Miracle-dz/UniFAR-FTUs huggingface dataset:
When Do Conflicts Feel Right for Prevention-Focused Individuals? The Debiasing Effect of Low Need for Closure

ABSTRACT Both lay beliefs and research findings suggest that people tend to avoid conflicts if interpersonal harmony is highly valued. Counter to this widely accepted convention, we adopt the perspective of motivated social cognition to argue that conflict avoidance is subject to the joint effect of the need for epistemic security (need for closure) and the motivation to prevent losses (prevention focus). Such effect is mediated by negative anticipation towards the consequences of confronting conflicts. Results across three studies indicated that individuals with relatively high need for closure and high prevention focus show the strongest conflict avoidance tendency due to their heightened negative anticipation. However, with low need for closure, the negative anticipation and conflict avoidance tendency of high prevention-focused individuals are weakened or even disappear. This research offers a novel theory about the mechanism of conflict avoidance. The findings about the debiasing role of low need for closure also provide rich implications for conflict resolutions.
Block-Coordinate Frank-Wolfe for Structural SVMs

We propose a randomized block-coordinate variant of the classic Frank-Wolfe algorithm for convex optimization with block-separable constraints. Despite its lower iteration cost, we show that it achieves the same convergence rate as the full Frank-Wolfe algorithm. We also show that, when applied to the dual structural support vector machine (SVM) objective, this algorithm has the same low iteration complexity as primal stochastic subgradient methods. However, unlike stochastic subgradient methods, the stochastic Frank-Wolfe algorithm allows us to compute the optimal step-size and yields a computable duality gap guarantee. Our experiments indicate that this simple algorithm outperforms competing structural SVM solvers.
Discrete Domains Mediate the Light-Responsive Nuclear and Cytoplasmic Localization of Arabidopsis COP1

The Arabidopsis CONSTITUTIVE PHOTOMORPHOGENIC1 (COP1) protein plays a critical role in the repression of photomorphogenesis during Arabidopsis seedling development. We investigated the control of COP1 partitioning between nucleus and cytoplasm, which has been implicated in the regulation of COP1 activity, by using fusion proteins between COP1 and β-glucuronidase or the green fluorescent protein. Transient expression assays using onion epidermal cells and data from hypocotyl cells of stably transformed Arabidopsis demonstrated that COP1 carries a single, bipartite nuclear localization signal that functions independently of light. Nuclear exclusion was mediated by a novel and distinct signal, bordering the zinc-finger and coiled-coil motifs, that was able to redirect a heterologous nuclear protein to the cytoplasm. The cytoplasmic localization signal functioned in a light-independent manner. Light regulation of nuclear localization was reconstituted by combining the individual domains containing the nuclear localization signal and the cytoplasmic localization signal; the WD-40 repeat domain of COP1 was not required. However, phenotypic analysis of transgenic seedlings suggested that the constitutively nuclear-localized WD-40 repeat domain was able to mimic aspects of COP1 function, as indicated by exaggerated hypocotyl elongation under light conditions.
Evolutionary Approach to Negotiation in Game AI

As modern games become more and more sophisticated graphically, so does the level of artificial intelligence that animates them thus, the larger the game budget, the more work is put into improving the AI. Unfortunately many of these games feature AIs that are standalone and do not communicate with each other, they do not try to negotiate in order to improve their individual standing. The current work focuses on analysing existing game types in order to establish types of negotiation that can be achieved between AI entities. Moreover, an evolutionary approach which focuses on achieving negotiation between these entities and tackles the problem of having multiple negotiation items with discrete values is presented.
Focused Issue: The Use of Information in Managing Supply Chains, Part 2 of 2: Coordinating Production and Delivery Under a (z, Z)-Type Vendor-Managed Inventory Contract

This paper models a type of vendor-managed inventory (VMI) agreement that occurs in practice called a (z, Z) contract. We investigate the savings due to better coordination of production and delivery facilitated by such an agreement. The optimal behavior of both the supplier and the retailer are characterized. The optimal replenishment and production policies for a supplier are found to be up-to policies, which are shown to be easily computed by decoupling the periods when the supplier outsources from those when the supplier does not outsource. A simple application of the newsvendor relation is used to define the retailer's optimal policy. Numerical analysis is conducted to compare the performance of a single supplier and a single retailer operating under a (z, Z) VMI contract with the performance of those operating under traditional retailer-managed inventory (RMI) with information sharing. Our results verify some observations made in industry about VMI and show that the (z, Z) type of VMI agreement performs significantly better than RMI in many settings, but can perform worse in others.
Alphas, Betas, and Incels: Theorizing the Masculinities of the Manosphere

