Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic Globalization and the Welfare State in Affluent Democracies, 1975–2001

Previous scholarship is sharply divided over how or if globalization influences welfare states. The effects of globalization may be positive causing expansion, negative triggering crisis and reduction, curvilinear contributing to convergence, or insignificant. We bring new evidence to bear on this debate with an analysis of three welfare state measures and a comprehensive array of economic globalization indicators for 17 affluent democracies from 1975 to 2001. The analysis suggests several conclusions. First, state-of-the-art welfare state models warrant revision in the globalization era. Second, most indicators of economic globalization do not have significant effects, but a few affect the welfare state and improve models of welfare state variation. Third, the few significant globalization effects are in differing directions and often inconsistent with extant theories. Fourth, the globalization effects are far smaller than the effects of domestic political and economic factors. Fifth, the effects of globalization are not systematically different between European and non-European countries, or liberal and non-liberal welfare regimes. Increased globalization and a modest convergence of the welfare state have occurred, but globalization does not clearly cause welfare state expansion, crisis, and reduction or convergence. Ultimately, this study suggests skepticism toward bold claims about globalization's effect on the welfare state.
Prediction of Protein Function Using Graph Container and Message Passing

We introduce a novel parameter called container flux, which is used to measure the information sharing capacity between two distinct nodes in a graph. Other useful information, both from gene expression or protein interaction test, can be readily incorporated into our container flux. Also, contain flux is a proper candidate for describing the multi-path communication effect caused by large amount of short pathways in real protein networks. In our test, we find there are usually 3∼15 pathways consisted of less than 4 edges, between two different proteins in the network built from Baker’s Yeast. We also formulate a new equation for protein function prediction by integrating the container flux as an information sharing component. Based on the scale-free characteristic of protein interaction network, we propose that these proteins of high degree would most likely to be the exemplars for difference clusters. By further exploration, we reveal an interesting consistency between the global optimization of our prediction equation and the exemplar guided clustering problems. we adopt a log-space version of sumproduct algorithm, a well-established algorithm called affinity propagation, to approximately solve our optimization problem. At the end, we assign every member of the same cluster with the exemplar’s functions. The exemplar-representing assumption is strongly supported by our preliminary experimental results.
FLUORINATED 2-(4-AMINO-3-METHYLPHENYL)BENZOTHIAZOLES INDUCE CYP1A1 EXPRESSION, BECOME METABOLIZED, AND BIND TO MACROMOLECULES IN SENSITIVE HUMAN CANCER CELLS

Fluorinated 2-(4-amino-3-methylphenyl)benzothiazoles possess potent antiproliferative activity against certain cancer cells, similar to the unfluorinated 2-(4-amino-3-methylphenyl)benzothiazole (DF 203, NSC 674495). In “sensitive” cancer cells, DF 203 is metabolized by, can induce expression of, and binds covalently to CYP1A1. Metabolism appears to be essential for its antiproliferative activity through DNA adduct formation. However, a biphasic dose-response relationship compromises its straightforward development as a chemotherapeutic agent. We investigated whether fluorinated benzothiazoles inhibit cancer cell growth without the biphasic dose-response, and whether the fluorinated benzothiazoles are also metabolized into reactive species, with binding to macromolecules in sensitive cancer cells. One fluorinated benzothiazole, 2-(4-amino-methylphenyl)-5-fluorobenzothiazole (5F 203, NSC 703786) did exhibit potent, antiproliferative activity without a biphasic dose-response. The fluorinated benzothiazoles were also metabolized only in cells, which subsequently showed evidence of cell death. We used microsomes from genetically engineered human B-lymphoblastoid cells expressing cytochromes P450 (CYP1A1, CYP1A2, or CYP1B1) to clarify the basis for fluorinated benzothiazole metabolism. 5F 203 induced CYP1A1 and CYP1B1 mRNA expression in sensitive breast and renal cancer cells, whereas 5F 203 induced CYP1A1 mRNA but not CYP1B1 mRNA expression in sensitive ovarian cancer cells. 5F 203 did not induce CYP1A1 or CYP1B1 mRNA expression in any “resistant” cancer cells. The fluorinated benzothiazoles induced CYP1A1 protein expression exclusively in sensitive cells. [14C]5F 203 bound substantially to subcellular fractions in sensitive cells but only minimally in resistant cells. These data are concordant with the antiproliferative activity of fluorinated benzothiazoles deriving from their ability to become metabolized and bind to macromolecules within sensitive cells.
The measurement of strategy convergence for reinforcement learning in discrete state space

