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Testing the qIAT as A Measure of Implicit Self-Criticism

Materials, data and analysis scripts accompanying Indirect Assessment of Beliefs About the Self: Implicit Self-Criticism, A doctoral dissertation submitted to Ben-Gurion University of the Negev by Michael Pinus, November 2020. The repository contains materials, analysis scripts, and data of five validation studies of indirect measures of self-criticism.

Let $[n]$ denote $\{0,1, ... , n-1\}$. A polynomial $f(x) = \sum a_i x^i$ is a Littlewood polynomial (LP) of length $n$ if the $a_i$ are $\pm 1$ for $i \in [n]$, and $a_i = 0$ for $i \ge n$. Such an LP is said to have order $m$ if it is divisible by $(x-1)^m$. The problem of finding the set $L_m$ of lengths of LPs of order $m$ is equivalent to finding the lengths of spectral-null codes of order $m$, and to finding $n$ such that $[n]$ admits a partition into two subsets whose first $m$ moments are equal. Extending the techniques and results of Boyd and others, we completely determine $L_7$ and $L_8$ and prove that 192 is the smallest element of $L_9$. Our primary tools are the use of carefully targeted searches using integer linear programming (both to find LPs and to disprove their existence for specific $n$ and $m$), and an unexpected new concept (that arose out of observed symmetry properties of LPs) that we call "regenerative pairs," which produce infinite arithmetic progressions in $L_m$. We prove that for $m \le$ 8, whenever there is an LP of length $n$ and order $m$, there is one of length $n$ and order $m$ that is symmetric (resp.~antisymmetric) if m is even (resp.~odd)., Comment: 15 pages, 1 figure

Recent works in personality and psychopathology emphasize both trait and state self-criticism as transdiagnostic risk factors for mental disorders. Yet, common screening and intake measures do not include assessment of state self-criticism. We provide a reanalysis of data from nine samples (total N=1,442), with the aim to identify and validate a state self-criticism subscale within the Brief Symptoms Inventory (BSI), a popular and extensively researched instrument for the assessment of general and specific psychopathology. We identified four potential state self-criticism subscales, comprising three to five items, tapping the experience of self-criticism. All state self-criticism subscales demonstrated good internal consistency and test-retest reliability. In addition, all subscales were highly correlated with psychopathology and low psychological well-being, thus suggesting strong convergent validity. Furthermore, all subscales demonstrated incremental predictive validity, when predicting psychological distress, depression, brooding and suicidal ideations, above and beyond trait self-criticism. Interestingly, our results show no clear advantage for one subscale over the others. Findings contribute to contemporary personality science, attesting to the importance of assessing personality on both trait and state features. We discuss clinical implications and offer clinicians a brief alternative to longer screening methods, focusing on currently 'inflamed' and distressing aspects of experience, namely the self-critical experience.

As the world views, incredulously, the calamitous consequences of the COVID-19 pandemic, the inseparable connections between body and mind become more and more apparent, even for the heretics (i.e., biological determinists). Such realizations also bolster the understanding of the close link between medical conditions and psychopathology. Launched prior to the COVID-19 epidemic, this special issue sets out to illuminate the prevalence, course, etiology, and responses to a myriad of psychopathological conditions in medical conditions. The 13 articles in this special issue address a variety of medical conditions (chronic illness and chronic pain, Pica, cancer, acute delirium, factitious disorders, functional neurological symptoms, sleep disorders, fetal conditions), mental disorders (depression, anxiety, suicidality, eating disorders, personality disorders, PTSD), medical settings (primary care vs. specialty clinics), and developmental levels (children, adolescents, and adults). The overarching theme emanating from reading these articles is that clinical-health psychology, or clinical psychology in medical settings, is an ever-needed field of inquiry, epitomizing interdisciplinarity and science/practice integration.

Supplemental Material, Revisiting_the_Effects_of_Societal_Threat_Perceptions_on_Conflict-Related_Political_Positions-final_JCR for Revisiting the Effects of Societal Threat Perceptions on Conflict-related Positions: A Three-wave Study by Julia Elad-Strenger, and Golan Shahar in Journal of Conflict Resolution

Constraint Satisfaction Problems (CSPs) are ubiquitous in computer science and specifically in AI. This paper presents a method of solving the counting problem for a wide class of CSPs using generating polynomials. Analysis of our method shows that it is much more efficient than the classic dynamic programming approach. For example, in the case of #SAT, our algorithm improves a result of Samer and Szeider. The presented algorithms mostly use algebraic operations on multivariate polynomials, which allows application of known optimizations and makes it possible to use existing software to implement them easily.