Since the emergence of Web 2.0 and social media, a particularly toxic brand of antifeminism has become evident across a range of online networks and platforms. Despite multiple internal conflicts and contradictions, these diverse assemblages are generally united in their adherence to Red Pill “philosophy,” which purports to liberate men from a life of feminist delusion. This loose confederacy of interest groups, broadly known as the manosphere, has become the dominant arena for the communication of men’s rights in Western culture. This article identifies the key categories and features of the manosphere and subsequently seeks to theorize the masculinities that characterize this discursive space. The analysis reveals that, while there are some continuities with older variants of antifeminism, many of these new toxic assemblages appear to complicate the orthodox alignment of power and dominance with hegemonic masculinity by operationalizing tropes of victimhood, “beta masculinity,” and involuntary celibacy (incels). These new hybrid masculinities provoke important questions about the different functioning of male hegemony off- and online and indicate that the technological affordances of social media are especially well suited to the amplification of new articulations of aggrieved manhood.
Eecient Color Segmentation under Varying Illumination Conditions

Video-based human body tracking using color segmentation often causes problems due to movements of the object or changes in the global illumination parameters. In this paper the innuence of varying lighting conditions and large object movements in space is measured and analysed. For color segmentation an eecient technique for histogram-classiication is used. Based on the measurement results we propose a simple method to combine the histograms of several measurements which improves the segmentation. The method leads to an automatic calibration procedure which allows stable segmentation under varying lighting conditions. Finally, an application of this method to a model-based person tracking system is described.
Fitting directed graphical Gaussian models with one hidden variable

We discuss directed acyclic graph (DAG) models to represent the independence structure of linear Gaussian systems with continuous variables: such models can be interpreted as a set of recursive univariate regressions. Then we consider Gaussian models in which one of the variables is not observed and we show how the incomplete log-likelihood of the observed data can be maximized using the EM. As the EM algorithm does not provide the matrix of the second derivatives we show how to get an explicit formula for the observed information matrix. We illustrate the utility of the models with two examples.
A variable depth search algorithm with branching search for the generalized assignment problem

In this paper, we propose a variable depth search (VDS) algorithm for the generalized assignment problem (GAP), which is one of the representative combinatorial optimization problems, and is known to be NP-hard. The VDS is a generalization of the local search. The main idea of VDS is to change the size of the neighborhood adaptively so that the algorithm can effectively traverse larger search space within reasonable computational time. In our previous paper (M. Yagiura, T. Yamaguchi and T. Ibaraki, “A variable depth search algorithm for the generalized assignment problem,” Proc. 2nd Metaheuristics International Conference (MIC97), 1997 129-130 (full version is to appear in the post-conference book)), we proposed a simple VDS algorithm for the GAP, and obtained good results. To further improve the performance of the VDS, we examine the effectiveness of incorporating branching search processes to construct the neighborhoods. Various types of branching rules are examined, and it is observed that appropriate .
SURFACE at Syracuse University SURFACE at Syracuse University

Experiments were conducted to test several hypotheses on methods for improving document classification for the malicious insider threat problem within the Intelligence Community. Bag-of-words (BOW) representations of documents were compared to Natural Language Processing (NLP) based representations in both the typical and one-class classification problems using the Support Vector Machine algorithm. Results show that the NLP features significantly improved classifier performance over the BOW approach both in terms of precision and recall, while using many fewer features. The one-class algorithm using NLP features demonstrated robustness when tested on new domains.
Robotic Doorknob Disinfector

The robotic door-handle disinfector is a robotic platform that travels heavily trafficked hallways and disinfects door-handles to improve public health. Machine learning algorithms were created to help the Erratic TM robotic platform navigate hallways and identify door-handles using only a commercial webcam and a laser scanner. A parts-based and a texture-based machine learning object detector were tested in a real-world environment. With the addition of a wall-aligning motion control algorithm, the partsbased object detector consistently detected >85% of the doorknobs in the environment and false-alarmed in <1% of the image frames. The robot does not require a map of the environment nor any modification to the environment. At the conclusion of the research project, the robot can autonomously navigate hallways and disinfect with UV light to help hospitals and other heavily infectious areas achieve lower infection rates.
ROBUST BAYESIAN DETECTION OF BRAIN ACTIVATED REGIONS WITH FUNCTIONAL MRI

