Parenting as Phenotype: A Behavioral Genetic Approach to Understanding Parenting

This article discusses the behavioral genetic (BG) approach to parenting. Parenting is considered a phenotype that can be influenced by nature and nurture. Genetic contributions to parenting are conceptualized as evidence of genotype–environment correlation (rGE). Early BG studies focused on demonstrating that some parenting dimensions were heritable due to passive and evocative rGE processes. Current studies are investigating moderators and mediators of genetic and environmental contributions to parenting. The paper uses parent and child report data on parental warmth from the Twins, Adoptees, Peers, and Siblings study to illustrate the BG approach. Results show that heritability is significant for parent and child reports, but environmental influences differ by information source. Three questions are addressed concerning the BG approach to parenting: What is the nature of parenting? How does the approach inform parenting practice and interventions? What are the future directions

Sparse Fault-Tolerant BFS Trees

This paper addresses the problem of designing a sparse {\em fault-tolerant} BFS tree, or {\em FT-BFS tree} for short, namely, a sparse subgraph $T$ of the given network $G$ such that subsequent to the failure of a single edge or vertex, the surviving part $T'$ of $T$ still contains a BFS spanning tree for (the surviving part of) $G$. Our main results are as follows. We present an algorithm that for every $n$-vertex graph $G$ and source node $s$ constructs a (single edge failure) FT-BFS tree rooted at $s$ with O(n \cdot \min\{\Depth(s), \sqrt{n}\}) edges, where \Depth(s) is the depth of the BFS tree rooted at $s$. This result is complemented by a matching lower bound, showing that there exist $n$-vertex graphs with a source node $s$ for which any edge (or vertex) FT-BFS tree rooted at $s$ has $\Omega(n^{3/2})$ edges. We then consider {\em fault-tolerant multi-source BFS trees}, or {\em FT-MBFS trees} for short, aiming to provide (following a failure) a BFS tree rooted at each source $s\in S$ for some subset of sources $S\subseteq V$. Again, tight bounds are provided, showing that there exists a poly-time algorithm that for every $n$-vertex graph and source set $S \subseteq V$ of size $\sigma$ constructs a (single failure) FT-MBFS tree $T^*(S)$ from each source $s_i \in S$, with $O(\sqrt{\sigma} \cdot n^{3/2})$ edges, and on the other hand there exist $n$-vertex graphs with source sets $S \subseteq V$ of cardinality $\sigma$, on which any FT-MBFS tree from $S$ has $\Omega(\sqrt{\sigma}\cdot n^{3/2})$ edges. Finally, we propose an $O(\log n)$ approximation algorithm for constructing FT-BFS and FT-MBFS structures. The latter is complemented by a hardness result stating that there exists no $\Omega(\log n)$ approximation algorithm for these problems under standard complexity assumptions

Computing a rectilinear shortest path amid splinegons in plane

We reduce the problem of computing a rectilinear shortest path between two given points s and t in the splinegonal domain \calS to the problem of computing a rectilinear shortest path between two points in the polygonal domain. As part of this, we define a polygonal domain \calP from \calS and transform a rectilinear shortest path computed in \calP to a path between s and t amid splinegon obstacles in \calS. When \calS comprises of h pairwise disjoint splinegons with a total of n vertices, excluding the time to compute a rectilinear shortest path amid polygons in \calP, our reduction algorithm takes O(n + h \lg{n}) time. For the special case of \calS comprising of concave-in splinegons, we have devised another algorithm in which the reduction procedure does not rely on the structures used in the algorithm to compute a rectilinear shortest path in polygonal domain. As part of these, we have characterized few of the properties of rectilinear shortest paths amid splinegons which could be of independent interest

Deterministic Sampling and Range Counting in Geometric Data Streams

We present memory-efficient deterministic algorithms for constructing epsilon-nets and epsilon-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. We show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. We use these techniques to approximate several robust statistics of geometric data streams, including Tukey depth, simplicial depth, regression depth, the Thiel-Sen estimator, and the least median of squares. Our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are inverse-polylogarithmic. We also include a lower bound for non-iceberg geometric queries.Comment: 12 pages, 1 figur

