PRICE DISCRIMINATION IN A FORM OF DISCOUNTS: CATEGORIZATION AND IMPACT ON COMPETITION

This paper is aimed to clarify the definition and categorization of discounts as well as pro- and anticompetitive effects of discounts. The author applied qualitative methods to the research. The modern literature review unfolds the gap of proper discounts definition, which is proposed to be covered by five-dimensions approach to discounts categorization. Based on such aspects of discount scheme as time, product, threshold, distribution level and customer, the approach provides comprehensive and uniform characteristics of discount. It allows assessing effects of competition, which are classified in two groups. Pro-competitive effects include stimulation of demand, decreasing cost due to economy of scale, solving coordination problems within a supply chain. Anti-competitive effects encompass predation scheme, raising rival’s cost, exclusive dealing, leverage and exclusionary bundling. The importance of correct assessment of the discounts by antitrust authorities is high as an overenforcement in this sphere may lead to adverse effect on total welfare.

Enough is too much: the excessiveness objection to sufficientarianism

The standard version of sufficientarianism maintains that providing people with enough, or as close to enough as is possible, is lexically prior to other distributive goals. This article argues that this is excessive – more than distributive justice allows – in four distinct ways. These concern the magnitude of advantage, the number of beneficiaries, responsibility and desert, and above-threshold distribution. Sufficientarians can respond by accepting that providing enough unconditionally is more than distributive justice allows, instead balancing sufficiency against other considerations.

Decentralized Swarm Desynchronization via Inter-agent Variation for Logistical Resupply

Decentralized computational swarms have been used to simulate the workings of insect colonies or hives, often utilizing a response threshold model which underlies agent interaction with dynamic environmental stimuli. Here, we propose a logistics resupply problem in which agents must select from multiple incoming scheduled tasks that generate competing resource demands for workers. This work diverges from previous attempts toward analyzing swarm behaviors by examining relative amounts of stress placed on a multi-agent system in conjunction with two mechanisms of response: variable threshold distribution, or duration level. Further, we demonstrate changes to the general swarm performance’s dependence on paired desynchronization type and schedule design, as the result of varied swarm conditions.

The Design, Simulation and Fabrication of an Omnidirectional Inertial Switch with Rectangular Suspension Spring

An omnidirectional inertial switch with rectangular spring is proposed in this paper, and the prototype has been fabricated by surface micromachining technology. To evaluate the threshold consistency and stability of omnidirectional inertia switch, the stiffness of rectangular suspension springs is analyzed. The simulation result shows that the coupling stiffness of the rectangular spring suspension system in the non-sensitive direction is a little more than that in the sensitive direction, which indicated that the omnidirectional switching system’s stability is reinforced, attributed to the design of rectangular springs. The dynamic response simulation shows that the threshold of the omnidirectional inertial switch using the rectangular suspension spring has high consistency in the horizontal direction. The prototype of an inertial switch is fabricated and tested successfully. The testing results indicate even threshold distribution in the horizontal direction. The threshold acceleration of the designed inertial switch is about 58 g in the X direction and 37 g in the Z direction; the contact time is about 18 μs.

Research on influence mechanism of running clothing fatigue based on BP neural network

Dress fatigue can affect the efficiency of sports, especially for running, the dress fatigue has a greater impact on it. Moreover, at present, there are few studies on dress fatigue. Based on this, this study is based on BP neural network, and uses surface electromyography theory and muscle fatigue measurement method to perform fatigue measurement. The fatigue threshold analysis is mainly carried out by the experimental method, and the prediction model of the wearing fatigue threshold based on BP neural network is constructed based on the actual demand. Moreover, this paper verifies the reliability of threshold distribution by experimental analysis combined with model analysis. In addition, the study sets the organizational structure and clothing pressure as verification indicators to analyze the performance of the model. The research results show that the model constructed in this study can effectively analyze the mechanism of fatigue impact of running dress, and this paper can provide reference for the study of dress fatigue.

Failure probability assessment of landslides triggered by earthquakes and rainfall: a case study in Yadong County, Tibet, China

Yadong County located in the southern Himalayan mountains in Tibet, China, is an import frontier county. It was affected by landslides after the 2011 Sikkim earthquake (Mw = 6.8) and the 2015 Gorkha earthquake (Mw = 7.8). Casualties and property damage were caused by shallow landslides during subsequent rainfall on the earthquake-destabilized slopes. Existing researches have generally examined rainfall- and earthquake-triggered landslides independently, whereas few studies have considered the combined effects of both. Furthermore, there is no previous study reported on landslide hazards in the study area, although the area is strategically applicable for trade as it is close to Bhutan and India. This study developed a new approach that coupled the Newmark method with the hydrological model based on geomorphological, geological, geotechnical, seismological and rainfall data. A rainfall threshold distribution map was generated, indicating that the southeast part of Yadong is prone to rainfall-induced landslides, especially when daily rainfall is higher than 45 mm/day. Permanent displacement predictions were used to identify landslide hazard zones. The regression model used to calculate these permanent displacement values was 71% accurate. Finally, landslide probability distribution maps were generated separately for dry and wet conditions with rainfall of varying intensities. Results can serve as a basis for local governments to manage seismic landslide risks during rainy seasons.

Diffusion/Contagion Processes on Social Networks

This study models how new ideas, practices, or diseases spread within and between communities, the diffusion of innovations or contagion. Several factors affect diffusion such as the characteristics of the initial adopters, the seeds; the structure of the network over which diffusion occurs; and the shape of the threshold distribution, which is the proportion of prior adopting peers needed for the focal individual to adopt. In this study, seven seeding conditions are modeled: (1) three opinion leadership indicators, (2) two bridging measures, (3) marginally positioned seeds, and (4) randomly selected seeds for comparison. Three network structures are modeled: (1) random, (2) small-world, and (3) scale-free. Four threshold distributions are modeled: (1) normal; (2) uniform; (3) beta 7,14; and (4) beta 1,2; all of which have a mean threshold of 33%, with different variances. The results show that seeding with nodes high on in-degree centrality and/or inverse constraint has faster and more widespread diffusion. Random networks had faster and higher prevalence of diffusion than scale-free ones, but not different from small-world ones. Compared with the normal threshold distribution, the uniform one had faster diffusion and the beta 7,14 distribution had slower diffusion. Most significantly, the threshold distribution standard deviation was associated with rate and prevalence such that higher threshold standard deviations accelerated diffusion and increased prevalence. These results underscore factors that health educators and public health advocates should consider when developing interventions or trying to understand the potential for behavior change.

Threshold Stochastic Conditional Duration Model for Financial Transaction Data

This paper proposes a variant of a threshold stochastic conditional duration (TSCD) model for financial data at the transaction level. It assumes that the innovations of the duration process follow a threshold distribution with a positive support. In addition, it also assumes that the latent first-order autoregressive process of the log conditional durations switches between two regimes. The regimes are determined by the levels of the observed durations and the TSCD model is specified to be self-excited. A novel Markov-Chain Monte Carlo method (MCMC) is developed for parameter estimation of the model. For model discrimination, we employ deviance information criteria, which does not depend on the number of model parameters directly. Duration forecasting is constructed by using an auxiliary particle filter based on the fitted models. Simulation studies demonstrate that the proposed TSCD model and MCMC method work well in terms of parameter estimation and duration forecasting. Lastly, the proposed model and method are applied to two classic data sets that have been studied in the literature, namely IBM and Boeing transaction data.