit. the end-product of a \u27Great Conversation\u27 which extended over two years (1985-1987), the volume contains ten essays by nine Dominican College faculty members. Each essay has been developed in the context of inter-disciplinary discussions to which specialists in art history, history, literature, and philosophy contributed their knowledge and insights. Lest that statement suggest placid armchair soliloquies. let me quickly add that the discussions were frank and vigorous, and served to focus, refine, and sometimes change altogether the final topics of the essays. ~ from the Introduction by Sister M. Samuel Conlan, O.P.https://scholar.dominican.edu/books/1097/thumbnail.jp

Insulin Resistance in Vascular Endothelial Cells Promotes Intestinal Tumor Formation

The risk of several cancers, including colorectal cancer, is increased in patients with obesity and type 2 diabetes, conditions characterized by hyperinsulinemia and insulin resistance. Because hyperinsulinemia itself is an independent risk factor for cancer development, we examined tissue-specific insulin action in intestinal tumor formation. In vitro, insulin increased proliferation of primary cultures of intestinal tumor epithelial cells from ApcMin/+ mice by over 2-fold. Surprisingly, targeted deletion of insulin receptors in intestinal epithelial cells in ApcMin/+ mice did not change intestinal tumor number or size distribution on either a low or high-fat diet. We therefore asked whether cells in the tumor stroma might explain the association between tumor formation and insulin resistance. To this end, we generated ApcMin/+ mice with loss of insulin receptors in vascular endothelial cells. Strikingly, these mice had 42% more intestinal tumors than controls, no change in tumor angiogenesis, but increased expression of vascular cell adhesion molecule-1 (VCAM-1) in primary culture of tumor endothelial cells. Insulin decreased VCAM-1 expression and leukocyte adhesion in quiescent tumor endothelial cells with intact insulin receptors and partly prevented increases in VCAM-1 and leukocyte adhesion after treatment with tumor necrosis factor-α. Knockout of insulin receptors in endothelial cells also increased leukocyte adhesion in mesenteric venules and increased the frequency of neutrophils in tumors. We conclude that although insulin is mitogenic for intestinal tumor cells in vitro, its action on tumor cells in vivo is via signals from the tumor microenvironment. Insulin resistance in tumor endothelial cells produces an activated, proinflammatory state that promotes tumorigenesis. Improvement of endothelial dysfunction may reduce colorectal cancer risk in patients with obesity and type 2 diabetes