Factors effecting families' response to a treatment offer by a child guidance clinic

Thesis (M.S.)--Boston UniversityThis is a study of factors in the initial contact related to families' handling of a treatment plan offered by a child guidance clinic. When a clinic considers cases for treatment plans it is important to know as closely as possible that the family can and will use such help. The needs of the community for the helping services of the clinic as shown, in part, by the waiting lists are a charge to the clinic to offer treatment wisely. The nature of many of the problem situations presented for consideration is such that the decision can be a crucial one in the lives of whole families. Clinics do not offer a simple remedy, but a complex problem-solving process which involves two or more members of the family in a new kind of experience with the combined efforts of the clinic team. Each clinic has objective criteria to consider in making its selection of cases and each has a vital interest in broadening this objective base for a more scientific procedure. This study of factors relating to acceptance of treatment is pertinent to that interest. Two groups of twelve cases presenting similar problems have been compared. One group consists of cases which did not accept treatment when it was offered. The other is a group of cases which accepted and entered into treatment. The application interviews as recorded in the case records were examined by means of a schedule. The schedule was constructed to examine factual data and the attitudes of both parents toward help, toward their child and toward the problem. The information from the two groups was then contrasted in an attempt to identify any significant differences. [TRUNCATED

Local biomass feedstocks availability for fueling ethanol production

Crop Production/Industries, Resource /Energy Economics and Policy,

Derived Demand for Fresh Cheese Products Imported into Japan

The objective of this article is to estimate the derived demand for imported fresh cheese products into Japan when fresh cheese import data are disaggregated by source country of production. We provide empirical measures of the sensitivity of demand to changes in total imports, own-price, and cross-prices among exporting countries for fresh cheese. Japan's derived demand for U.S. fresh cheese products is perfectly inelastic. Thus, the import demand competition among importing countries should be based upon differences in product characteristics.Demand and Price Analysis, International Relations/Trade,

Symmetry Properties of Nested Canalyzing Functions

Many researchers have studied symmetry properties of various Boolean functions. A class of Boolean functions, called nested canalyzing functions (NCFs), has been used to model certain biological phenomena. We identify some interesting relationships between NCFs, symmetric Boolean functions and a generalization of symmetric Boolean functions, which we call $r$-symmetric functions (where $r$ is the symmetry level). Using a normalized representation for NCFs, we develop a characterization of when two variables of an NCF are symmetric. Using this characterization, we show that the symmetry level of an NCF $f$ can be easily computed given a standard representation of $f$. We also present an algorithm for testing whether a given $r$-symmetric function is an NCF. Further, we show that for any NCF $f$ with $n$ variables, the notion of strong asymmetry considered in the literature is equivalent to the property that $f$ is $n$-symmetric. We use this result to derive a closed form expression for the number of $n$-variable Boolean functions that are NCFs and strongly asymmetric. We also identify all the Boolean functions that are NCFs and symmetric.Comment: 17 page

A Corpus Investigation of Syntactic Embedding in Piraha

The Pirahã language has been at the center of recent debates in linguistics, in large part because it is claimed not to exhibit recursion, a purported universal of human language. Here, we present an analysis of a novel corpus of natural Pirahã speech that was originally collected by Dan Everett and Steve Sheldon. We make the corpus freely available for further research. In the corpus, Pirahã sentences have been shallowly parsed and given morpheme-aligned English translations. We use the corpus to investigate the formal complexity of Pirahã syntax by searching for evidence of syntactic embedding. In particular, we search for sentences which could be analyzed as containing center-embedding, sentential complements, adverbials, complementizers, embedded possessors, conjunction or disjunction. We do not find unambiguous evidence for recursive embedding of sentences or noun phrases in the corpus. We find that the corpus is plausibly consistent with an analysis of Pirahã as a regular language, although this is not the only plausible analysis

Finding Nontrivial Minimum Fixed Points in Discrete Dynamical Systems

Networked discrete dynamical systems are often used to model the spread of contagions and decision-making by agents in coordination games. Fixed points of such dynamical systems represent configurations to which the system converges. In the dissemination of undesirable contagions (such as rumors and misinformation), convergence to fixed points with a small number of affected nodes is a desirable goal. Motivated by such considerations, we formulate a novel optimization problem of finding a nontrivial fixed point of the system with the minimum number of affected nodes. We establish that, unless P = NP, there is no polynomial time algorithm for approximating a solution to this problem to within the factor n^1-\epsilon for any constant epsilon > 0. To cope with this computational intractability, we identify several special cases for which the problem can be solved efficiently. Further, we introduce an integer linear program to address the problem for networks of reasonable sizes. For solving the problem on larger networks, we propose a general heuristic framework along with greedy selection methods. Extensive experimental results on real-world networks demonstrate the effectiveness of the proposed heuristics.Comment: Accepted at AAAI-2

Networked Anti-Coordination Games Meet Graphical Dynamical Systems: Equilibria and Convergence

Evolutionary anti-coordination games on networks capture real-world strategic situations such as traffic routing and market competition. In such games, agents maximize their utility by choosing actions that differ from their neighbors' actions. Two important problems concerning evolutionary games are the existence of a pure Nash equilibrium (NE) and the convergence time of the dynamics. In this work, we study these two problems for anti-coordination games under sequential and synchronous update schemes. For each update scheme, we examine two decision modes based on whether an agent considers its own previous action (self essential ) or not (self non-essential ) in choosing its next action. Using a relationship between games and dynamical systems, we show that for both update schemes, finding an NE can be done efficiently under the self non-essential mode but is computationally intractable under the self essential mode. To cope with this hardness, we identify special cases for which an NE can be obtained efficiently. For convergence time, we show that the best-response dynamics converges in a polynomial number of steps in the synchronous scheme for both modes; for the sequential scheme, the convergence time is polynomial only under the self non-essential mode. Through experiments, we empirically examine the convergence time and the equilibria for both synthetic and real-world networks.Comment: Accepted at AAAI-2

Learning the Topology and Behavior of Discrete Dynamical Systems

Discrete dynamical systems are commonly used to model the spread of contagions on real-world networks. Under the PAC framework, existing research has studied the problem of learning the behavior of a system, assuming that the underlying network is known. In this work, we focus on a more challenging setting: to learn both the behavior and the underlying topology of a black-box system. We show that, in general, this learning problem is computationally intractable. On the positive side, we present efficient learning methods under the PAC model when the underlying graph of the dynamical system belongs to some classes. Further, we examine a relaxed setting where the topology of an unknown system is partially observed. For this case, we develop an efficient PAC learner to infer the system and establish the sample complexity. Lastly, we present a formal analysis of the expressive power of the hypothesis class of dynamical systems where both the topology and behavior are unknown, using the well-known formalism of the Natarajan dimension. Our results provide a theoretical foundation for learning both the behavior and topology of discrete dynamical systems.Comment: Accepted at AAAI-2