Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Holothuroid Ichtyotoxic Saponins on the Gills of Free-Living Fishes and Symbiotic Pearlfishes

Several carapid fishes, known as pearlfishes, are endosymbiotic in holothuroids and asteroids. These echinoderms contain a strong concentration of saponins that are efficient membranolytic repellents to predators. We compared the effects of exposure to saponins from the sea cucumber body wall and from the Cuvierian tubules on the behavior and gill ultrastructure of pearlfishes and free-living fishes. Saponins were extracted from the body wall of two holothuroids, the Mediterranean Holothuria forskali and the tropical Bohadschia atra, and from the water surrounding the Cuvierian tubules of B. atra. Five species of carapids that live in symbiosis with holothuroids and seven species of free-living fishes were exposed to these extracts. The free-living fishes exhibited a stress response and died about 45 times faster than pearlfishes when exposed to the same quantity of saponins. Cuvierian tubules and saponins extracted from the body wall were lethal to the free-living fishes, whereas the carapids were much less sensitive. The carapids did not exhibit a stress response. The high toxicity shown by Cuvierian tubules was not explained by the nature of the saponins that were identified by mass spectrometry, but it is likely due to the higher concentration of saponins in the tubules. Histology and scanning and transmission electron microscopy of the gills of the free-living fishes and pearlfishes showed that saponins act at the level of the secondary lamellae where they induce the detachment of the epithelia, create edema at the level of the epithelia, and induce pores in the epithelial cells that lead to their destruction and the invasion of inner cells (pillar cells and red blood cells). This sequence of events happens 5 min after saponin exposure in free-living fishes and after 1 h in carapids.
PCR arrays indicate that the expression of extracellular matrix and cell adhesion genes in human adipocytes is regulated by IL-1β (interleukin-1β)

Abstract The role of IL-1β in regulating the expression of extracellular matrix (ECM) and cell adhesion genes in human adipocytes has been examined. Adipocytes differentiated in culture were incubated with IL-1β for 4 or 24 h and RNA probed with PCR arrays for 84 ECM and cell adhesion genes. Treatment with IL-1β resulted in changes in the expression at one or both time points of ∼50% of the genes probed by the arrays, the majority being down-regulated. Genes whose expression was down-regulated by IL-1β included those encoding several collagen chains and integrin subunits. In contrast, IL-1β induced substantial increases (>10-fold) in the expression of ICAM1, VCAM1, MMP1 and MMP3; the secretion of the encoded proteins was also markedly stimulated. IL-1β has a pervasive effect on the expression of ECM and cell adhesion genes in human adipocytes, consistent with the derangement of tissue structure during inflammation in white fat.
New insertion sequences of Sulfolobus: functional properties and implications for genome evolution in hyperthermophilic archaea

Analyses of complete genomes indicate that insertion sequences (ISs) are abundant and widespread in hyperthermophilic archaea, but few experimental studies have measured their activities in these hosts. As a way to investigate the impact of ISs on Sulfolobus genomes, we identified seven transpositionally active ISs in a widely distributed Sulfolobus species, and measured their functional properties. Six of the seven were found to be distinct from previously described ISs of Sulfolobus, and one of the six could not be assigned to any known IS family. A type II ‘Miniature Inverted‐repeat Transposable Element’ (MITE) related to one of the ISs was also recovered. Rates of transposition of the different ISs into the pyrEF region of their host strains varied over a 250‐fold range. The Sulfolobus ISs also differed with respect to target‐site selectivity, although several shared an apparent preference for the pyrEF promoter region. Despite the number of distinct ISs assayed and their molecular diversity, only one demonstrated precise excision from the chromosomal target region. The fact that this IS is the only one lacking inverted repeats and target‐site duplication suggests that the observed precise excision may be promoted by the IS itself. Sequence searches revealed previously unidentified partial copies of the newly identified ISs in the Sulfolobus tokodaii and Sulfolobus solfataricus genomes. The structures of these fragmentary copies suggest several distinct molecular mechanisms which, in the absence of precise excision, inactivate ISs and gradually eliminate the defective copies from Sulfolobus genomes.
On Modelling Credit Risk Using Arbitrage Free Models

By examining the distribution of state prices obtained from binomial versions of Jarrow and Turnbull (1995), Lando (1998) and Duffie and Singleton (1999), we are able to suggest which credit risk parameters are of critical interest. We find that it appears worthwhile to parameterize credit risk since even the simplest parameterized model obtains large changes in the distribution of state prices when compared to a non-parameterized model. Similarly we find large differences in the distribution of state prices as we add correlation and moderate changes as we add time varying recovery rates. Finally, the choice between the RM or RF recovery assumption appears innocuous, but the choice between RT and these two recovery assumptions is not.
Document level semantic comprehension of noisy text streams via convolutional neural networks