Minesweeper is a popular single player game. Various strategies have been suggested in order to improve the probability of winning the game. In this paper, we present an optimal strategy for playing Minesweeper on a graph when it is known that exactly one cell is mined.

A configuration management database (CMDB) can be considered to be a large graph representing the IT infrastructure entities and their interrelationships. Mining such graphs is challenging because they are large, complex, and multi-attributed and have many repeated labels. These characteristics pose challenges for graph mining algorithms, due to the increased cost of subgraph isomorphism (for support counting) and graph isomorphism (for eliminating duplicate patterns). The notion of pattern frequency or support is also more challenging in a single graph, since it has to be defined in terms of the number of its (potentially, exponentially many) embeddings. We present CMDB-Miner, a novel two-step method for mining infrastructure patterns from CMDB graphs. It first samples the set of maximal frequent patterns and then clusters them to extract the representative infrastructure patterns. We demonstrate the effectiveness of CMDB-Miner on real-world CMDB graphs, as well as synthetic graphs.

Minesweeper is a popular single player game. It has been shown that the Minesweeper consistency problem is NP-complete and the Minesweeper counting problem is #P-complete. In this paper, we present efficient algorithms for solving these problems for Minesweeper graphs with bounded treewidth. Our algorithms turn out to be much better than those based directly on dynamic programming. The algorithms mostly use of algebraic operations on multivariate polynomials, so that one may use existing software to implement them easily.

Let N* q (m) be the minimal positive integer N, for which there exists a splitting of the set [0,N - 1] into q subsets, So, S 1, ..., S q-1 , whose first m moments are equal. Similarly, let m* q (N) be the maximal positive integer m, such that there exists a splitting of [0, N-1] into q subsets whose first m moments are equal. For q = 2, these functions were investigated by several authors, and the values of N* 2 (m) and m* 2 (N) have been found for m < 8 and N < 167, respectively. In this paper, we deal with the problem for any prime q. We demonstrate our methods by finding m* 3 (N) for any N < 90 and N* 3 (m) for m < 6.

The item cold-start problem is of a great importance in collaborative filtering (CF) recommendation systems. It arises when new items are added to the inventory and the system cannot model them properly since it relies solely on historical users' interactions (e.g., ratings). Much work has been devoted to mitigate this problem mostly by employing hybrid approaches that combine content-based recommendation techniques or by devoting a portion of the user traffic for exploration to gather interactions from random users. We focus on pure CF recommender systems (i.e., without content or context information) in a realistic online setting, where random exploration is inefficient and smart exploration that carefully selects users is crucial due to the huge flux of new items with short lifespan. We further assume that users arrive randomly one after the other and that the system has to immediately decide whether the arriving user will participate in the exploration of the new items. For this setting we present ExcUseMe, a smart exploration algorithm that selects a predefined number of users for exploring new items. ExcUseMe gradually excavates the users that are more likely to be interested in the new items and models the new items based on the users' interactions. We evaluated ExcUseMe on several datasets and scenarios and compared it to state-of-the-art algorithms. Experimental results indicate that ExcUseMe is an efficient algorithm that outperforms all other algorithms in all tested scenarios.

It is well known that collaborative filtering (CF) based recommender systems provide better modeling of users and items associated with considerable rating history. The lack of historical ratings results in the user and the item cold-start problems. The latter is the main focus of this work. Most of the current literature addresses this problem by integrating content-based recommendation techniques to model the new item. However, in many cases such content is not available, and the question arises is whether this problem can be mitigated using CF techniques only. We formalize this problem as an optimization problem: given a new item, a pool of available users, and a budget constraint, select which users to assign with the task of rating the new item in order to minimize the prediction error of our model. We show that the objective function is monotone-supermodular, and propose efficient optimal design based algorithms that attain an approximation to its optimum. Our findings are verified by an empirical study using the Netflix dataset, where the proposed algorithms outperform several baselines for the problem at hand., Comment: 11 pages, 2 figures

Let N*(m) be the minimal length of a polynomial with ±1 coefficients divisible by (x-1) m . Byrnes noted that N*(m) < 2 m for each m, and asked whether in fact N*(m) = 2 m . Boyd showed that N*(m) = 2 m for all m < 5, but N*(6) = 48. He further showed that N*(7) = 96, and that AT*(8) is one of the 5 numbers 96,144,160,176, or 192. Here we prove that N*(8) = 144. Similarly, let m*(N) be the maximal power of (x - 1) dividing some polynomial of degree N - 1 with ±1 coefficients. Boyd was able to find m*(N) for N < 88. In this paper we determine m*(N) for N < 168.

