Values, Lifestyle, and Discipleship: Session 3

...So you can teach a one year old a two year old. You had a two year old often enough when you tell him not to go in the street, he associates the pain on the rear with the Knoll, and he doesn\u27t go in the street. That\u27s called obedience somewhere you\u27ve got to make the transition to honor, and you got to honor your parents. Why? Because it\u27s a biblical command. I don\u27t think anybody doesn\u27t honor their parents has any right to go out on the street and share Jesus with people and say, it\u27s wonderful to be a Christian if we haven\u27t put our own parental thing together. See, that\u27s a biblical responsibility. Honor thy father and mother. Why

Values, Lifestyle, and Discipleship: Session 2

Okay, all right. Your beliefs would be saying, I know this thing is right. Your values would be saying, but I\u27m not doing that. I\u27m not walking that out. I made this statement yesterday. I said to me, like, functional values are the ones the wheels on my belief wagon. In other words, I\u27m saying, I\u27ve got beliefs here. I believe this and this and this and this and this. And in order to walk that out, I\u27ve got to get wheels on that thing. I\u27ve got to make it move

The set of solutions of random XORSAT formulae

The XOR-satisfiability (XORSAT) problem requires finding an assignment of $n$ Boolean variables that satisfy $m$ exclusive OR (XOR) clauses, whereby each clause constrains a subset of the variables. We consider random XORSAT instances, drawn uniformly at random from the ensemble of formulae containing $n$ variables and $m$ clauses of size $k$. This model presents several structural similarities to other ensembles of constraint satisfaction problems, such as $k$-satisfiability ($k$-SAT), hypergraph bicoloring and graph coloring. For many of these ensembles, as the number of constraints per variable grows, the set of solutions shatters into an exponential number of well-separated components. This phenomenon appears to be related to the difficulty of solving random instances of such problems. We prove a complete characterization of this clustering phase transition for random $k$-XORSAT. In particular, we prove that the clustering threshold is sharp and determine its exact location. We prove that the set of solutions has large conductance below this threshold and that each of the clusters has large conductance above the same threshold. Our proof constructs a very sparse basis for the set of solutions (or the subset within a cluster). This construction is intimately tied to the construction of specific subgraphs of the hypergraph associated with an instance of $k$-XORSAT. In order to study such subgraphs, we establish novel local weak convergence results for them.Comment: Published at http://dx.doi.org/10.1214/14-AAP1060 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Dynamic Energy Management

We present a unified method, based on convex optimization, for managing the power produced and consumed by a network of devices over time. We start with the simple setting of optimizing power flows in a static network, and then proceed to the case of optimizing dynamic power flows, i.e., power flows that change with time over a horizon. We leverage this to develop a real-time control strategy, model predictive control, which at each time step solves a dynamic power flow optimization problem, using forecasts of future quantities such as demands, capacities, or prices, to choose the current power flow values. Finally, we consider a useful extension of model predictive control that explicitly accounts for uncertainty in the forecasts. We mirror our framework with an object-oriented software implementation, an open-source Python library for planning and controlling power flows at any scale. We demonstrate our method with various examples. Appendices give more detail about the package, and describe some basic but very effective methods for constructing forecasts from historical data.Comment: 63 pages, 15 figures, accompanying open source librar

One‐dimensional patterning of cells in silicone wells via compression‐induced fracture

We have adapted our existing compression‐induced fracture technology to cell culture studies by generating linear patterns on a complex cell culture well structure rather than on simple solid constructs. We present a simple method to create one‐dimensional (1D), submicron, and linear patterns of extracellular matrix on a multilayer silicone material. We identified critical design parameters necessary to optimize compression‐induced fracture patterning on the wells, and applied stresses using compression Hoffman clamps. Finite‐element analyses show that the incorporation of the well improves stress homogeneity (stress variation = 25%), and, thus, crack uniformity over the patterned region. Notably, a shallow well with a thick base (vs. deeper wells with thinner bases) reduces out‐of‐plane deflections by greater than a sixth in the cell culture region, improving clarity for optical imaging. The comparison of cellular and nuclear shape indices of a neuroblast line cultured on patterned 1D lines and unpatterned 2D surfaces reveals significant differences in cellular morphology, which could impact many cellular functions. Because 1D cell cultures recapitulate many important phenotypical traits of 3D cell cultures, our culture system offers a simple means to further study the relationship between 1D and 3D cell culture environments, without demanding expensive engineering techniques and expertise. © 2013 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 102A: 1361–1369, 2014.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106690/1/jbma34814.pd