Miracle-dz/UniFAR-FTUs huggingface dataset:
Diversity of culturable ericoid mycorrhizal fungi of Rhododendron decorum in Yunnan, China

The diversity of ericoid mycorrhizal fungi isolated from Rhododendron decorum Franch. in Yunnan, southwestern China, was examined for the first time. In total 300 hair-root samples were collected from 13 R. decorum individuals in two adjacent wild population sites and one cultivated population site. Two hundred eighteen slow-growing isolates were obtained; the ability of some to form ericoid mycorrhiza was tested in vitro. One hundred twenty-five isolates formed hyphal structures morphologically corresponding to ericoid mycorrhiza, and these were determined by morphological and molecular means to belong to 12 fungal species. There were hardly any differences in species among the three sampled populations. The sequences of several isolates were similar to those of Oidiodendron maius and ericoid mycorrhizal fungi from Helotiales, accounting respectively for 18.4% and 24.8% of the total culturable ericoid mycorrhizal fungi assemblage. Dark septate endophytes were detected in the sampled hair roots by microscopy.
Mitochondrial DNA in Postmortem Brain from Patients with Parkinson's Disease

To the Editors: Using Southern blot analysis with mitochondrial DNA (mtDNA) as a probe, we reported that the mtDNA was normal in the putamen, the cortex, and the substantia nigra of patients with Parkinson's disease, where a complex I defect had been observed (Lestienne et al., 1990). However, Ikebe et al. (1 990) using the much more sensitive technique of polymerase chain reaction (PCR) (Saiki et al., 1985) recently detected small amounts of the mtDNA deleted genome in the striatum of patients with Parkinson's disease and senescence. We have repeated this experiment and found that in addition to numerous bands, the deleted genome was present in a very low amount even in a control. This is shown in Fig. 1, where we have done a PCR shifi assay using two different forward and reverse oligonucleotide primers to amplify the
Antioxidant activity in cells and organs.

Antioxidant activity in cells occurs at several levels. The present work focuses on some aspects of enzymatic antioxidant defense. In particular, the so-called ancillary enzymes and transport systems are presented. Recent aspects on the control of the levels of antioxidant enzymes include the oxyR regulon in microorganisms as well as the response to DNA hypomethylation in livers of mice. Ebselen is a novel selenoorganic compound with antioxidant activity capable of conferring protection against oxidative challenge. Its activity to catalyse the GSH-peroxidase reaction is thought to mediate the effect in intact cells. The nonenzymatic antioxidant defense (e.g., vitamins E and C and other natural or chemically synthesized compounds) form an important complementary part of cellular antioxidant defense.
Therapeutic Factors in Group Treatment as Perceived by Sex Offenders

Abstract Thirty-four (34) federally sentenced sex offenders in British Columbia were surveyed using the Yalom (1995) 12 therapeutic factors presented in a 60-item questionnaire Likert format, as well as a semi-structured interview regarding their perceptions of which curative factors were most beneficial to them in treatment. The mean scores for catharsis and self-understanding were found to be rated significantly more helpful than the other factors, while the mean scores for Guidance and Identification were rated significantly less helpful. These findings were consistent with previous research with male sex offenders. Years of education was positively correlated with catharsis, cohesion, self-understanding, and universality. Results suggest that if therapists and programme designers want to maximize the investment of sexual offenders in therapy, they need to build a programme that fosters an atmosphere where group members can work together in a supportive environment and can express thoughts and feelings, and share stories, in such a way that they gain a greater self-understanding.
A Small Aperiodic Set of Tiles

We give a simple set of two tiles that can only tile aperiodically | that is no tiling with these tiles is invariant under any in nite cyclic group of isometries. Although general constructions for producing aperiodic sets of tiles are nally appearing, simple aperiodic sets are fairly rare. This set is among the smallest sets ever found. A tiling is non-periodic if there is no in nite cyclic group of isometries leaving the tiling invariant. In E, this is equivalent to requiring that no translation leaves the tiling invariant. A set of tiles is aperiodic if it is possible to completely tile the plane with comgruent copies of the tiles, but only non-periodically. For example, a pair of unit squares, one black and one white, is not an aperiodic set of tiles: it is possible to tile non-periodically with black and white squares but they can tile periodically as well. Here we give a new, simple example of a set of aperiodic tiles, the T (trilobite) and C (cross) ( gure 1); in any tiling with these tiles, we will require that the \tips" of the tiles meet as pictured at right. (A local condition such as this is a \matching rule"). Two variations of the tiles are given at the end of this paper. These tiles are among the simplest ever found, and are related to a a family of aperiodic sets of 2 tiles in each En, n 3 [10]. The reader may wish to examine a photocopy of the appendix with a pair of scissors. cross tips must meet like so: i.e.
Utilizing Partial Policies for Identifying Equivalence of Behavioral Models