A configuration management database (CMDB) can be considered to be a large graph representing the IT infrastructure entities and their inter-relationships. Mining such graphs is challenging because they are large, complex, and multi-attributed, and have many repeated labels. These characteristics pose challenges for graph mining algorithms, due to the increased cost of sub graph isomorphism (for support counting), and graph isomorphism (for eliminating duplicate patterns). The notion of pattern frequency or support is also more challenging in a single graph, since it has to be defined in terms of the number of its (potentially, exponentially many) embeddings. We present CMDB-Miner, a novel two-step method for mining infrastructure patterns from CMDB graphs. It first samples the set of maximal frequent patterns, and then clusters them to extract the representative infrastructure patterns. We demonstrate the effectiveness of CMDB-Miner on real-world CMDB graphs.

We propose a new IT automation technology for configuration management: automatic baseline policy extraction out of the Configuration Management Data Base (CMDB). Whereas authoring a configuration policy rule manually is time consuming and unlikely to realize the actual state of the configurations in the overall organization, this new approach summarizes the de-facto configurations from the data. IT staff, instead of authoring the policy rule, is required to simply validate and possibly enhance the automatically extracted policy. Our technology applies data-mining to organization's configuration assets in the CMDB, and automatically identifies repeating structures of compound configurations. Based on these repeating structures, we build policy rules for compound configuration items. The heart of our technique is a new distance measure we introduce between the configuration assets, whose computation is reduced to a minimum-cost flow problem.

Batrachochytriumdendrobatidis (Bd) is a globally ubiquitous fungal infection that has emerged to become a primary driver of amphibian biodiversity loss. Despite widespread effort to understand the emergence of this panzootic, the origins of the infection, its patterns of global spread, and principle mode of evolution remain largely unknown. Using comparative population genomics, we discovered three deeply diverged lineages of Bd associated with amphibians. Two of these lineages were found in multiple continents and are associated with known introductions by the amphibian trade.We found that isolates belonging to one clade, the global panzootic lineage (BdGPL) have emerged across at least five continents during the 20th century and are associated with the onset of epizootics in North America, Central America, the Caribbean, Australia, and Europe. The two newly identified divergent lineages, Cape lineage (BdCAPE) and Swiss lineage (BdCH), were found to differ in morphological traits when compared against one another and BdGPL, and we show that BdGPL is hypervirulent. BdGPL uniquely bears the hallmarks of genomic recombination, manifested as extensive intergenomic phylogenetic conflict and patchily distributed heterozygosity. Wepostulate that contact between previously genetically isolated allopatric populations of Bd may have allowed recombination to occur, resulting in the generation, spread, and invasion of the hypervirulent BdGPL leading to contemporary disease-driven losses in amphibian biodiversity.

Mitochondrial evolution has given rise to a complex array of organelles, ranging from classical aerobic mitochondria to mitochondrial remnants known as hydrogenosomes and mitosomes. The latter are found in anaerobic eukaryotes, and these highly derived organelles often retain only scant evidence of their mitochondrial origins. Intermediate evolutionary stages have also been reported as facultatively or even strictly anaerobic mitochondria, and hydrogenosomes that still retain some mitochondrial features. However, the diversity among these organelles with transitional features remains rather unclear and barely studied. Here, we report the sequence, structure, and gene content of the mitochondrial DNA of the anaerobic stramenopile Proteromonas lacertae. It has a linear genome with a unique central region flanked by two identical large inverted repeats containing numerous genes and "telomeres'' with short inverted repeats. Comparison with the organelle genome of the strictly anaerobic human parasite Blastocystis reveals that, despite the close similarity of the sequences, features such as the genome structure display striking differences. It remains unclear whether the virtually identical gene repertoires are the result of convergence or descent.