The concept of entropy is introduced into reinforcement learning. The definitions of the local strategy entropy and global strategy entropy are proposed. The global strategy entropy is proved to be the quantitative problem independent measurement of the learning progress, i.e. the convergence degree of the strategy. To improve the learning performance, reinforcement learning with self-adaptive learning rate is proposed based on the strategy entropy. The experimental results show that learning based on the local strategy entropy has better learning performance than those with fixed learning rates.
IRIS: a new reclaiming algorithm for server-based real-time systems

In this paper we present a new algorithm for CPU resource reservation in real-time systems that allows the coexistence of hard, soft and non real-time tasks. The proposed algorithm is specifically designed to handle computational overload. A task that needs more CPU-time than reserved can reuse the spare bandwidth, without interfering with the others tasks. With respect to other reclamation schemes, the novelty of the proposed algorithm is that the spare bandwidth is fairly distributed among the needing servers. The effectiveness of the algorithm is demonstrated with an extensive set of experiments. We also propose a methodology to set scheduling parameters depending on the type of the task and on the time constraints needed.
Src Regulates the Activity of the ING1 Tumor Suppressor

The INhibitor of Growth 1 (ING1) is stoichiometric member of histone deacetylase (HDAC) complexes and functions as an epigenetic regulator and a type II tumor suppressor. It impacts cell growth, aging, apoptosis, and DNA repair, by affecting chromatin conformation and gene expression. Down regulation and mislocalization of ING1 have been reported in diverse tumor types and Ser/Thr phosphorylation has been implicated in both of these processes. Here we demonstrate that both in vitro and in vivo, the tyrosine kinase Src is able to physically associate with, and phosphorylate ING1, which results in a nuclear to cytoplasmic relocalization of ING1 in cells and a decrease of ING1 stability. Functionally, Src antagonizes the ability of ING1 to induce apoptosis, most likely through relocalization of ING1 and down regulation of ING1 levels. These effects were due to both kinase-dependent and kinase-independent properties of Src, and were most apparent at elevated levels of Src expression. These findings suggest that Src may play a major role in regulating ING1 levels during tumorigenesis in those cancers in which high levels of Src expression or activity are present. These data represent the first report of tyrosine kinase-mediated regulation of ING1 levels and suggest that kinase activation can impact chromatin structure through the ING1 epigenetic regulator.
Systematics of Hypanartia ( Lepidoptera : Nymphalidae : Nymphalinae ) , with a test for geographical speciation mechanisms in the Andes

A taxonomic review of the Neotropical nymphaline butter ̄y genus Hypanartia HuÈbner is presented, including notes on the taxonomy, biology and distribution of its component species, illustrations of all taxa and the male genitalia of all species, and the description of four new species and two new subspecies: Hypanartia celestia sp.n. , H. cinderella sp.n. , H. dione disjuncta ssp.n. , H. fassli sp.n. , H. trimaculata sp.n. and H. trimaculata autumna ssp.n. Hypanartia arcaei (Salvin) is placed as a subspecies of H. dione (Latreille) (stat.n.) and lectotypes are designated for eight nominal taxa. Fourteen species are recognized, with the centre of diversity being in high Andean cloud forest habitats. A cladistic analysis was conducted, based on ®fty-three illustrated characters of male genitalic and abdominal morphology, and external facies, to investigate phylogenetic relationships. The resulting phylogenetic hypothesis was used to test four different geographical mechanisms of speciation in the Andes: colonization from temperate latitudes, speciation across elevational gradients, radiation within the Andes and allopatric speciation between the Andes and other montane regions. There is evidence that speciation across an elevational gradient occurred twice, both times into elevations largely unoccupied by the genus, and in both cases followed by subsequent, elevationally sympatric, in situ radiation. Differentiation in allopatry between montane regions has apparently been of recent in ̄uence only, causing infraspeci®c variation in two species. These results parallel several recent studies of Andean bird speciation.
A P ] 2 8 M ay 2 00 8 Adaptive design of supercomputer experiments

