Miracle-dz/UniFAR-FTUs huggingface dataset:
cGMP inhibits L-type Ca2+ channel currents through protein phosphorylation in rat pinealocytes

In this study, the effect of cGMP on the dihydropyridine-sensitive (L- type) Ca2+ current was investigated using the whole cell version of the patch-clamp technique in rat pinealocytes. Dibutyryl-cGMP (1 x 10(-4) M) induced a pronounced inhibition of the L-type Ca2+ channel current. The dibutyryl-cGMP effect was concentration dependent. Elevation of cGMP by nitroprusside had a similar inhibitory action on the L-type Ca2+ channel current. Norepinephrine, which increased cGMP in rat pinealocytes, also inhibited this current. The action of cGMP was independent of cAMP elevation since the cAMP antagonist, Rp-cAMPs, had no effect on the inhibitory action of dibutyryl-cGMP. The involvement of cyclic GMP-dependent protein kinase was suggested by the blocking action of two protein kinase inhibitors, (1-(5-isoquinolinesulfonyl)-2- methylpiperazine (H7) and N-(2-guanidinoethyl)-5- isoquinolinesulfonamide (HA1004), on the dibutyryl-cGMP effect on the L- type Ca2+ channel current. Taken together, these results suggest that (1) cGMP modulates L-type Ca2+ channel currents in rat pinealocytes, causing inhibition of this current; (2) the action of cGMP appears to be independent of cAMP elevation; and (3) phosphorylation by cGMP- dependent protein kinase may be involved.
Robust nonnegative matrix factorization using L21-norm

Nonnegative matrix factorization (NMF) is widely used in data mining and machine learning fields. However, many data contain noises and outliers. Thus a robust version of NMF is needed. In this paper, we propose a robust formulation of NMF using L21 norm loss function. We also derive a computational algorithm with rigorous convergence analysis. Our robust NMF approach, (1) can handle noises and outliers; (2) provides very efficient and elegant updating rules; (3) incurs almost the same computational cost as standard NMF, thus potentially to be used in more real world application tasks. Experiments on 10 datasets show that the robust NMF provides more faithful basis factors and consistently better clustering results as compared to standard NMF.
Exploring intellectual capital in family firms. An empirical investigation

We investigate the influence of family ownership and family involvement in the management on the firm's intellectual capital (IC). The resource-based theory of the firm predicts both benefits and disadvantages of the family on the firm's IC. Using Pulic's VAIC as a proxy for the IC of the company, we test two sets of competing hypotheses through multivariate regressions of panel data from Italian listed companies. The results show that family firms have a significantly higher average VAIC than non-family firms. We find a non-linear association between family involvement in the management and IC. At lower levels, the family involvement has a positive association with IC. At higher levels, when the benefits of the family interaction with the business are overcompensated by the disadvantages, the relationship reverses and becomes negative. The research can contribute to both the academic literature on intellectual capital and to family business studies.
Tweets and votes, a special relationship: the 2009 federal election in germany

As the microblogging service Twitter becomes an increasingly popular tool for politicians and general users to comment on and discuss politics, researchers increasingly turn to the relationship between tweets mentioning parties or candidates and their respective electoral fortunes. This paper offers a detailed analysis of Twitter messages posted during the run-up to the 2009 federal election in Germany and their relationship to the electoral fortunes of Germany's parties and candidates. This analysis will focus on four metrics for measuring the attention on parties and candidates on Twitter and the relationship to their respective vote share. The metrics discussed here are: the total number of hashtags mentioning a given political party; the dynamics between explicitly positive or explicitly negative mentions of a given political party; the total number of hashtags mentioning one of the leading candidates, Angela Merkel (CDU) or Frank-Walter Steinmeier (SPD); and the total number of users who used hashtags mentioning a given party or candidate. The results will show that during the campaign of 2009 Twitter messages commenting on parties and candidates showed little, if any, systematic relationship with subsequent votes on election day. In the discussion of the results, I will raise a number of issues that researchers interested in predicting elections with Twitter will have to address to advance the state of the literature.
Optimal prefiltering in iterative feedback tuning

Iterative feedback tuning (IFT) is a data-based method for the iterative tuning of restricted complexity controllers. A "special experiment" in which a batch of previously collected output data is fed back at the reference input allows one to compute an unbiased estimate of the gradient of the control performance criterion. We show that, by performing an optimal filtering of the data that are fed back, one can minimize the asymptotic variability of the control performance cost and, hence, minimize the average performance degradation that results from the randomness of the data. The expression of the optimal filter is derived, and a simulation illustrates the benefits that result from using this optimal filter as compared to the use of the classical constant filter.
Preserving Liveness with Rule-Based Refinement of Place/Tr ansition Systems