To know or not to know? Dilemmas for women receiving unknown oocyte donation

BACKGROUND: This study aims to provide insight into the reasons for choosing an unknown oocyte donor and to explore recipients’ feelings and wishes regarding donor information. METHODS: In-depth interviews were carried out with 11 women at different stages of treatment. Seven were on a waiting list and four have given birth to donor oocyte babies. The interviews were analysed using interpretative phenomenological analysis. RESULTS: The choice of unknown donor route was motivated by a wish to feel secure in the role of mother as well as to avoid possible intrusions into family relationships. The information that is available about unknown donors is often very limited. In the preconception phase of treatment, some participants wanted more information about the donor but others adopted a not-knowing stance that protected them from the emotional impact of needing a donor. In the absence of information that might normalize her, there was a tendency to imagine the donor in polarised simplistic terms, so she may be idealized or feared. Curiosity about the donor intensified once a real baby existed, and the task of telling a child was more daunting when very little was known about the donor. A strong wish for same-donor siblings was expressed by all of the participants who had given birth. CONCLUSIONS: This qualitative study throws light on the factors that influence the choice of unknown donation. It also highlights the scope for attitudes to donor information to undergo change over the course of treatment and after giving birth. The findings have implications for pretreatment counselling and raise a number of issues that merit further exploration

Cohesion, team mental models, and collective efficacy: Towards an integrated framework of team dynamics in sport

A nomological network on team dynamics in sports consisting of a multi-framework perspective is introduced and tested. The aim was to explore the interrelationship among cohesion, team mental models (TMM), collective-efficacy (CE), and perceived performance potential (PPP). Three hundred and forty college-aged soccer players representing 17 different teams (8 female and 9 male) participated in the study. They responded to surveys on team cohesion, TMM, CE and PPP. Results are congruent with the theoretical conceptualization of a parsimonious view of team dynamics in sports. Specifically, cohesion was found to be an exogenous variable predicting both TMM and CE beliefs. TMM and CE were correlated and predicted PPP, which in turn accounted for 59% of the variance of objective performance scores as measured by teams’ season record. From a theoretical standpoint, findings resulted in a parsimonious view of team dynamics, which may represent an initial step towards clarifying the epistemological roots and nomological network of various team-level properties. From an applied standpoint, results suggest that team expertise starts with the establishment of team cohesion. Following the establishment of cohesiveness, teammates are able to advance team-related schemas and a collective sense of confidence. Limitations and key directions for future research are outlined

Examining the Psychometric Properties of the CEAC (Comparing e-Cigarette and Cigarette) Questionnaire and Its Usefulness as a Predictor of e-Cigarette Use

Background: Electronic cigarette (e-cigarette) use continues to rise, while there is conflicting evidence about the health effects of its use. As such, research is needed to better determine risks factors for e-cigarette use. Accumulating evidence suggests that attitudes toward e-cigarette use could be a potential risk factor for e-cigarette use. Objectives: This study sought to examine the psychometric properties of the Comparing E-cigarette And Cigarette questionnaire (CEAC), and to replicate a structural model of the relationship between impulsive-related personality traits and e-cigarette use mediated by positive attitudes toward e-cigarettes. Methods: Participants were 525 adults (mean age = 33.42, SD = 11.27) who completed the CEAC and UPPS-P (trait impulsivity) questionnaires online. Results: Confirmatory factor analysis of the CEAC replicated the a priori factor structure of the questionnaire reasonably well (χ2(df = 32) =172.85, CFI = 0.94, TLI = 0.91, RMSEA = 0.09 (0.08–0.11, 90% Confidence Interval, SRMR = 0.06). Structural path analysis showed that deficits in conscientiousness was significantly negatively related to e-cigarette attitudes (β = –0.20, p = .01), while urgency (β = 0.19, p = .018) showed a significant positive relationship to e-cigarette attitudes. E-cigarette users showed significantly more positive attitudes toward e-cigarettes than nonusers (β = 0.59, p < .001). No significant direct effects were found between impulsivity-related traits and e-cigarette use. Conclusions: The present study suggests that impulsivity-related traits and attitudes toward e-cigarettes are likely to be important risk factors for e-cigarette use. Future prospective and experimental studies should test if the causal model described in this study predicts risk for e-cigarette use, and whether this model could therefore be used to guide strategies for reducing risk for e-cigarette use