We present a novel approach for identifying exact and approximate behavioral equivalence between models of agents. This is significant because both decision making and game play in multiagent settings must contend with behavioral models of other agents in order to predict their actions. One approach that reduces the complexity of the model space is to group models that are behaviorally equivalent. Identifying equivalence between models requires solving them and comparing entire policy trees. Because the trees grow exponentially with the horizon, our approach is to focus on partial policy trees for comparison and determining the distance between updated beliefs at the leaves of the trees. We propose a principled way to determine how much of the policy trees to consider, which trades off solution quality for efficiency. We investigate this approach in the context of the interactive dynamic influence diagram and evaluate its performance.
Online User Activities Discovery Based on Time Dependent Data

Network evolution is a hot research topic especially when social networking has become an important Web application. The access histories of Web users which contain the users traces' on a social network have not been considered useful data. However, they may reveal more about the network's connectedness if the history's time-sensitive characteristic is analyzed and studied. In this paper, we model the user's daily activities in a time series model to reflect the dynamic nature of a social network due to various user behavior patterns over a period of time. We begin to study the activity pattern for a single user. We then expand that study over the whole network. Through the model, we can quantitatively analyze the user's contribution to the social network and predict the user's response when there is a new action by another user.
Co-evolutionary learning on noisy tasks

The paper studies the effect of noise on co-evolutionary learning, using Backgammon as a typical noisy task. It might seem that co-evolutionary learning would be ill-suited to noisy tasks: genetic drift causes convergence to a population of similar individuals, and on noisy tasks it would seem to require many samples (i.e., many evaluations and long computation time) to discern small differences between similar population members. Surprisingly, the paper learns otherwise: for small population sizes, the number of evaluations does have an effect on learning; but for sufficiently large populations, more evaluations do not improve learning at all-population size is the dominant variable. This is because a large population maintains more diversity, so that the larger differences in ability can be discerned with a modest number of evaluations. This counter-intuitive result means that co-evolutionary learning is a feasible method for noisy tasks, such as military situations and investment management.
Amplitude and frequency modulation in wall turbulence

Abstract In this study we examine the impact of the strength of the large-scale motions on the amplitude and frequency of the small scales in high-Reynolds-number turbulent boundary layers. Time series of hot-wire data are decomposed into large- and small-scale components, and the impact of the large scale on the amplitude and frequency of the small scales is considered. The amplitude modulation effect is examined by conditionally averaging the small-scale intensity ( ${ u}_{S}^{2} $ ) for various values of the large-scale fluctuation ( ${u}_{L} $ ). It is shown that ${ u}_{S}^{2} $ increases with increasing value of ${u}_{L} $ in the near-wall region, whereas, farther away from the wall, ${ u}_{S}^{2} $ decreases with increasing ${u}_{L} $ . The rate of increase in small-scale intensity with the strength of the large-scale signal is neither symmetric (about ${u}_{L} = 0$ ) nor linear. The extent of the frequency modulation is examined by counting the number of occurrences of local maxima or minima in the small-scale signal. It is shown that the frequency modulation effect is confined to the near-wall region and its extent diminishes rapidly beyond ${y}^{+ } = 100$ . A phase lag between the large- and small-scale fluctuations, in terms of amplitude modulation, has also been identified, which is in agreement with previous studies. The phase lag between large- and small-scale fluctuations for frequency modulation is comparable to that of amplitude modulation in the near-wall region. The combined effect of both amplitude and frequency modulation is also examined by computing conditional spectra of the small-scale signal conditioned on the large scales. In the near-wall region, the results indicate that the peak value of pre-multiplied spectra increases with increasing value of ${u}_{L} $ , indicating amplitude modulation, while the frequency at which this peak occurs also increases with increasing value of ${u}_{L} $ , revealing frequency modulation. The overall trends observed from the conditional spectra are consistent with the results obtained through statistical analyses. Finally, a physical mechanism that can capture most of the above observations is also presented.
Perceived Partner Responsiveness Mediates the Association Between Social Anxiety and Relationship Satisfaction in Committed Couples

Despite the inherent interpersonal nature of social anxiety (SA), a surprisingly sparse literature addresses the interpersonal processes occurring within the committed romantic relationships of SA individuals. The current study tested the hypothesis that the relational phenomenon of perceived partner (un)responsiveness (PPR; Reis, Clark, & Holmes, 2004), mediates the association between SA and poor relationship satisfaction. We used recently-developed actor-partner-interdependence mediational models with data from a 35-day dyadic diary study of 80 committed couples. Social anxiety was found to be tied to poor relationship satisfaction in the daily lives of both persons with SA (actors) and their partners. For the actors, this negative association was fully mediated by the actor's perception of poor partner responsiveness. In contrast, for the partners, this negative association was not attributable to PPR. The results remained essentially unchanged even when controlling for comorbid depressive symptoms an.
Personality and current political beliefs: a comparative study of Polish and Belgian samples