In a transformer having a primary winding which is connectable to an a.c. voltage source via switch means which opens and closes at a controllable frequency, there is connected in parallel with the primary or secondary winding of the transformer a circuit which for at least a part of the time during which the switch means opens maintains magnetization of the transformer in a direction opposite to the direction of the magnetization caused by the subsequent closing of the switch means.
Analysis of Foreign Tourism Demand for Croatian Destinations: Long-Run Elasticity Estimates

Given that tourism is a significant source of export revenues for Croatia, it is vital for policymakers to understand the factors affecting foreign tourism demand for Croatian destinations. This study provides long-run elasticity estimates associated with aggregate foreign tourism demand for Croatian destinations in the period 1994:1-2004:4 using the autoregressive distributed lag (ARDL) approach. Foreign tourism demand is proxied by the aggregate number of foreign overnight stays in Croatia. The long-run elasticity estimates indicate that tourism demand is positive and highly elastic with respect to the income of tourist-generating countries. Moreover, tourism demand was adversely affected by the political conflicts in the 1990s. The real exchange rate and transportation costs are not statistically significant determinants of foreign tourism demand.
The Role of Small and Large Businesses in Economic Development

Increasingly, economic development experts are abandoning traditional approaches to economic development that rely on recruiting large enterprises with tax breaks, financial incentives, and other inducements. Instead, they are relying on building businesses from the ground up and supporting the growth of existing enterprises. This approach has two complementary features. The first is to develop and support entrepreneurs and small businesses. The second is to expand and improve infrastructure and to develop or recruit a highly skilled and educated workforce. Both efforts depend in large part on improving the quality of life in the community and creating an attractive business climate. ; Edmiston explores whether promoting entrepreneurship and small businesses makes sense as an economic development strategy. He concludes that it probably does, but with some caveats. Small businesses are potent job creators, but so are large businesses. The attribution of the bulk of net job creation to small businesses arises largely from relatively large job losses at large firms, not to especially robust job creation by small firms. More important, data show that, on average, large businesses offer better jobs than small businesses, both in terms of compensation and stability. Further, there is little convincing evidence to suggest that small businesses have an edge over larger businesses in innovation. More research is needed to properly evaluate the case for a small business strategy, and indeed, to determine whether or not public engagement in economic development itself is a cost-effective and worthwhile pursuit.
The Effect of Bank Shocks on Corporate Financing and Investment: Evidence from 2007-2009 Financial Crisis

We examine how shocks to banks’ financial conditions impact corporate financing and investment decisions using the 2007-2009 financial crisis as an experimental setting. We find that average firms relied more heavily on bank credit during the crisis. However, firms whose banks incurred a larger amount of nonperforming loans used less bank credit when comparing their bank debt before and during the crisis. Their reduction on bank debt weren’t replaced by alternative credit such as public debt or trade credit. There is some evidence that shocks on banks eventually affected corporate real activities; firms with more adversely affected banks invest less and hoard more cash during the crisis compared to their pre-crisis level. Overall, our results suggest that adverse shocks on the banking system can curtail bank lending and negatively affect the real sector. JEL classification: G01, G21, G31
Comprehensive Analysis of Ultrasonic Vocalizations in a Mouse Model of Fragile X Syndrome Reveals Limited, Call Type Specific Deficits

Fragile X syndrome (FXS) is a well-recognized form of inherited mental retardation, caused by a mutation in the fragile X mental retardation 1 (Fmr1) gene. The gene is located on the long arm of the X chromosome and encodes fragile X mental retardation protein (FMRP). Absence of FMRP in fragile X patients as well as in Fmr1 knockout (KO) mice results, among other changes, in abnormal dendritic spine formation and altered synaptic plasticity in the neocortex and hippocampus. Clinical features of FXS include cognitive impairment, anxiety, abnormal social interaction, mental retardation, motor coordination and speech articulation deficits. Mouse pups generate ultrasonic vocalizations (USVs) when isolated from their mothers. Whether those social ultrasonic vocalizations are deficient in mouse models of FXS is unknown. Here we compared isolation-induced USVs generated by pups of Fmr1-KO mice with those of their wild type (WT) littermates. Though the total number of calls was not significantly different between genotypes, a detailed analysis of 10 different categories of calls revealed that loss of Fmr1 expression in mice causes limited and call-type specific deficits in ultrasonic vocalization: the carrier frequency of flat calls was higher, the percentage of downward calls was lower and that the frequency range of complex calls was wider in Fmr1-KO mice compared to their WT littermates.
An adaptive classifier fusion method for analysis of knee-joint vibroarthrographic signals