The functional Magnetic Resonance imaging (fMRI) is currently the most prominent method used for functional brain imaging, and it is a big step forward in the process of answering the main question asked to all the functional imaging methods: What are the brain regions involved in mediating a specific brain function? And thought the fMRI’s obvious qualities have allowed for its fast acceptance and development, its limitations are far from letting this question to become a "closed problem". The fMRI experiments usually look for the change in blood oxygenation and blood volume resulting from altered neural activity. This signal, called blood-oxygenation-leveldependent (BOLD), results from the endogenous paramagnetic contrast property of the deoxygenated hemoglobin. Hence, increased blood flow reduces the local concentration of deoxygenated hemoglobin causing an increase in the MR signal on a T2*-weighted image [1]. It is commonly accepted, and has been empirically proved, that there is a strong correlation between neural activity and the vascular response that leads to the consequent increase of this BOLD signal citation. This relation, know as the hemodynamic response function (HRF), is at the core of fMRI data analysis. Inferences about which brain regions are involved in the particular stimulated cognitive and sensorimotor functions are based on how well the BOLD signal correlates with this stimulation, mediated by the HRF. Contrary to the impression one might get in a brief review of the literature, there are not many ways to analyze fMRI time-series with a diversity of statistical and conceptual approaches. In fact, with very few exceptions, every analysis is a variant of the general linear model (GLM), that expresses the observed response variable in
Negative Life Events Scale for Students (NLESS).

Rationale is presented for the derivation of a new measure of stressful life events for use with students [Negative Life Events Scale for Students (NLESS)]. Ten stressful life events questionnaires were reviewed, and the more than 600 items mentioned in these scales were culled based on the following criteria: (a) only long-term and unpleasant events were retained, (b) duplicates were eliminated, and (c) items measuring the same event domain were combined to form one item. The NLESS provides the following measures of negative life event stress: (a) normative scoring, (b) subjective scoring, (c) recent versus distal events, and (d) total number of events experienced.
Automatic Identification of Chinese Prepositional Phrase Including Verbs

In this paper, with the help of corpus which was changed by the Harbin Institute of Technology Information Retrieval Laboratory's Chinese dependency-based Treebank and by using the parser MaltParser as an implementation tool, this paper proposed and implementation a Chinese dependency parsing algorithm, in order to effectively identify the right boundary of the prepositional phrases that contains a verb. Empirical results show that this algorithm has improved the error when analyze the prepositional phrase containing a verb.
Wykorzystanie wybranych aspektów teorii integralnej w kreowaniu nowego podejścia do przywództwa

This article set the cognitive aim relating to the applications of Integral Theory and the concept of Spiral Dynamics in the field of leadership. Taken considerations are subordinated to the problem of using the above theory and concepts in contemporary leadership, indicating the benefits arising from their use. The implementation of the aim took place using study literature. The literature research suggests that the use of Integral Theory in relation to leadership allows for a holistic view on the investigated issue from four perspectives (quadrants) and the introduction of the so-called the developmental perspective (levels and lines) defining the stages of development leader. Integral Theory offers leaders a “map”, which facilitates the understanding of a complex reality, the complexity of the people, which it directs, and their world and challenges that they face. This allows leaders to develop a way to improve their own competence, as well as is a source of inspiration and knowledge how to motivate others.
Modeling the Economic Interaction of Agents With Diverse Abilities to Recognize Equilibrium Patterns

We model differences among agents in their ability to recognise temporal patterns of prices. Using the concept of DeBruijin sequences in two dynamic models of markets, we demonstrate the existence of equilibria in which prices fluctuate in a pattern that is independent of the fundamentals and that can be recognised only by the more competent agents.
In Defense of Genopolitics

The American Political Science Review recently published a critique of an article we published in the Journal of Politics in 2008. In that article we showed that variants of the genes 5HTT and MAOA were significantly associated with voter turnout in a sample of 2,300 subjects from the National Longitudinal Study of Adolescent Health. Here, we address the critique first by conducting a replication study using an independent sample of 9,300 subjects. This study replicates the gene-environment interaction of the 5HTT gene variant with church attendance, but not the association with MAOA. We then focus on the general argument of the critique, showing that many of its characterizations of the literature in genetics and in political science are misleading or incorrect. We conclude by illustrating the ways in which genopolitics has already made a lasting contribution to the field of political science and by offering guidelines for future studies in genopolitics that are based on state-of-the-art recommendations from the field of behavior genetics.
Markerless view independent gait analysis with self-camera calibration

We present a new method for viewpoint independent markerless gait analysis. The system uses a single camera, does not require camera calibration and works with a wide range of directions of walking. These properties make the proposed method particularly suitable for identification by gait, where the advantages of completely unobtrusiveness, remoteness and covertness of the biometric system preclude the availability of camera information and use of marker based technology. Tests on more than 200 video sequences with subjects walking freely along different walking directions have been performed. The obtained results show that markerless gait analysis can be achieved without any knowledge of internal or external camera parameters and that the obtained data that can be used for gait biometrics purposes. The performance of the proposed method is particularly encouraging for its appliance in surveillance scenarios.
The nature and rate of cognitive maturation from late childhood to adulthood

