Phase separation effects and the nematic-isotropic transition in polymer and low molecular weight liquid crystals doped with nanoparticles

Properties of the nematic–isotropic phase transition in polymer and low molecular weight liquid crystals doped with nanoparticles have been studied both experimentally and theoretically in terms of molecular mean-field theory. The variation of the transition temperature and the transition heat with the increasing volume fraction of CdSe quantum dot nanoparticles in copolymer and low molecular weight nematics has been investigated experimentally and the data are interpreted using the results of the molecular theory which accounts for a possibility of phase separation when the system undergoes the nematic–isotropic transition. The theory predicts that the nematic and isotropic phases with different concentrations of nanoparticles may coexist over a broad temperature range, but only if the nanoparticle volume fraction exceeds a certain threshold value which depends on the material parameters. Such unusual phase separation effects are determined by the strong interaction between nanoparticles and mesogenic groups and between nanoparticles themselves

Society-in-the-Loop: Programming the Algorithmic Social Contract

Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, `SITL = HITL + Social Contract.'Comment: (in press), Ethics of Information Technology, 201

Edgeworth Expansion of the Largest Eigenvalue Distribution Function of GUE Revisited

We derive expansions of the resolvent Rn(x;y;t)=(Qn(x;t)Pn(y;t)-Qn(y;t)Pn(x;t))/(x-y) of the Hermite kernel Kn at the edge of the spectrum of the finite n Gaussian Unitary Ensemble (GUEn) and the finite n expansion of Qn(x;t) and Pn(x;t). Using these large n expansions, we give another proof of the derivation of an Edgeworth type theorem for the largest eigenvalue distribution function of GUEn. We conclude with a brief discussion on the derivation of the probability distribution function of the corresponding largest eigenvalue in the Gaussian Orthogonal Ensemble (GOEn) and Gaussian Symplectic Ensembles (GSEn)

Nearest Points on Toric Varieties

We determine the Euclidean distance degree of a projective toric variety. This extends the formula of Matsui and Takeuchi for the degree of the $A$-discriminant in terms of Euler obstructions. Our primary goal is the development of reliable algorithmic tools for computing the points on a real toric variety that are closest to a given data point.Comment: 20 page

Extended requirements traceability: results of an industrial case study

Contribution structures offer a way to model the network of people who have participated in the requirements engineering process. They further provide the opportunity to extend conventional forms of artifact-based requirements traceability with the traceability of contributing personnel. In this paper, we describe a case study that investigated the modeling and use of contribution structures in an industrial project. In particular, we demonstrate how they made it possible to answer previously unanswerable questions about the human source(s) of requirements. In so doing, we argue that this information addresses problems currently attributed to inadequate requirements traceability

Assessment of chronic postsurgical pain after knee replacement : a systematic review

Objective: Approximately 20% of patients experience chronic pain after total knee replacement (TKR), yet there is no consensus about how best to assess such pain. This systematic review aimed to identify measures used to characterise chronic pain after TKR. Methods: MEDLINE, Embase, PsycINFO, Cochrane Library and CINAHL databases were searched for research articles published in all languages from January 2002- November 2011. Articles were eligible for inclusion if they assessed knee pain at a minimum of 3-months after TKR, yielding a total of 1,164 articles. Data extracted included study design, country, timings of assessments, and outcome measures containing pain items. Outcome measures were compared with domains recommended by IMMPACT for inclusion in assessment of chronic pain related outcomes within clinical trials. Temporal trends were also explored. Results: The review found use of a wide variety of composite and single-item measures, with the American Knee Society Score most common. Many measures used in published studies do not capture the multi-dimensional nature of pain recommended by IMMPACT; of those commonly used, the WOMAC and Oxford Knee Score are most comprehensive. Geographical trends were evident, with nation-specific preferences for particular measures. A recent reduction in use of some clinically-administered tools was accompanied by increased use of patient-reported outcome measures. Conclusion: There was wide variation in methods of pain assessment alongside nation-specific preferences and changing temporal trends in pain assessment after TKR. Standardisation and improvements in assessment is needed to enhance the quality of research and facilitate the establishment of a core outcome set