Computer experiments are often performed to allow modeling of a response surface of a physical experiment that can be too costly or difficult to run except using a simulator. Running the experiment over a dense grid can be prohibitively expensive, yet running over a sparse design chosen in advance can result in obtaining insufficient information in parts of the space, particularly when the surface calls for a nonstationary model. We propose an approach that automatically explores the space while simultaneously fitting the response surface, using predictive uncertainty to guide subsequent experimental runs. The newly developed Bayesian treed Gaussian process is used as the surrogate model, and a fully Bayesian approach allows explicit measures of uncertainty. We develop an adaptive sequential design framework to cope with an asynchronous, random, agent–based supercomputing environment, by using a hybrid approach that melds optimal strategies from the statistics literature with flexible strategies from the active learning literature. The merits of this approach are borne out in several examples, including the motivating computational fluid dynamics simulation of a rocket booster.
An Audit Method Based on Mathematical Statistics Detection in Database Audit System

According to the method of database audit and the characteristics of current data, this paper design an audit method based on mathematical statistics detection for the audit of database and the control of risk. Through making statistical analysis to user's behavior, system will generate user's normal behavior module used in database audit system. This method based on memory mathematical statistics, and on the premise of using hash tables as user's indexes, it also uses AVL tree to store audit object's indexes for making it easy to do statistics and configure audit rules. When generating audit rules, this paper uses weighted calculation. By setting appropriate parameters to adjust the role each factor in generating rules, it will generate rules more conforming to the requirements.
eaction-centric modeling of microbial ecosystems

The growth of microbial populations catalyzing biochemical reactions leads to positive feedback loops and self-amplifying process dynamics at ecosystem scales. Hence, the state of a biocatalyzed process is not completely determined by its physicochemical state, but also depends on current cell or enzyme concentrations that are often unknown. Here we propose a generic approach to modeling reaction networks of natural and engineered microbial ecosystems, that is able to capture the self-amplifying nature of biochemical reactions without explicit reference to the underlying microbial populations. This is achieved by keeping track of a system’s “capacity” to perform particular reactions, rather than the cell populations actually catalyzing them. Our reaction-centric approach minimizes the need for cell-physiological parameters such as yield factors and provides a suitable framework for describing a system’s dynamics purely in terms of chemical concentrations and fluxes. We demonstrate our approach using data from an incubation experiment involving urea hydrolysis and nitrification, as well as time series from a longterm nitrifying bioreactor experiment. We show that reaction-centric models can capture the dynamical character of microbially catalyzed reaction kinetics and enable the reconstruction of bioprocess states using solely chemical data, hence reducing the need for laborious biotic measurements in environmental and industrial process monitoring. © 2016 Elsevier B.V. All rights reserved.
Markov Models of Amino Acid Substitution to Study Proteins with Intrinsically Disordered Regions