To better understand the nature and rate of cognitive change across adolescence, the Cogstate Brief Battery (CBB) was utilized to assess psychomotor function, attention, working memory, and visual learning in individuals aged 10–18 years old. Since all CBB tasks have equivalent perceptual, motor, and linguistic demands as well as being appropriate for both children and adults, this approach allowed direct across-age comparison of multiple cognitive domains. Exponential decreases in reaction time and linear increases in accuracy were observed across adolescent development in a cross-sectional sample of 38,778 individuals and confirmed in a 5788 individual longitudinal sample with 1-year repeat assessments. These results have important implications for the repeated assessment of cognition during development where expected maturational changes in cognition must be accounted for during cognitive testing.
Expanding Science and Technology Thesauri from Bibliographic Datasets Using Word Embedding

The use of thesauri and taxonomies for science and technology information in scientometrics has been attracting attention. However, manual construction and maintenance of thesauri is expensive and requires significant time, thus, methods for semi-automatic construction and maintenance are being actively studied. We propose a method to expand an existing thesaurus using the abstracts of articles from state-of-the-art technological domains with limited structured information. Specifically, we consider a method for properly allocating new terms to the hierarchical structures of an existing thesaurus using rapidly evolving word embedding. In an experiment, word vectors of 500 degrees are constructed from 567,000 biomedical articles and are clustered after dimension reduction using principal component analysis. Then, semantic relations are estimated based on the spatial relations between the new term and any of the terms in the thesaurus. We then conducted a comparison of the results obtained from three experts. In future, we will develop a recommendation system for new terms related to the existing terms to support semi-automatic thesaurus maintenance.
Monoamine Oxidase-A in Borderline Personality Disorder and Antisocial Personality Disorder

Monoamine oxidase A (MAO-A) is a brain enzyme that serves several physiologic functions, including metabolism of monoamine neurotransmitters and induction of pro-apoptotic signaling pathways. Increased brain MAO-A level is present in clinical disorders characterized by low mood states, whereas decreased brain MAO-A level is associated with higher trait impulsivity and aggression in healthy volunteers. Borderline personality disorder (BPD) and antisocial personality disorder (ASPD) are common psychiatric conditions that exact a high healthcare and societal burden. BPD is associated with acute episodes of severe dysphoria, and ASPD presents high levels of impulsivity and aggression. The overall aim of the thesis was to investigate MAOA brain level in BPD and ASPD. The first experiment used [C] harmine positron emission tomography (PET) to assess MAO-A total distribution volume (MAO-A VT), an index of MAO-A density, in females with BPD. Our results showed that MAO-A VT was elevated in the prefrontal cortex (PFC) and anterior cingulate cortex (ACC) of severe BPD compared to control groups. Greater PFC and ACC MAO-A VT was additionally associated with more severe mood symptoms and suicidality in BPD. The second experiment applied [C] harmine PET to examine MAO-A VT in
Analysis Of Interest Points Of Curvelet Coefficients Contributions Of Microscopic Images And Improvement Of Edges

This paper focuses on improved edge model based on Curvelet coefficients analysis. Curvelet transform is a powerful tool for multiresolution representation of object with anisotropic edge. Curvelet coefficients contributions have been analyzed using Scale Invariant Feature Transform (SIFT), commonly used to study local structure in images. The permutation of Curvelet coefficients from original image and edges image obtained from gradient operator is used to improve original edges. Experimental results show that this method brings out details on edges when the decomposition scale increases.
Automatic Image Annotations by Mining Web Image Data

The exponential growth of Web images has created a compelling need for innovative methods to retrieve and manage them. Automatic image annotation is an effective way for resolving this problem. In this paper, we propose a novel system that automatically annotates images by semantic corpus which is constructed by mining Web image data. It includes three parts: 1) Constructing the semantic annotation corpus by mining 413,006 Web images and their surrounding text collected from several image search engine; 2) Searching for visually similar images in this semantic annotation corpus and extracting candidate annotation terms; 3) Ranking candidate annotation terms to filter out noisy ones. Our system is evaluated using two benchmark image datasets. Experimental results indicate that this approach is effective.
Introduction of multiphosphonate ligand to peptide nucleic acid for metal ion conjugation

Peptide nucleic acid (PNA) is one of the most widely used synthetic DNA analogs. Conjugation of functional molecules to PNA is very effective to further widen its potential applications. For this purpose, here we report the synthesis of several ligand monomers and introduced them to PNA. These ligand-modified PNAs attract cerium ion and are useful for site-selective DNA hydrolysis. It should be noted that these ligands on PNA are also effective even under the conditions of invasion complex.