Non-GAAP Tax Rate: Do Managers Use It to Achieve Earnings Targets?

In this study, we examine tax reporting in a non-GAAP setting. We focus on non-GAAP tax rates, which we define as the tax rates applied to non-GAAP exclusions (hereafter, exclusions). Using detailed hand-collected data, we find that non-GAAP tax rates are systematically lower (higher) when exclusions are income-increasing (income-decreasing), leading to higher after-tax non-GAAP earnings. In addition, using GAAP effective tax rate (hereafter, GAAP ETR) and the statutory tax rate as proxies for the non-discretionary portion of the non-GAAP tax rate, we find robust evidence that managers opportunistically use non-GAAP tax rates to achieve after-tax non-GAAP earnings targets. Finally, we document that firm-reported after-tax non-GAAP earnings are less persistent for future GAAP earnings, compared to non-GAAP earnings calculated using GAAP ETR or the statutory tax rate. The lower persistence of firm-reported non-GAAP earnings implies that non-GAAP tax rates are sometimes too high or too low, thus contaminating the after-tax non-GAAP earnings with mostly transitory exclusion items

Quantum Criticality from in-situ Density Imaging

We perform large-scale Quantum Monte Carlo (QMC) simulations for strongly interacting bosons in a 2D optical lattice trap, and confirm an excellent agreement with the benchmarking in-situ density measurements by the Chicago group [1]. We further present a general finite temperature phase diagram both for the uniform and the trapped systems, and demonstrate how the universal scaling properties near the superfluid(SF)-to-Mott insulator(MI) transition can be observed by analysing the in-situ density profile. The characteristic temperature to find such quantum criticality is estimated to be of the order of the single-particle bandwidth, which should be achievable in the present or near future experiments. Finally, we examine the validity regime of the local fluctuation-dissipation theorem (FDT), which can be a used as a thermometry in the strongly interacting regime.Comment: 4 page

Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers

For machine learning with tabular data, Table Transformer (TabTransformer) is a state-of-the-art neural network model, while Differential Privacy (DP) is an essential component to ensure data privacy. In this paper, we explore the benefits of combining these two aspects together in the scenario of transfer learning -- differentially private pre-training and fine-tuning of TabTransformers with a variety of parameter-efficient fine-tuning (PEFT) methods, including Adapter, LoRA, and Prompt Tuning. Our extensive experiments on the ACSIncome dataset show that these PEFT methods outperform traditional approaches in terms of the accuracy of the downstream task and the number of trainable parameters, thus achieving an improved trade-off among parameter efficiency, privacy, and accuracy. Our code is available at github.com/IBM/DP-TabTransformer.Comment: submitted to ICASSP 202

Corporate Diversification And Firm Performance Impact On Chief Executive Officers Salary

The purpose of this research is to examine CEO salary and to explore whether the independent variables (international diversification, industrial diversification, market-based performance, accounting-based performance) are associated with CEO salary. Corporate diversification in this study is divided into international diversification and industrial diversification. Data for the study was obtained from annual reports of CEO salary on the ExecuComp database. Compensation data collected from the annual reports encompassed 2,448 CEOs from 1,622 firms. The dependent variable was developed from a review of CEO salary and accounting literature. The hypothesized predictors of CEO salary were identified through a review of existing studies. The results show that the higher the degree of international diversification and/or industrial diversification, the more CEOs receive in fixed salary. In addition, this study found that CEO salary is a better predictor of accounting performance than stock return performance

Why Focal Firms Share Information? A Study of the Effects of Power and Information Technology Competence

Supply chain management has become an important issue for Taiwan\u27s manufacturing industry due to escalating global competition. Virtual vertical integration is an important issue in supply chain management. Because organizations only have limited resources, they pursue long-term partnership with specific transaction partners. They share information to improve visibility, speed responses to markets, and reduce costs from information distortion or information asymmetry. This study empirically explores the factors affecting inter-organizational information sharing from the perspective of focal firms. 1,000 questionnaires were administered to top 1,000 manufacturing companies in Taiwan, with 139 valid responses. The results show that partner\u27s power and relation-specific asset investments positively affect inter-organizational information sharing. On the other hand, the partner\u27s power does not significantly affect the organization\u27s relation-specific investments. This study further investigates the moderating role of information technology competence. The result indicates that when an organization has lower information technology competence, the relationship between the partner\u27s power and relation-specific investments is significant. Implications and discussion are then provided

