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This paper presents a mathematical model for a cognitive communication network applicable to satellite communications with ground stations. The model employs abstract elements to describe a communications network, allowing the approach to be applied to a wide range of real-world communications systems and problems. The model includes representation of communications paths, spacecraft capabilities, time-varying demand for data transfer, changes in visibility due to satellite motion, time-varying availability of channels, and regulatory constraints on the use of radio communication bands. These model elements permit the detailed description of the structure and constraints of a communications problem. The model establishes a formal definition for a communication schedule which assigns communications resources to specific communicators at specific times. The model also formalizes constraints on the interactions between communicators, establishing the definition of a valid schedule in which communications conflicts do not occur and the definition of a good schedule in which communications resources are used efficiently. The paper also presents a dynamic reasoning methodology which uses the model to allocate communications resources in response to changing network conditions and communications loads. Implementation of the reasoning process using Answer Set Programming is demonstrated, providing illustration of the practicality of the approach. The application of the model and methodology to an example satellite communication network is presented. Using this approach significantly improved performance with respect to static resource allocation is demonstrated.

Recent numerical analyses to optimize the design of microfluidic devices for more effective entrapment or segregation of surrogate circulating tumor cells (CTCs) from healthy cells have been reported in the literature without concurrently accommodating the non-Newtonian nature of the body fluid and the non-uniform geometric shapes of the CTCs. Through a series of two-dimensional proof-of-concept simulations with increased levels of complexity (e.g., number of particles, inline obstacles), we investigated the validity of the assumptions of the Newtonian fluid behavior for pseudoplastic fluids and the circular particle shape for different-shaped particles (DSPs) in the context of microfluidics-facilitated shape-based segregation of particles. Simulations with a single DSP revealed that even in the absence of internal geometric complexities of a microfluidics channel, the aforementioned assumptions led to 0.11-0.21W (W is the channel length) errors in lateral displacements of DSPs, up to 3-20% errors in their velocities, and 3-5% errors in their travel times. When these assumptions were applied in simulations involving multiple DSPs in inertial microfluidics with inline obstacles, errors in the lateral displacements of DSPs were as high as 0.78W and in their travel times up to 23%, which led to different (un)symmetric flow and segregation patterns of DSPs. Thus, the fluid type and particle shape should be included in numerical models and experiments to assess the performance of microfluidics for targeted cell (e.g., CTCs) harvesting., 15 pages, 6 figures

This paper reports, for the first time, the computational performance of SequenceL for mesoscale simulations of large numbers of particles in a microfluidic device via the lattice-Boltzmann method. The performance of SequenceL simulations was assessed against the optimized serial and parallelized (via OpenMP directives) FORTRAN90 simulations. At present, OpenMP directives were not included in interparticle and particle-wall repulsive (steric) interaction calculations due to difficulties that arose from inter-iteration dependencies between consecutive iterations of the do-loops. SequenceL simulations, on the other hand, relied on built-in automatic parallelism. Under these conditions, numerical simulations revealed that the parallelized FORTRAN90 outran the performance of SequenceL by a factor of 2.5 or more when the number of particles was 100 or less. SequenceL, however, outran the performance of the parallelized FORTRAN90 by a factor of 1.3 when the number of particles was 300. Our results show that when the number of particles increased by 30-fold, the computational time of SequenceL simulations increased linearly by a factor of 1.5, as compared to a 3.2-fold increase in serial and a 7.7-fold increase in parallelized FORTRAN90 simulations. Considering SequenceL's efficient built-in parallelism that led to a relatively small increase in computational time with increased number of particles, it could be a promising programming language for computationally-efficient mesoscale simulations of large numbers of particles in microfluidic experiments. (C) 2016 Elsevier B.V. All rights reserved.

An ongoing debate in patent law involves the role that “non-practicing entities,” sometimes called “patent trolls” serve in the patent system. Some argue that they serve as valuable market intermediaries and other argue that they are a drain on innovation and an impediment to a well-functioning patent system. In this article, we add to the data available in this debate by conducting an event study that analyzes the market reaction to patent litigation filed by large, “mass-aggregator” NPE entities against large publicly traded companies. This study advances the literature by attempting to reproduce the results of previous event studies done in this area on newer market data and also by subjecting the event study results to more rigorous statistical analysis. In contrast to a previous event study, in our study we found that the market reacted little, if at all, to the patent litigation filed by large NPEs.