Content comprehension in text is one of the challenges in natural language processing. Understanding text at a low level has become increasingly relevant due to the surge in the amount of content on the web space, where most of it is stream data. In our case, data streams are considered to be an ordered sequence of short and noisy textual messages that are read once or fewer number of times, for example tweets. Our approach entails processing and interpreting streaming texts at document level in mini-batches via deep convolutional networks for opinion, semantic or relationship analysis. Training our model is iterative and incremental, where documents are learnt by understanding the sentence structure and content in vector form based on a known offline model. The model however, incrementally adapts to the changing textual patterns. Our conceptual framework design is distributed in nature such that a pipeline of inputs, deep processing framework and output will be coordinated by the Apache Storm framework. This design is applicable in real time sentiment analysis, opinion mining, and stance detection among others.
Microglia activation in retinal degeneration

Microglia cells are phagocytic sentinels in the CNS and in the retina required for neuronal homeostasis and innate immune defense. Accumulating experimental evidence suggests that chronic microglia activation is associated with various neurodegenerative diseases including retinal dystrophies. Endogenous triggers alert microglia cells rapidly in the degenerating retina, leading to local proliferation, migration, enhanced phagocytosis, and secretion of cytokines, chemokines, and neurotoxins. This amplified, immunological cascade and the loss of limiting control mechanisms may contribute significantly to retinal tissue damage and proapoptotic events. This review summarizes the developmental and immune surveillance functions of microglia in the healthy retina and discusses early signaling events and transcriptional networks of microglia activation in retinal degeneration. The characterization of activation pathways at the molecular level may lead to innovative, therapeutic options in degenerative retinal diseases based on a selective, pharmacological interference with the neurotoxic activities of microglia cells, without compromising their homeostastic functions.
Effect of High Advanced Glycation End-Product Diet on Pulmonary Inflammatory Response and Pulmonary Function Following Gastric Aspiration

ABSTRACT It is not clear why some patients with aspiration advance to acute lung injury or acute respiratory distress syndrome, whereas others do not. The Western diet is high in advanced glycation end-products (AGEs), which have been found to be proinflammatory. We hypothesize that dietary AGEs exaggerate the pulmonary inflammatory response following gastric aspiration. CD-1 mice were randomized to receive either a low-AGE (LAGE) or a high-AGE (HAGE) diet for 4 weeks. Five hours after intratracheal instillation of acidified small gastric particles, pulmonary function was determined. Polymorphonuclear neutrophil counts, albumin, cytokine/chemokine, and tumor necrosis factor soluble receptor II concentrations in the bronchoalveolar lavage and lung myeloperoxidase activity were measured. Compared with LAGE-fed animals, those fed a HAGE diet had increased lung tissue resistance (P = 0.017), bronchoalveolar lavage albumin concentration (P < 0.05), pulmonary polymorphonuclear neutrophil counts (P = 0.0045), and lung myeloperoxidase activity (P = 0.002) following aspiration. In addition, the plasma levels of tumor necrosis factor soluble receptor II were significantly elevated (P < 0.05), whereas paradoxically levels of keratinocyte chemoattractant and monocyte chemoattractant protein 1 were decreased in mice with HAGE diet. In conclusion, a diet high in AGEs exacerbates acute lung injury following gastric aspiration as evidenced by increases in neutrophil infiltration, airway albumin leakage, and decreased pulmonary compliance. This is the first evidence implicating exacerbation of acute inflammatory lung injury by dietary AGEs. Targeting AGEs in the circulatory system may offer a therapeutic strategy for limiting lung injury following gastric aspiration.
Bifactor Models and Rotations: Exploring the Extent to Which Multidimensional Data Yield Univocal Scale Scores

The application of psychological measures often results in item response data that arguably are consistent with both unidimensional (a single common factor) and multidimensional latent structures (typically caused by parcels of items that tap similar content domains). As such, structural ambiguity leads to seemingly endless “confirmatory” factor analytic studies in which the research question is whether scale scores can be interpreted as reflecting variation on a single trait. An alternative to the more commonly observed unidimensional, correlated traits, or second-order representations of a measure's latent structure is a bifactor model. Bifactor structures, however, are not well understood in the personality assessment community and thus rarely are applied. To address this, herein we (a) describe issues that arise in conceptualizing and modeling multidimensionality, (b) describe exploratory (including Schmid–Leiman [Schmid & Leiman, 1957] and target bifactor rotations) and confirmatory bifactor modeling, (c) differentiate between bifactor and second-order models, and (d) suggest contexts where bifactor analysis is particularly valuable (e.g., for evaluating the plausibility of subscales, determining the extent to which scores reflect a single variable even when the data are multidimensional, and evaluating the feasibility of applying a unidimensional item response theory (IRT) measurement model). We emphasize that the determination of dimensionality is a related but distinct question from either determining the extent to which scores reflect a single individual difference variable or determining the effect of multidimensionality on IRT item parameter estimates. Indeed, we suggest that in many contexts, multidimensional data can yield interpretable scale scores and be appropriately fitted to unidimensional IRT models.
Toward Autonomic Computing: Adaptive Neural Network for Trajectory Planning