Abstract-Externally recorded knee-joint vibroarthrographic (VAG) signals bear diagnostic information related to degenerative conditions of cartilage disorders in a knee. In this paper, the number of atoms derived from wavelet matching pursuit (MP) decomposition and the parameter of turns count with the fixed threshold that characterizes the waveform variability of VAG signals were extracted for computer-aided analysis. A novel multiple classifier system (MCS) based on the adaptive weighted fusion (AWF) method is proposed for the classification of VAG signals. The experimental results shows that the proposed AWF-based MCS is able to provide the classification accuracy of 80.9%, and the area of 0.8674 under the receiver operating characteristic curve over the data set of 89 VAG signals. Such results are superior to those obtained with best component classifier in the form of least-squares support vector machine, and the popular Bagging ensemble method.
Complementarities and Cumulative Processes in Models of Monopolistic Competition

Monopolistic competition models have frequently been applied in macroeconomics, growth and development, and international and interregional economics. The three features of monopolistic competition, the monopoly power of producers, the lack of strategic interaction, and endogenous product variety, make it a useful framework to examine the aggregate implications of imperfect competition, increasing returns and incomplete markets. This papers presents a highly selective review in this area, with special emphasis on complementarity and its role in generating multiplier processes, business cycles, clustering, underdevelopment traps, regional disparities, and sustainable growth, or more generally, what Myrdal (1957) called the "principle of circular and cumulative causation. "
ON ANALYTIC AND MEROMORPHIC FUNCTIONS AND SPACES OF QK -TYPE SPACE

Starting from a nondecreasing function K : [0,∞) → [0,∞), we introduce a Möbius-invariant Banach space QK of functions analytic in the unit disk in the plane. We give a general theory of these spaces which for special choices of K give most basic properties of Qp-spaces. Furthermore, we have found necessary and sufficient conditions on K to have QK = B or QK = D, where the Bloch space B is the largest and the Dirichlet space D is the smallest space of QK -type. We consider also the meromorphic counterpart Q K of QK and discuss the differences between the spaces Q K and QK . We prove some general results on q-valent functions and QK spaces which as corollaries have classical results on univalent functions, the Bloch space and BMOA.
An Eye-Tracking Investigation of Written Sarcasm Comprehension: The Roles of Familiarity and Context

This article addresses a current theoretical debate between the standard pragmatic model, the graded salience hypothesis, and the implicit display theory, by investigating the roles of the context and of the properties of the sarcastic utterance itself in the comprehension of a sarcastic remark. Two eye-tracking experiments were conducted where we manipulated the speaker’s expectation in the context and the familiarity of the sarcastic remark. The results of the first eye-tracking study showed that literal comments were read faster than unfamiliar sarcastic comments, regardless of whether an explicit expectation was present in the context. The results of the second eye-tracking study indicated an early processing difficulty for unfamiliar sarcastic comments, but not for familiar sarcastic comments. Later reading time measures indicated a general difficulty for sarcastic comments. Overall, results seem to suggest that the familiarity of the utterance does indeed affect the time course of sarcasm processing (supporting the graded salience hypothesis), although there is no evidence that making the speaker’s expectation explicit in the context affects it as well (thus failing to support the implicit display theory).
Information literacy and learning

This thesis explores the relationship between information literacy and learning. In formal education, students are frequently required to independently find and use information to learn about a topic, and information literacy is often claimed to be a generic skill and graduate attribute. However, to date; the experienced relationship between information literacy and learning has not been investigated. In order to investigate this experience, I have based this research on interviews with 19 students enrolled in third year music composition courses, and 18 students enrolled in a third year tax law course at an Australian university. My primary research question was 'What is the experienced relationship between information literacy and learning? ' The secondary research question was "What are the generic and situated aspects of information literacy? ' In this study, I have used phenomenography to describe the qualitatively different ways that students in two distinct disciplines experience the relationship between information literacy and learning. I have suggested curriculum implications of this description based on a relational approach to learning and teaching. The outcomes of the study include two related sets of categories which map the experience of students in music composition and tax law, and the theoretical GeST windows model for information literacy which is based upon literacy models and theories. The key findings of this study include: * A description of the nature of the experienced relationship between information literacy and learning in music composition and tax law as 1) Applying, 2) Discovering and 3) Expressing (music) or Understanding (tax law); * the theoretical GeST windows model and alignment of the model with the empirical study; * the presentation of curriculum implications in music and tax law, and * an exploration of the nature of information as-it-is-experienced. The findings may be used by teachers, students, librarians, academic skills advisors, academic developers and policy makers in higher education.
Training Conditional Random Fields Using Incomplete Annotations

We address corpus building situations, where complete annotations to the whole corpus is time consuming and unrealistic. Thus, annotation is done only on crucial part of sentences, or contains unresolved label ambiguities. We propose a parameter estimation method for Conditional Random Fields (CRFs), which enables us to use such incomplete annotations. We show promising results of our method as applied to two types of NLP tasks: a domain adaptation task of a Japanese word segmentation using partial annotations, and a part-of-speech tagging task using ambiguous tags in the Penn treebank corpus.
The impact of video motion analysis on kinematics graph interpretation skills