Background Intrinsically disordered proteins (IDPs) or proteins with disordered regions (IDRs) do not have a well-defined tertiary structure, but perform a multitude of functions, often relying on their native disorder to achieve the binding flexibility through changing to alternative conformations. Intrinsic disorder is frequently found in all three kingdoms of life, and may occur in short stretches or span whole proteins. To date most studies contrasting the differences between ordered and disordered proteins focused on simple summary statistics. Here, we propose an evolutionary approach to study IDPs, and contrast patterns specific to ordered protein regions and the corresponding IDRs. Results Two empirical Markov models of amino acid substitutions were estimated, based on a large set of multiple sequence alignments with experimentally verified annotations of disordered regions from the DisProt database of IDPs. We applied new methods to detect differences in Markovian evolution and evolutionary rates between IDRs and the corresponding ordered protein regions. Further, we investigated the distribution of IDPs among functional categories, biochemical pathways and their preponderance to contain tandem repeats. Conclusions We find significant differences in the evolution between ordered and disordered regions of proteins. Most importantly we find that disorder promoting amino acids are more conserved in IDRs, indicating that in some cases not only amino acid composition but the specific sequence is important for function. This conjecture is also reinforced by the observation that for of our data set IDRs evolve more slowly than the ordered parts of the proteins, while we still support the common view that IDRs in general evolve more quickly. The improvement in model fit indicates a possible improvement for various types of analyses e.g. de novo disorder prediction using a phylogenetic Hidden Markov Model based on our matrices showed a performance similar to other disorder predictors.
The Relationship Between Briefly Induced Affect and Cognitive Control Processes: An Event-Related Potential (ERP) Study

The Relationship Between Briefly-Induced Affect and Cognitive Control Processes: An Event-Related Potential (ERP) Study Hilary Anne Smith Department of Psychology, BYU Master of Science Positive affect is generally associated with improvements in cognitive abilities; however, few studies have addressed positive affect and its relation to specific cognitive control processes. Previous research suggests positive affect conditions are more flexible/distractible states, suggesting cognitive control processes are perhaps decreased in context maintenance and increased in conflict detection/resolution. To measure the cognitive control processes, specific components of the scalp-recorded event-related potentials (ERPs) called the cue slow wave (context maintenance), the N450 (conflict detection), and conflict SP (conflict resolution) were acquired in response to an affective single-trial, cued-Stroop task. Participants were presented with pleasant, neutral, and unpleasant images prior to Stroop instruction (i.e., respond to “color” or “word”) and response. Participants had greater accuracy during the pleasant condition when given a longer delay for extra time to process the high conflict task, t(36) = 3.09, p = . 004, 95% CI (0.07, 0.02) compared to the unpleasant condition. Additionally, the unpleasant condition resulted in greater context maintenance than pleasant (increased cue-related slow wave amplitude; t(40) = 2.38, p = . 02). Unpleasant conditions were associated with greater conflict resolution processes (as measured by the conflict SP) with high conflict trials, t(40) = 2.55, p = . 015; whereas pleasant did in congruent trials, t(40) = 2.707, p = . 010. Findings suggest negative affective states increase participants’ focus on the task in avoidance of the distracting unpleasant picture. Our findings lay the foundation for understanding the differences between state and trait affect on cognitive control processes.
Hierarchical Convex Approximation of 3D Shapes for Fast Region Selection

Given a 3D solid model S represented by a tetrahedral mesh, we describe a novel algorithm to compute a hierarchy of convex polyhedra that tightly enclose S. The hierarchy can be browsed at interactive speed on a modern PC and it is useful for implementing an intuitive feature selection paradigm for 3D editing environments. Convex parts often coincide with perceptually relevant shape components and, for their identification, existing methods rely on the boundary surface only. In contrast, we show that the notion of part concavity can be expressed and implemented more intuitively and efficiently by exploiting a tetrahedrization of the shape volume. The method proposed is completely automatic, and generates a tree of convex polyhedra in which the root is the convex hull of the whole shape, and the leaves are the tetrahedra of the input mesh. The algorithm proceeds bottom‐up by hierarchically clustering tetrahedra into nearly convex aggregations, and the whole process is significantly fast. We prove that, in the average case, for a mesh of n tetrahedra O(n log2 n) operations are sufficient to compute the whole tree.
A Literature Review of Research on Facebook Use

