An explanation for earnings management : opportunistic or signaling?

In a two-period and two-type framework, the market does not know a firm’s economic earnings creation ability, which could be high or low, but infers it by observing the firm’s accounting earnings. The firm liquidates some of its shares in the first period, and the rest in the second period. This paper provides a reason that a manager, no matter the firm’s type, may transfer some earnings from the second period and report high accounting earnings in the first period, ifthe first period’s economic income is low, because such action could have positive effects on the firm’s market value. We further argue that smoothing earnings is a signaling strategy for a high type firm, but an opportunistic behavior for a low type firm. In addition, we point out that the higher the liquidation needs in the first period, or the less information about the firm’s type the market has, then he more aggressive the manager may engage in earnings smoothing

Online delay-guaranteed workload scheduling to minimize power cost in cloud data centers using renewable energy

More and more cloud data centers are turning to leverage on-site renewable energy to reduce power cost for sustainable development. But how to effectively coordinate the intermittent renewable energy with workload remains to be a great challenge. This paper investigates the problem of workload scheduling for power cost minimization under the constraints of different Service Level Agreements (SLAs) of delay tolerant workload and delay sensitive workload for green data centers in a smart grid. Different from the existing studies, we take into consideration of the impact of zero price in the smart grid and the cost of on-site renewable energy. To handle the randomness of workload, electricity price and renewable energy availability, we first formulate the problem as a constrained stochastic problem. Then we propose an efficient online control algorithm named ODGWS (Online Delay-Guaranteed Workload Scheduling) which makes online scheduling decisions achieve a bounded guarantee from the worst scheduling delay for delay tolerant workload. Compared with the existing solutions, our ODGWS decomposes the problem into that of solving a simple optimization problem within each time slot in O(1) time without needing any future information. The rigorous theoretical analysis demonstrates that our algorithm achieves a [O([Formula presented]),O(V)] cost-delay tradeoff, where V is a balance parameter between the cost optimality and service quality. Extensive simulations based on real-world traces are done to evaluate the performance of our algorithm. The results show that ODGWS saves about 5% average power cost compared with the baseline algorithms

Online delay-guaranteed workload scheduling to minimize power cost in cloud data centers using renewable energy

More and more cloud data centers are turning to leverage on-site renewable energy to reduce power cost for sustainable development. But how to effectively coordinate the intermittent renewable energy with workload remains to be a great challenge. This paper investigates the problem of workload scheduling for power cost minimization under the constraints of different Service Level Agreements (SLAs) of delay tolerant workload and delay sensitive workload for green data centers in a smart grid. Different from the existing studies, we take into consideration of the impact of zero price in the smart grid and the cost of on-site renewable energy. To handle the randomness of workload, electricity price and renewable energy availability, we first formulate the problem as a constrained stochastic problem. Then we propose an efficient online control algorithm named ODGWS (Online Delay-Guaranteed Workload Scheduling) which makes online scheduling decisions achieve a bounded guarantee from the worst scheduling delay for delay tolerant workload. Compared with the existing solutions, our ODGWS decomposes the problem into that of solving a simple optimization problem within each time slot in O(1) time without needing any future information. The rigorous theoretical analysis demonstrates that our algorithm achieves a [O([Formula presented]),O(V)] cost-delay tradeoff, where V is a balance parameter between the cost optimality and service quality. Extensive simulations based on real-world traces are done to evaluate the performance of our algorithm. The results show that ODGWS saves about 5% average power cost compared with the baseline algorithms

Material Wear Calculation of Braking Surface under High-Power Braking Conditions

The wear phenomenon of the braking surface of a high-power disc brake under emergency braking conditions is analyzed in this paper. Considering the classical Archard wear model, including the influence of the braking load, speed, and friction coefficient on the braking surface, the wear model of the brake disc surface is established to obtain the wear depth and distribution. It is essential to investigate the wear mechanism of the brake disc surface, and the evolution of wear laws is revealed under different braking parameters. The results have shown that the brake disc surface wear is constantly accumulating. The large load, the high speed, and the large friction coefficient would aggravate the surface wear area. It is expected that the wear study of the brake disc surface can guide the design of the disc brake

Catalytic reduction of nitrogen to produce ammonia by bismuth-based catalysts: State of the art and future prospects

This review provides an up-to-date review on Bi-based nitrogen-fixation materials and future directions for the development of new Bi-based nitrogen-fixation materials under ambient conditions.</p