Cognitive approach through the neural network â€œNNâ€ paradigm is a critical discipline that will help bring about autonomic computing â€œAC. â€ NN-related research, some involving new ways to apply control theory and control laws, can provide insight into how to run complex systems that optimize to their environments. NN is one kind of AC system that can embody human cog-nitive powers and that can adapt, learn, and take over certain functions previously performed by humans. In recent years, artificial neural networks have received a great deal of attention for their ability to perform nonlinear mappings. In trajectory control of robotic devices, neural networks provide a fast method of autonomously learning the relation between a set of output states and a set of input states. In this article, we apply the cognitive approach to solve position controller problems using an inverse geometrical model. In order to control a robot manipulator in the accomplishment of a task, trajectory planning is required in advance or in real time. The desired trajectory is usually described in Cartesian coordinates and needs to be converted to joint space for the purpose of analyzing and controlling the system behavior. In this article, we use a memory neural network (MNN) to solve the optimization problem concerning the inverse of the direct geometrical model of the redundant manipulator when subject to constraints. Our approach offers substantially better accuracy, avoids the computation of the inverse or pseudo-inverse Jacobian matrix, and does not produce problems such as singularity, redundancy, and considerably increased computational complexity.
Spin-Offs: Why Geography Matters

Based on unique data covering individuals, firms, industries and regions for the 1999–2005 period, we contribute with new knowledge concerning the impact of regional variables on spin-offs. Implementing a large number of controls, as well as different estimation techniques and robustness tests, we show that Jacobian externalities have a positive effect on spin-offs. Moreover, using an entropy measure to disentangle unrelated and related variety (RV), we conclude that the effect is confined to RV. These findings are likely to be associated with strong welfare effects: a standard deviation increase (decrease) in related (unrelated) variety increases spin-off propensity by approximately 25%. Other variables are shown to have economic effects of a similar magnitude but may have a different effect across sectors. Sensitivity analyses indicate that the impact of other determinants proposed in the literature (e.g., Marshallian externalities and scale effects) is too small to be detected.
Female Entrepreneurship and Government Policy: Evaluating the Impact of Subsidies on Firms' Survival

This paper assesses the effectiveness of Law 215/1992, an incentive scheme intended to boost female entrepreneurship in Italy. Under the law, which was only implemented in 1997 and remained in force for a decade, the allocation of subsidies among the regions was inversely proportional to their female labour market participation rates. Focussing on the subsidies for start-ups, we analyze survival patterns of subsidized versus non-subsidized firms. We find that subsidized firms show higher survival rates than non-subsidized firms for a period of up to five years after incorporation. After five years the survival patterns are very similar, leading us to conclude that the incentive scheme had no permanent effect on the subsidized firms but only produced a i? ½honeymoon effecti? ½.
An Analysis of the Budget Variables and the Asymmetry of Shocks in the Frequency Domain for OECD Countries

This paper makes use of frequency domain techniques to investigate the business cycle properties of the fiscal variables for 13 OECD economies. In general, the correlations with the economic activity indicators are substantially larger for the revenues than for the expenditures. The countries for which we find high (or very high) correlation of the budget balance and/or the government revenues with the economic activity are Australia (budget balance only), Finland, France, Germany, USA and Austria (revenues only). A picture of low correlation emerges for the case of Italy, Netherlands, Spain, Portugal, Greece and the UK. The correlations are also higher for major business cycles than for shorter business cycles. As the major source of risks for EMU is the incidence of asymmetric shocks among EMU members, evidence from the spectral analysis is also presented on this domain. With regard to GDP data, from a sample of nine EU countries three of them, Finland, Austria, Portugal show low, or very low correlation with EU-15, especially for short business cycles. On the other hand, Germany, France, and in general the Netherlands and Spain show a high level of correlation with the EU15 cycle. The UK shows a high correlation with major business cycles and only medium correlation for short business cycles. Italy shows high correlation for cycles ranging from 2 to 3 years. The low synchrony of short business cycles detected for some countries (Finland, Greece, Italy, Portugal, and Sweden) could be a source of concern to the operation of EMU. If this pattern is not changed by EMU, it could pose a high burden on fiscal policy, and requires the attaining of a sound fiscal position in order not to breach SGP dispositions.
An Efficient Secure Scheme Based on Hierarchical Topology in the Smart Home Environment