This paper represents a review of more than one hundred studies on the social networking website Facebook. An initial selection has been made and has led to the identification of eight main research themes: effects on the users, friendship, construction of impressions, privacy, use, Facebook and politics, self-expression and construal, social capital, and the merging of social spheres. This paper focuses on Facebook use, which is currently the most researched theme. How do individuals use Facebook and why? Six different categories are identified: initiating and maintaining relationships, learning about others, recognition, personality and willingness to communicate, social influence, and experience. The major studies for each category are presented, with an emphasis on the most influential ones in the field. The focus of this literary review is on the commonalities and differences that arise from the results. Hypotheses are presented when possible, and a few theoretical explanations are provided. As a result, one could notice that Facebook is mainly used to keep in touch with other people, but not in a conventional way as users tend to 'spy' on other users' profiles. This phenomenon leads to a growing exhibitionism, which is in turn related to individuals' personality traits. Use of Facebook is also influenced by peers and experience with the website. A few limitations are discussed, and gender is found to be a possible factor influencing Facebook use. Suggestions for further study are provided.
Enzymatically Modified Starch Favorably Modulated Intestinal Transit Time and Hindgut Fermentation in Growing Pigs

Aside from being used as stabilizing agents in many processed foods, chemically modified starches may act as functional dietary ingredients. Therefore, development of chemically modified starches that are less digestible in the upper intestinal segments and promote fermentation in the hindgut receives considerable attention. This study aimed to investigate the impact of an enzymatically modified starch (EMS) on nutrient flow, passage rate, and bacterial activity at ileal and post-ileal level. Eight ileal-cannulated growing pigs were fed 2 diets containing 72% purified starch (EMS or waxy cornstarch as control) in a cross-over design for 10 d, followed by a 4-d collection of feces and 2-d collection of ileal digesta. On d 17, solid and liquid phase markers were added to the diet to determine ileal digesta flow for 8 h after feeding. Reduced small intestinal digestion after the consumption of the EMS diet was indicated by a 10%-increase in ileal flow and fecal excretion of dry matter and energy compared to the control diet (P<0.05). Moreover, EMS feeding reduced ileal transit time of both liquid and solid fractions compared to the control diet (P<0.05). The greater substrate flow to the large intestine with the EMS diet increased the concentrations of total and individual short-chain fatty acids (SCFA) in feces (P<0.05). Total bacterial 16S rRNA gene abundance was not affected by diet, whereas the relative abundance of the Lactobacillus group decreased (P<0.01) by 50% and of Enterobacteriaceae tended (P<0.1) to increase by 20% in ileal digesta with the EMS diet compared to the control diet. In conclusion, EMS appears to resemble a slowly digestible starch by reducing intestinal transit and increasing SCFA in the distal large intestine.
Social cognition in intellectually disabled male criminal offenders: a deficit in affect perception?

Purpose Although intellectual disability (ID) and criminal offending have long been associated, the nature of this link is obfuscated by reliance on historically unrigorous means of assessing ID and fractionating social cognitive skills. The purpose of this paper is to review and report current findings and set an agenda for future research in social perception, social inference and social problem solving in ID violent offenders. Design/methodology/approach The literature is reviewed on comorbidity of criminal offending and ID, and on social cognitive impairment and ID offending. In an exploratory case-control series comprising six violent offenders with ID and five similarly able controls, emotion recognition and social inference are assessed by the Awareness of Social Inference Test and social problem-solving ability and style by an adapted Social Problem-Solving Inventory. Findings Violent offenders recognised all emotions except “anxious”. Further, while offenders could interpret and integrate wider contextual cues, absent such cues offenders were less able to use paralinguistic cues (e.g. emotional tone) to infer speakers’ feelings. Offenders in this sample exceeded controls’ social problem-solving scores. Originality/value This paper confirms that ID offenders, like neurotypical offenders, display specific deficits in emotion recognition – particularly fear recognition – but suggests that in ID offenders impairments of affect perception are not necessarily accompanied by impaired social problem solving. The implication for therapeutic practice is that ID offenders might be most effectively rehabilitated by targeting simpler, low-level cognitive processes, such as fear perception, rather than adapting treatment strategies from mainstream offenders.