The Coolest Way to Generate Binary Strings

Pick a binary string of length n and remove its first bit b. Now insert b after the first remaining 10, or insert $\overline{b}$ at the end if there is no remaining 10. Do it again. And again. Keep going! Eventually, you will cycle through all 2 ⁿ of the binary strings of length n. For example, are the binary strings of length n=4, where and . And if you only want strings with weight (number of 1s) between ? and u? Just insert b instead of $\overline{b}$ when the result would have too many 1s or too few 1s. For example, are the strings with n=4, ?=0 and u=2. This generalizes ‘cool-lex’ order by Ruskey and Williams (The coolest way to generate combinations, Discrete Mathematics) and we present two applications of our ‘cooler’ order. First, we give a loopless algorithm for generating binary strings with any weight range in which successive strings have Levenshtein distance two. Second, we construct de Bruijn sequences for (i) ?=0 and any u (maximum specified weight), (ii) any ? and u=n (minimum specified weight), and (iii) odd u?? (even size weight range). For example, all binary strings with n=6, ?=1, and u=4 appear once (cyclically) in . We also investigate the recursive structure of our order and show that it shares certain sublist properties with lexicographic order.     

Two-Way Interconnection with Partial Consumer Participation

This paper incorporates partial consumer participation in a model of competition between telecommunications networks with two-way interconnection. It is shown, in contrast to the results of similar models with full participation, that the firms' equilibrium profits depend on the level of a reciprocal access charge under two-part retail pricing. Under some simplifying assumptions, it is shown that firms prefer the access charge be set equal to the marginal cost of termination, which coincides with the social optimum. Without these additional assumptions the model is analytically complex and simulation results are presented that suggest firms prefer the access charge to be less than marginal cost, while the socially optimal access charge may be above or below cost depending on the differentiation of the firms.     

The Flexible Rare Event Sampling Harness System (FRESHS)

We present the software package FRESHS (http://www.freshs.org) for parallel simulation of rare events using sampling techniques from the ‘splitting’ family of methods. Initially, Forward Flux Sampling (FFS) and Stochastic Process Rare Event Sampling (SPRES) have been implemented. These two methods together make rare event sampling available for both quasi-static and full non-equilibrium regimes. Our framework provides a plugin system for software implementing the underlying physics of the system of interest. At present, example plugins exist for our framework to steer the popular MD packages GROMACS, LAMMPS and ESPResSo, but due to the simple interface of our plugin system, it is also easy to attach other simulation software or self-written code. Use of our framework does not require recompilation of the simulation program. The modular structure allows the flexible implementation of further sampling methods or physics engines and creates a basis for objective comparison of different sampling algorithms.     

Overview or "underview"? Comment on Satz and Fletcher's "Emergent trends in neuropsychology: An overview."

Argues that P. Satz and J. M. Fletcher (see record 1982-05864-001) ignored research contradicting their dismissal of evidence of the greater plasticity and recovery from damage of the infant than adult brain as "myths." It is also argued that their overview also failed to consider critical complications that may limit or reverse patterns of recovery and overlooked accumulating evidence of principles not only underlying the pathogenic mechanism in earlier or later disorganizations of cerebral functions and principles of their organization but especially their reorganization following brain insults in infants and adults. (56 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Trustworthy Proof Checker

Proof-carrying code (PCC) and other applications in computer security require machine-checkable proofs of properties of machine-language programs. The main advantage of the PCC approach is that the amount of code that must be explicitly trusted is very small: it consists of the logic in which predicates and proofs are expressed, the safety predicate, and the proof checker. We have built a minimal proof checker, and we explain its design principles and the representation issues of the logic, safety predicate, and safety proofs. We show that the trusted computing base (TCB) in such a system can indeed be very small. In our current system the TCB is less than 2,700 lines of code (an order of magnitude smaller even than other PCC systems), which adds to our confidence of its correctness.     

Fast Lighting Independent Background Subtraction

This paper describes a simple method of fast background subtraction based upon disparity verification that is invariant to arbitrarily rapid run-time changes in illumination. Using two or more cameras, the method requires the off-line construction of disparity fields mapping the primary background images. At runtime, segmentation is performed by checking background image to each of the additional auxiliary color intensity values at corresponding pixels. If more than two cameras are available, more robust segmentation can be achieved and, in particular, the occlusion shadows can be generally eliminated as well. Because the method only assumes fixed background geometry, the technique allows for illumination variation at runtime. Since no disparity search is performed, the algorithm is easily implemented in real-time on conventional hardware.     

