Identification of Mental States and Interpersonal Functioning in Borderline Personality Disorder

Atypical identification of mental states in the self and others has been proposed to underlie interpersonal difficulties in borderline personality disorder (BPD), yet no previous empirical research has directly examined associations between these constructs. We examine 3 mental state identification measures and their associations with experience-sampling measures of interpersonal functioning in participants with BPD relative to a healthy comparison (HC) group. We also included a clinical comparison group diagnosed with avoidant personality disorder (APD) to test the specificity of this constellation of difficulties to BPD. When categorizing blended emotional expressions, the BPD group identified anger at a lower threshold than did the HC and APD groups, but no group differences emerged in the threshold for identifying happiness. These results are consistent with enhanced social threat identification and not general negativity biases in BPD. The Reading the Mind in the Eyes Test (RMET) showed no group differences in general mental state identification abilities. Alexithymia scores were higher in both BPD and APD relative to the HC group, and difficulty identifying one’s own emotions was higher in BPD compared to APD and HC. Within the BPD group, lower RMET scores were associated with lower anger identification thresholds and higher alexithymia scores. Moreover, lower anger identification thresholds, lower RMET scores, and higher alexithymia scores were all associated with greater levels of interpersonal difficulties in daily life. Research linking measures of mental state identification with experience-sampling measures of interpersonal functioning can help clarify the role of mental state identification in BPD symptoms

Reflections on a coaching pilot project in healthcare settings

This paper draws on personal reflection of coaching experiences and learning as a coach to consider the relevance of these approaches in a management context with a group of four healthcare staff who participated in a pilot coaching project. It explores their understanding of coaching techniques applied in management settings via their reflections on using coaching approaches and coaching applications as healthcare managers. Coaching approaches can enhance a manager’s skill portfolio and offer the potential benefits in terms of successful goal achievement, growth, mutual learning and development for both themselves and staff they work with in task focused scenarios

Parameterized Complexity of the k-anonymity Problem

The problem of publishing personal data without giving up privacy is becoming increasingly important. An interesting formalization that has been recently proposed is the $k$-anonymity. This approach requires that the rows of a table are partitioned in clusters of size at least $k$ and that all the rows in a cluster become the same tuple, after the suppression of some entries. The natural optimization problem, where the goal is to minimize the number of suppressed entries, is known to be APX-hard even when the records values are over a binary alphabet and $k=3$, and when the records have length at most 8 and $k=4$ . In this paper we study how the complexity of the problem is influenced by different parameters. In this paper we follow this direction of research, first showing that the problem is W[1]-hard when parameterized by the size of the solution (and the value $k$). Then we exhibit a fixed parameter algorithm, when the problem is parameterized by the size of the alphabet and the number of columns. Finally, we investigate the computational (and approximation) complexity of the $k$-anonymity problem, when restricting the instance to records having length bounded by 3 and $k=3$. We show that such a restriction is APX-hard.Comment: 22 pages, 2 figure

Computable randomness is about more than probabilities

We introduce a notion of computable randomness for infinite sequences that generalises the classical version in two important ways. First, our definition of computable randomness is associated with imprecise probability models, in the sense that we consider lower expectations (or sets of probabilities) instead of classical 'precise' probabilities. Secondly, instead of binary sequences, we consider sequences whose elements take values in some finite sample space. Interestingly, we find that every sequence is computably random with respect to at least one lower expectation, and that lower expectations that are more informative have fewer computably random sequences. This leads to the intriguing question whether every sequence is computably random with respect to a unique most informative lower expectation. We study this question in some detail and provide a partial answer

Reconfiguration of Dominating Sets

We explore a reconfiguration version of the dominating set problem, where a dominating set in a graph $G$ is a set $S$ of vertices such that each vertex is either in $S$ or has a neighbour in $S$. In a reconfiguration problem, the goal is to determine whether there exists a sequence of feasible solutions connecting given feasible solutions $s$ and $t$ such that each pair of consecutive solutions is adjacent according to a specified adjacency relation. Two dominating sets are adjacent if one can be formed from the other by the addition or deletion of a single vertex. For various values of $k$, we consider properties of $D_k(G)$, the graph consisting of a vertex for each dominating set of size at most $k$ and edges specified by the adjacency relation. Addressing an open question posed by Haas and Seyffarth, we demonstrate that $D_{\Gamma(G)+1}(G)$ is not necessarily connected, for $\Gamma(G)$ the maximum cardinality of a minimal dominating set in $G$. The result holds even when graphs are constrained to be planar, of bounded tree-width, or $b$-partite for $b \ge 3$. Moreover, we construct an infinite family of graphs such that $D_{\gamma(G)+1}(G)$ has exponential diameter, for $\gamma(G)$ the minimum size of a dominating set. On the positive side, we show that $D_{n-m}(G)$ is connected and of linear diameter for any graph $G$ on $n$ vertices having at least $m+1$ independent edges.Comment: 12 pages, 4 figure