With the increase in the use of mobile devices in the workplace, both employer supplied and personally owned, and the major role social media has begun to play in today’s world, businesses face many new challenges with their employees. Social media may be seen by some employers as a virtual Pandora’s Box. Though it may seem to hold bountiful riches, employee posts can unleash a firestorm of unforeseen challenges and consequences ranging from financial, to legal, to ethical. In looking at business use of social media, this article will discuss the prevalence of social media use, possible legal liabilities thereof, and policies to consider.

Constitution-making is a ubiquitous but poorly understood phenomenon. There is much speculation but relatively little evidence about the impact of different design processes on constitutional outcomes. Much of the debate reduces to the question of who is involved in the process and when. We consider two central issues in this regard. The first is the problem of institutional self-dealing, or whether governmental organs that have something to gain from the constitutional outcome should be involved in the process. The second has to do with the merits of public involvement in the process. Both of these concerns have clear normative implications and both are amenable to straightforward social scientific analysis. This article surveys the relevant research on constitution-making, describes the conceptual issues involved in understanding constitution-making, reviews the various claims regarding variation in constitution-making processes, and presents a set of baseline empirical results from a new set of data on the content and process of constitution-making.

This paper describes an approach to fault tolerant design and implementation that uses a formal model to automatically generate fault detection and response methods. The approach is designed for resource-constrained embedded systems with high reliability requirements such as manned or critical space assets. The formal model-based approach offers several advantages over a conventional approach based on manual failure mode analysis (FMA). The primary benefits are increased confidence in the fault tolerance of the design and in the corresponding implementation. Increased confidence in the design is achieved because both the system architecture and reliability requirements are precisely described in a single formal model written in Answer Set Prolog (ASP). The readability of ASP facilitates precise communication between system engineers and stakeholders, thus increasing the likelihood that design errors are corrected early in the development cycle. Increased confidence in the implementation is achieved because it is automatically generated using the model and is guaranteed to satisfy the specified reliability requirements. Importantly, the control flow of the resulting implementation is straightforward and readable. Besides increased confidence, our approach is resilient to architecture and requirements changes. In our experience, once the model is updated it takes less than 10 minutes to re-generate the implementation and download to the target.

In this paper we further develop the formal theory of intentions suggested by C. Baral and M. Gelfond in 2005. In this work the authors formalized the behavior of an agent intending to execute a sequence of actions. The resulting axioms for intentions written in Knowledge Representation language Answer Set Prolog allowed to easily express such properties of intentions as persistence and non-procrastination. This paper expands this work to allow reasoning with intentions in the presence of unexpected observations, and intentions to achieve goals. The theory is formulated in the extension of Answer Set Prolog, called CR-Prolog.

In the wake of Bernard Madoff’s $65 billion Ponzi scheme and the recent economic crisis stemming largely from loosely regulated subprime lending and mortgage-backed securities, President Obama signed the Dodd-Frank Wall Street Reform and Consumer Protection Act (“Dodd-Frank”) on July 21, 2010, signaling loudly and clearly that change is coming to Wall Street. But Wall Street is not the only one receiving a message. Buried deep within the 2,319 pages of the Dodd-Frank Act, companies can find Section 922, the whistleblower provision, which provides a bounty for whistleblowers who report securities violations to the Securities and Exchange Commission. These bounty provisions and the subsequent rules implementing them have been criticized by many as ineffective and unnecessarily intrusive on established internal compliance programs. In light of these criticisms, this Article analyzes the Dodd-Frank bounty program and its likely effect on corporate internal compliance programs, relying largely upon literature and studies in the areas of behavioral economics, organizational behavior, and business ethics relating to whistleblowing. The authors argue that rather than undermining internal compliance programs, the Dodd-Frank bounty program will serve as a much needed check on poorly administered internal compliance that are not adequately policing fraud and unethical behavior.