Modeling the glucose regulatory system in extreme preterm infants

Background

Premature infants represent a significant proportion of the neonatal intensive care population. Blood glucose homeostasis in this group is often disturbed by immaturity of endogenous regulatory systems and the stress of their condition. Hypo- and hyperglycemia are frequently reported in very low birth weight infants, and more mature infants often experience low levels of glycemia. A model capturing the unique fundamental dynamics of the neonatal glucose regulatory system could be used to develop better blood glucose control methods.

Methods

A metabolic system model is adapted from adult critical care to the unique physiological case of the neonate. Integral-based fitting methods were used to identify time-varying insulin sensitivity and non-insulin mediated glucose uptake profiles. The clinically important predictive ability of the model was assessed by assuming insulin sensitivity was constant over prediction intervals of 1, 2 and 4 h forward and comparing model-simulated versus actual clinical glucose values for all recorded interventions. The clinical data included 1091 glucose measurements over 3567 total patient hours, along with all associated insulin and nutritional infusion data, for N = 25 total cases. Ethics approval was obtained from the Upper South A Regional Ethics Committee for this study.

Results

The identified model had a median absolute percentage error of 2.4% [IQR: 0.9-4.8%] between model-fitted and clinical glucose values. Median absolute prediction errors at 1-, 2- and 4-h intervals were 5.2% [IQR: 2.5-10.3%], 9.4% [IQR: 4.5-18.4%] and 13.6% [IQR: 6.3-27.6%] respectively.

Conclusions

The model accurately captures and predicts the fundamental dynamic behaviors of the neonatal metabolism well enough for effective clinical decision support in glycemic control. The adaptation from adult to a neonatal case is based on the data from the literature. Low prediction errors and very low fitting errors indicate that the fundamental dynamics of glucose metabolism in both premature neonates and critical care adults can be described by similar mathematical models.     

Shorthand Universal Cycles for Permutations

The set of permutations of ??n??={1,??,n} in one-line notation is ??(n). The shorthand encoding of a ₁?a _n ????(n) is a ₁?a _n?1. A shorthand universal cycle for permutations (SP-cycle) is a circular string of length n! whose substrings of length n?1 are the shorthand encodings of ??(n). When an SP-cycle is decoded, the order of ??(n) is a Gray code in which successive permutations differ by the prefix-rotation ?? _i =(1 2 ? i) for i??{n?1,n}. Thus, SP-cycles can be represented by n! bits. We investigate SP-cycles with maximum and minimum ??weight?? (number of ?? _n?1s in the Gray code). An SP-cycle n a n b?n z is ??periodic?? if its ??sub-permutations?? a,b,??,z equal ??(n?1). We prove that periodic min-weight SP-cycles correspond to spanning trees of the (n?1)-permutohedron. We provide two constructions: B(n) and C(n). In B(n) the spanning trees use ??half-hunts?? from bell-ringing, and in C(n) the sub-permutations use cool-lex order by Williams (SODA, 987?C996, 2009). Algorithmic results are: (1)?memoryless decoding of B(n) and C(n), (2)?O((n?1)!)-time generation of B(n) and C(n) using sub-permutations, (3)?loopless generation of B(n)??s binary representation n bits at a time, and (4)?O(n+??(n))-time ranking of B(n)??s permutations where ??(n) is the cost of computing a permutation??s inversion vector. Results (1)?C(4) improve on those for the previous SP-cycle construction D(n) by Ruskey and Williams (ACM Trans. Algorithms 6(3):Art.?45, 2010), which we characterize here using ??recycling??.     

Mood modeling: accuracy depends on active logging and reflection

Current behavior change systems often demand extremely advanced sensemaking skills, requiring users to interpret personal datasets in order to understand and change behavior. We describe EmotiCal, a system to help people better manage their emotions, that finesses such complex sensemaking by directly recommending specific mood-boosting behaviors to users. This paper first describes how we develop the accurate mood models that underlie these mood-boosting recommendations. We go on to analyze what types of information contribute most to the predictive power of such models, and how we might design systems to reliably collect such predictive information. Our results show that we can derive very accurate mood models with relatively small samples of just 70 users. These models explain 61% of variance by combining: (a) user reflection about the effects of different activities on mood, (b) user explanations of how different activities affect mood, and (c) individual differences. We discuss the implications of these findings for the design of behavior change systems, as well as for theory and practice. Contrary to many recent approaches, our findings argue for the importance of active user reflection rather than passive sensing.