Parameterized complexity of the MINCCA problem on graphs of bounded decomposability

In an edge-colored graph, the cost incurred at a vertex on a path when two incident edges with different colors are traversed is called reload or changeover cost. The "Minimum Changeover Cost Arborescence" (MINCCA) problem consists in finding an arborescence with a given root vertex such that the total changeover cost of the internal vertices is minimized. It has been recently proved by G\"oz\"upek et al. [TCS 2016] that the problem is FPT when parameterized by the treewidth and the maximum degree of the input graph. In this article we present the following results for the MINCCA problem: - the problem is W[1]-hard parameterized by the treedepth of the input graph, even on graphs of average degree at most 8. In particular, it is W[1]-hard parameterized by the treewidth of the input graph, which answers the main open problem of G\"oz\"upek et al. [TCS 2016]; - it is W[1]-hard on multigraphs parameterized by the tree-cutwidth of the input multigraph; - it is FPT parameterized by the star tree-cutwidth of the input graph, which is a slightly restricted version of tree-cutwidth. This result strictly generalizes the FPT result given in G\"oz\"upek et al. [TCS 2016]; - it remains NP-hard on planar graphs even when restricted to instances with at most 6 colors and 0/1 symmetric costs, or when restricted to instances with at most 8 colors, maximum degree bounded by 4, and 0/1 symmetric costs.Comment: 25 pages, 11 figure

Efficacy and safety of talimogene laherparepvec versus granulocyte-macrophage colony-stimulating factor in patients with stage IIIB/C and IVM1a melanoma: subanalysis of the Phase III OPTiM trial

Objectives: Talimogene laherparepvec is the first oncolytic immunotherapy to receive approval in Europe, the USA and Australia. In the randomized, open-label Phase III OPTiM trial (NCT00769704), talimogene laherparepvec significantly improved durable response rate (DRR) versus granulocyte-macrophage colony-stimulating factor (GM-CSF) in 436 patients with unresectable stage IIIB-IVM1c melanoma. The median overall survival (OS) was longer versus GM-CSF in patients with earlier-stage melanoma (IIIB-IVM1a). Here, we report a detailed subgroup analysis of the OPTiM study in patients with IIIB-IVM1a disease. Patients and methods: The patients were randomized (2:1 ratio) to intralesional talimogene laherparepvec or subcutaneous GM-CSF and were evaluated for DRR, overall response rate (ORR), OS, safety, benefit-risk and numbers needed to treat. Descriptive statistics were used for subgroup comparisons. Results: Among 249 evaluated patients with stage IIIB-IVM1a melanoma, DRR was higher with talimogene laherparepvec compared with GM-CSF (25.2% versus 1.2%; P < 0.0001). ORR was also higher in the talimogene laherparepvec arm (40.5% versus 2.3%; P < 0.0001), and 27 patients in the talimogene laherparepvec arm had a complete response, compared with none in GM-CSF-treated patients. The incidence rates of exposure-adjusted adverse events (AE) and serious AEs were similar with both treatments. Conclusion: The subgroup of patients with stage IIIB, IIIC and IVM1a melanoma (57.1% of the OPTiM intent-to-treat population) derived greater benefit in DRR and ORR from talimogene laherparepvec compared with GM-CSF. Talimogene laherparepvec was well tolerated

Vertex Cover Kernelization Revisited: Upper and Lower Bounds for a Refined Parameter

An important result in the study of polynomial-time preprocessing shows that there is an algorithm which given an instance (G,k) of Vertex Cover outputs an equivalent instance (G',k') in polynomial time with the guarantee that G' has at most 2k' vertices (and thus O((k')^2) edges) with k' <= k. Using the terminology of parameterized complexity we say that k-Vertex Cover has a kernel with 2k vertices. There is complexity-theoretic evidence that both 2k vertices and Theta(k^2) edges are optimal for the kernel size. In this paper we consider the Vertex Cover problem with a different parameter, the size fvs(G) of a minimum feedback vertex set for G. This refined parameter is structurally smaller than the parameter k associated to the vertex covering number vc(G) since fvs(G) <= vc(G) and the difference can be arbitrarily large. We give a kernel for Vertex Cover with a number of vertices that is cubic in fvs(G): an instance (G,X,k) of Vertex Cover, where X is a feedback vertex set for G, can be transformed in polynomial time into an equivalent instance (G',X',k') such that |V(G')| <= 2k and |V(G')| <= O(|X'|^3). A similar result holds when the feedback vertex set X is not given along with the input. In sharp contrast we show that the Weighted Vertex Cover problem does not have a polynomial kernel when parameterized by the cardinality of a given vertex cover of the graph unless NP is in coNP/poly and the polynomial hierarchy collapses to the third level.Comment: Published in "Theory of Computing Systems" as an Open Access publicatio