Video motion analysis software was used by introductory physics students in a variety of instructional settings. 368 high school and college students took part in a study where the effect of graduated variations in the use of a video analysis tool was examined. Post‐instruction assessment of student ability to interpret kinematics graphs indicates that groups using the tool generally performed better than students taught via traditional instruction. The data further establishes that the greater the integration of video analysis into the kinematics curriculum, the larger the educational impact. An additional comparison showed that graph interpretation skills were significantly better when a few traditional labs were simply replaced with video analysis experiments. Hands‐on involvement appeared to play a critical role. Limiting student experience with the video analysis technique to a single teacher‐led demonstration resulted in no improvement in performance relative to traditional instruction. Offering mor.
Improved External Memory BFS Implementation

Breadth first search (BFS) traversal on massive graphs in external memory was considered non-viable until recently, because of the large number of I/Os it incurs. Ajwani et al. [3] showed that the randomized variant of the o(n) I/O algorithm of Mehlhorn and Meyer [24] (MM_BFS) can compute the BFS level decomposition for large graphs (around a billion edges) in a few hours for small diameter graphs and a few days for large diameter graphs. We improve upon their implementation of this algorithm by reducing the overhead associated with each BFS level, thereby improving the results for large diameter graphs which are more difficult for BFS traversal in external memory. Also, we present the implementation of the deterministic variant of MM_BFS and show that in most cases, it outperforms the randomized variant. The running time for BFS traversal is further improved with a heuristic that preserves the worst case guarantees of MM_BFS. Together, they reduce the time for BFS on large diameter graphs from days shown in [3] to hours. In particular, on line graphs with random layout on disks, our implementation of the deterministic variant of MM_BFS with the proposed heuristic is more than 75 times faster than the previous best result for the randomized variant of MM_BFS in [3].
Centralizers on prime and semiprime rings

The purpose of this paper is to investigate identities satisfied by centralizers on prime and semiprime rings. We prove the following result: Let R be a noncommutative prime ring of characteristic different from two and let S and T be left centralizers on R. Suppose that (S(x),T(x))S(x) + S(x)(S(x),T(x)) = 0 is fulfilled for all x ∈ R. If S 6 0 (T 6 0) then there existsfrom the extended centroid of R such that T = �S (S = �T).
Neural stochastic codes, encoding and decoding

Identifying informative aspects of brain activity has traditionally been thought to provide insight into how brains may perform optimal computations. However, here we show that this need not be the case when studying spike-time precision or response discrimination, among other activity aspects beyond noise correlations. Our results show that decoders designed with noisy data may perform optimally on quality data, thereby potentially yielding experimental and computational savings.
How Many Volunteers Does it Take to Map an Area Well? The Validity of Linus’ Law to Volunteered Geographic Information

Abstract title/> In the area of volunteered geographical information (VGI), the issue of spatial data quality is a clear challenge. The data that are contributed to VGI projects do not comply with standard spatial data quality assurance procedures, and the contributors operate without central coordination and strict data collection frameworks. However, similar to the area of open source software development, it is suggested that the data hold an intrinsic quality assurance measure through the analysis of the number of contributors who have worked on a given spatial unit. The assumption that as the number of contributors increases so does the quality is known as ‘Linus’ Law’ within the open source community. This paper describes three studies that were carried out to evaluate this hypothesis for VGI using the OpenStreetMap dataset, showing that this rule indeed applies in the case of positional accuracy.
A mechanistic‐stochastic formulation of bed load particle motions: From individual particle forces to the Fokker‐Planck equation under low transport rates

Bed load transport is a highly complex process. The probability density function (PDF) of particle velocities results from the local particle momentum variability in response to fluid drag and interactions with the bed. Starting from the forces exerted on a single particle under low transport rates (i.e., rolling and sliding regimes), we derive here the nonlinear stochastic Langevin equation (LE) to describe the dynamics of a single particle, accounting for both the deterministic and the stochastic components of such forces. Then, the Fokker‐Planck equation (FPE), which describes the evolution of the PDF of the ensemble particle velocities, is derived from the LE. We show that the theoretical PDFs of both streamwise and cross‐stream velocities obtained by solving the FPE under equilibrium conditions have exponential form (PDFs of both positive and negative velocities decay exponentially), consistent with the experimental data by Roseberry et al. ( ). Moreover, we theoretically show how the exponential‐like PDF of an ensemble of particle velocities results from the forces exerted on a single particle. We also show that the simulated particle motions using the proposed Langevin model exhibit an emergent nonlinear relationship between hop distances and travel times (power law with exponent 5/3), in agreement with the experimental data, providing a statistical description of the particles' random motion in the context of a stochastic transport process. Finally, our study emphasizes that the motion of individual particles, described by the LE, and the behavior of the ensemble, described by the FPE, are connected within a statistical mechanics framework.