Astrocytic LRP1 mediates brain Aβ clearance and impacts amyloid deposition

Accumulation and deposition of amyloid-β (Aβ) in the brain represent an early and perhaps necessary step in the pathogenesis of Alzheimer's disease (AD). Aβ accumulation leads to the formation of Aβ aggregates, which may directly and indirectly lead to eventual neurodegeneration. While Aβ production is accelerated in many familial forms of early-onset AD, increasing evidence indicates that impaired clearance of Aβ is more evident in late-onset AD. To uncover the mechanisms underlying impaired Aβ clearance in AD, we examined the role of low-density lipoprotein receptor-related protein 1 (LRP1) in astrocytes. Although LRP1 has been shown to play critical roles in brain Aβ metabolism in neurons and vascular mural cells, its role in astrocytes, the most abundant cell type in the brain responsible for maintaining neuronal homeostasis, remains unclear. Here, we show that astrocytic LRP1 plays a critical role in brain Aβ clearance. LRP1 knockdown in primary astrocytes resulted in decreased cellular Aβ uptake and degradation. In addition, silencing of LRP1 in astrocytes led to downregulation of several major Aβ-degrading enzymes, including matrix metalloproteases MMP2, MMP9, and insulin-degrading enzyme. More important, conditional knock-out of theLrp1gene in astrocytes in the background of APP/PS1 mice impaired brain Aβ clearance, exacerbated Aβ accumulation, and accelerated amyloid plaque deposition without affecting its production. Together, our results demonstrate that astrocytic LRP1 plays an important role in Aβ metabolism and that restoring LRP1 expression and function in the brain could be an effective strategy to facilitate Aβ clearance and counter amyloid pathology in AD.SIGNIFICANCE STATEMENTAstrocytes represent a major cell type regulating brain homeostasis; however, their roles in brain clearance of amyloid-β (Aβ) and underlying mechanism are not clear. In this study, we used both cellular models and conditional knock-out mouse models to address the role of a critical Aβ receptor, the low-density lipoprotein receptor-related protein 1 (LRP1) in astrocytes. We found that LRP1 in astrocytes plays a critical role in brain Aβ clearance by modulating several Aβ-degrading enzymes and cellular degradation pathways. Our results establish a critical role of astrocytic LRP1 in brain Aβ clearance and shed light on specific Aβ clearance pathways that may help to establish new targets for AD prevention and therapy.</jats:p

Phase and Amplitude Responses of Narrow-Band Optical Filter Measured by Microwave Network Analyzer

The phase and amplitude responses of a narrow-band optical filter are measured simultaneously using a microwave network analyzer. The measurement is based on an interferometric arrangement to split light into two paths and then combine them. In one of the two paths, a Mach-Zehnder modulator generates two tones without carrier and the narrow-band optical filter just passes through one of the tones. The temperature and environmental variations are removed by separated phase and amplitude averaging. The amplitude and phase responses of the optical filter are measured to the resolution and accuracy of the network analyzer

AIN-Based Action Selection Mechanism for Soccer Robot Systems

[[abstract]]Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure developed based on geometry approach will become a very complex task. In this paper, a novel action-select algorithm for soccer robots is proposed by using the concepts of artificial immune network (AIN). This AIN-based action-select provides an efficient and robust algorithm for robot role selection. Meanwhile, a reinforcement learning mechanism is applied in the proposed algorithm to enhance the response of the adaptive immune system. Simulation and experiment are carried out to verify the proposed AIN-based algorithm, and the results show that the proposed algorithm provides an efficient and applicable algorithm for mobile robots to play soccer game.[[incitationindex]]EI[[booktype]]電子版[[booktype]]紙