The relationship between the five-factor model of personality and ideological variables of conservatism and right wing beliefs was tested in two adult samples, one in Poland (N=146) and one in Belgium (N=203). The main question in this study was as follow: are there any differences between the Polish and Belgian samples with regard to the relationship between political ideology and personality characteristics? Our results showed that correlations between Openness and right wing ideology were significant and negative in both samples. Results also demonstrated that Conscientiousness was quite robust correlates of political ideology. Another problem examined in this study referred to the question of whether there are any differences between Polish and Belgian samples with regard to the level of conservatism and rightist beliefs. We assumed that level of conservatism would be higher for Poles than for Belgians. However, the results showed that it was comparable in both samples.
Expressivity versus efficiency of graph kernels

Recently, kernel methods have become a popular tool for machine learning and data mining. As most ‘real-world’ data is structured, research in kernel methods has begun investigating kernels for various kinds of structured data. One of the most widely used tools for modeling structured data are graphs. In this paper we study the trade-off between expressivity and efficiency of graph kernels. First, we motivate the need for this discussion by showing that fully general graph kernels can not even be approximated efficiently. We also discuss generalizations of graph kernels defined in literature and show that they are either not positive definite or not very useful. Finally, we propose a new graph kernel based on subtree patterns. We argue that while a little more computationally expensive, this kernel is more expressive than kernels based on walks.
Low-voltage analog current-mode Central Pattern Generator circuit for robotic chewing locomotion using 130nanometer CMOS technology

Rhythmic animal locomotive behaviour such as walking, running, swimming and flying is known to be driven by biological neural networks with phase-locked oscillatory behaviour called Central Pattern Generator. This paper describes a Central Pattern Generator(CPG) circuit for locomotion control of rhythmic robotic chewing. A two-neuron CPG model slightly modified from the Matsuoka's oscillator model has been implemented in low-voltage analog CMOS circuit using the IBM 130 nm CMOS technology. Compared to digital implementation, the analog CPG consumes less power and occupies less silicon area. The analog CPG consists of current-mode low-pass filters and current mirrors implementing the neurons which are cross-connected by inhibitory synaptic links. There are two tonic sensory inputs, two internal states and two adaptation outputs for muscles for the CPG circuit.
Race-Ethnicity, Social Background, and Grade Retention

AUTHOR Hauser, Robert M. ; Pager, Devah I. ; Simmons, Solon J. TITLE Race-Ethnicity, Social Background, and Grade Retention. CDE Working Paper. INSTITUTION Wisconsin Univ., Madison. Center for Demography and Ecology. SPONS AGENCY Wisconsin Univ., Madison. Graduate School. REPORT NO CDE-WP-2000-08 PUB DATE 2000-07-00 NOTE 97p. ; Paper presented at the Annual Meeting of the American Sociological Association (Washington, DC, August 2000). Also supported by the William Vilas Estate Trust. PUB TYPE Reports Evaluative (142) -Speeches/Meeting Papers (150) EDRS PRICE MF01/PC04 Plus Postage. DESCRIPTORS Age Differences; Black Students; Educational Policy; Elementary Secondary Education; Enrollment Trends; *Grade Repetition; Hispanic American Students; *Racial Differences; Social Promotion; *Socioeconomic Status IDENTIFIERS African Americans
Inverse probability weighting for covariate adjustment in randomized studies

Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting a ‘favorable’ model that yields strong treatment benefit estimate. Although there is a large volume of statistical literature targeting on the first aspect, realistic solutions to enforce objective inference and improve precision are rare. As a typical randomized trial needs to accommodate many implementation issues beyond statistical considerations, maintaining the objectivity is at least as important as precision gain if not more, particularly from the perspective of the regulatory agencies. In this article, we propose a two‐stage estimation procedure based on inverse probability weighting to achieve better precision without compromising objectivity. The procedure is designed in a way such that the covariate adjustment is performed before seeing the outcome, effectively reducing the possibility of selecting a ‘favorable’ model that yields a strong intervention effect. Both theoretical and numerical properties of the estimation procedure are presented. Application of the proposed method to a real data example is presented. Copyright © 2013 John Wiley & Sons, Ltd.
A general encoding framework for representing network measurement and topology data

Scientific applications are evolving rapidly and rely heavily on the network for data movement, communication, control and result collection. This reliance on the network has increased the breadth of consumers of network status information while the increasing complexity of networks has expanded the diversity of the producers of this information. To enable this wide variety of producers and consumers to effectively interoperate, relevant standards are paramount.
Tagged Dataflow: a Formal Model for Iterative Map-Reduce

In this paper, we consider the recent iterative extensions of the Map-Reduce framework and we argue that they would greatly benefit from the research work that was conducted in the area of dataflow computing more than thirty years ago. In particular, we suggest that thetagged-dataflowmodel of computation can be used as the formal framework be- hind existing and future iterative generalizations of Map- Reduce. Moreover, we present various applications in which the tagged model gives elegant solutions with increased par- allelism. The tagged-dataflow approach for iterative Map- Reduce creates a number of interesting research challenges which deserve further investigation, such as the requirement for a more sophisticated fault tolerance model.
Model checking with multi-valued temporal logics

Multi-valued logics support the explicit modeling of uncertainty and disagreement by allowing additional truth values in the logic. Such logics can be used for verification of dynamic properties of systems where complete, agreed upon models of the system are not available. This paper presents a symbolic model checker for multi-valued temporal logics. The model checker works for any multi-valued logic whose truth values form a quasi-boolean lattice. Our models are generalized Kripke structures, where both atomic propositions and transitions between states may take any of the truth values of a given multi-valued logic. Properties to be model checked are expressed in CTL, generalized with a multi-valued semantics. The design of the model checker is based on the use of MDDs, a multi-valued extension of binary decision diagrams.
Trajectory planning of robots with dynamics and inequalities

Proposes a trajectory planning scheme for open-chain systems to steer in joint space between a start and a goal, while explicitly satisfying the dynamic equations and inequality constraints prescribed in terms of joint torques, joint angles, and their higher derivatives. The algorithm consists of four steps: (i) the structure of the dynamic equations is exploited to embed the dynamic equations explicitly into the constraints; (ii) the inequalities in the space of joint angles and their derivatives are inner approximated by a set of linear inequalities, i.e., a polytope; (iii) a feasible trajectory is then sought within a class of basis functions by using a discrete collocation grid in time where the inequalities are satisfied; and (iv) the feasible trajectories are characterized in terms of a convex set of the coefficients associated with the basis functions. The approach is illustrated in theory and experiments with a master-slave dual-arm manipulation system.
Normalized alignment of dependency trees for detecting textual entailment

In this paper, we investigate the usefulness of normalized alignment of dependency trees for entailment prediction. Overall, our approach yields an accuracy of 60% on the RTE2 test set, which is a significant improvement over the baseline. Results vary substantially across the different subsets, with a peak performance on the summarization data. We conclude that normalized alignment is useful for detecting textual entailments, but a robust approach will probably need to include additional sources of information.
Unlimited Liability and Law Firm Organization: Tax Factors and the Direction of Causation

In a recent issue of this Journal, Carr and Mathewson (1988) test a model of the impact of limited and unlimited liability regimes on the nature of firms by comparing the performance of law firms operated as partnerships and sole proprietorships (and therefore subject to unlimited liability) with that of law firms operated as corporations (and therefore subject to limited liability). ' In their model, "unlimited liability by raising the cost of ownership rights discourages investment in the firm, causing legal firms to be inefficiently small" (p. 779). The peculiar history of organizational form in the legal profession seemed to provide an opportunity to test their model's prediction. Prior to the 1960s, state law prevented law firms from incorporating, with the effect that unlimited liability was mandated. During the 1960s and early 1970s, a large number of states passed statutes that allowed law and other professional service firms to incorporate, thereby giving such firms the option to elect either an unlimited or a limited liability regime. The result was a universe that included some law firms that were subject to unlimited liability and some that were subject to limited liability. Carr and Mathewson test their model's prediction that law firms would reach a larger, more efficient size under a limited liability regime by using 1972 and 1977 census data to compare firm size based on liability status. Consistent with their model's prediction, they report "that liability status significantly affects law firm size: a change in liability status from unlimited to limited increases the average law firm size in 1972 (as measured by annual receipts) by approximately $79,000 (in 1972 dollars) or 48 percent. A similar result flows from the 1977 data" (p. 781). While their use of a convenient change in the state regulation of
Situation Schemata as Representation Format and Query Language for a Non-Standard Database System

Computers will probably never achieve the level of human skills in natural language processing, but they can well aid in such actions as searching in a database. The project NALOG – NAtural language processing and LOGic programming – aims at querying a database in natural language and getting answers in natural language again. As query language and internal representation format, we explore the use of situation schemata which were developed in an attempt to bring together the unification-based frameworks prominent in NL syntax analysis and situation semantics, one of the leading NL semantic theories. We describe an experimental question-answering system based on the Complex-Relational Data Base. Operations of the Complex-Relational Algebra perform directly on situation schemata generated from NL questions. As far as we know, we present the first evaluation strategy for situation schemata directly based on a relational data model.