As the Internet of Things (IoT) has developed, the emerging sensor network (ESN) that integrates emerging technologies, such as autonomous driving, cyber-physical systems, mobile nodes, and existing sensor networks has been in the limelight. Smart homes have been researched and developed by various companies and organizations. Emerging sensor networks have some issues of providing secure service according to a new environment, such as a smart home, and the problems of low power and low-computing capacity for the sensor that previous sensor networks were equipped with. This study classifies various sensors used in smart homes into three classes and contains the hierarchical topology for efficient communication. In addition, a scheme for establishing secure communication among sensors based on physical unclonable functions (PUFs) that cannot be physically cloned is suggested in regard to the sensor’s low performance. In addition, we analyzed this scheme by conducting security and performance evaluations proving to constitute secure channels while consuming fewer resources. We believe that our scheme can provide secure communication by using fewer resources in a smart home environment in the future.
Effectiveness of Outpatient, Day Hospital, and Inpatient Psychotherapeutic Treatment for Patients with Cluster B Personality Disorders

Background: For patients with cluster B personality disorders there is no consensus regarding the optimal treatment setting. The aim of this study was to compare the effectiveness of different psychotherapeutic settings for patients with cluster B personality disorders, i.e. outpatient, day hospital, and inpatient treatment. Methods: The study was conducted between March 2003 and June 2008 in 6 mental health care centres in the Netherlands, with a sample of 207 patients with a DSM-IV-TR axis II cluster B diagnosis. Patients were assigned to 3 different settings of psychotherapeutic treatment and effectiveness was assessed at 18 months after baseline. An intention-to-treat analysis was conducted for psychiatric symptoms (Brief Symptom Inventory), psychosocial functioning (Outcome Questionnaire-45), and quality of life (EQ-5D), using multilevel statistical modelling. As the study was non-randomised, the propensity score method was used to control for initial differences. Results: Patients in all 3 settings improved significantly in terms of psychiatric symptoms, social and interpersonal functioning, and quality of life 18 months after baseline. The inpatient group showed the largest improvements. The comparison of outpatient and inpatient treatment regarding psychiatric symptoms showed a marginally significant result (p = 0.057) in favour of inpatient treatment. Conclusions: Patients with cluster B personality disorders improved in all investigated treatment settings, with a trend towards larger improvements of psychiatric symptoms in the inpatient setting compared to the outpatient setting. Specialised inpatient treatment should be considered as a valuable treatment option for cluster B personality disorders, both in research and in clinical practice.
Accurate inductances and magnet flux linkage estimation in interior PMSM employing speed harmonic measurements

The equivalent circuit parameters of an interior permanent magnet synchronous machine (PMSM) vary under different operating conditions due to magnetic saturation and temperature rise. Knowledge of accurate machine parameters is of paramount importance for high performance PMSM control and condition monitoring. Therefore, this paper presents a novel parameter estimation method, which employs both the electrical and mechanical model of an interior PMSM (IPMSM) for simultaneously estimating three parameters; namely, the d- and q-axis inductances and permanent magnet flux linkage. Specifically, the proposed parameter estimation approach is mathematically justified at first. Thereafter, by using the machine mechanical model with the speed measurement, a third equation in addition to the dq-axis voltage equations is developed to make the estimation model full-rank for simultaneously estimating three parameters. Lastly, the proposed approach is implemented with the recursive least square algorithm to estimate machine parameters and it is validated with simulations and experimental tests on a laboratory IPMSM drive system.
IDENTIFYING REGIME CHANGES IN MARKET VOLATILITY

A casual inspection of a graph of volatility indexes over time indicates that volatility has undergone infrequent, but significant, shifts in its average level. The purpose of this article is to test for multiple structural breaks in the mean level of market volatility measured by the VIX and VXO, and to identify statistically the dates of these mean shifts. We find evidence of three distinct periods: pre-1992, 1992-1997, and post-1997. We find that the mean volatility, as well as its standard deviation, was lowest during 1992-1997. Our findings provide statistical evidence consistent with popular beliefs that market volatility changes over time. 2006 The Southern Finance Association and the Southwestern Finance Association.
Local Politics, Organized Interests, and Land-Use Policy

This research note examines the influence of organized interests in the land-use policy-making process from the perspective of urban planners employed in city government. Perceptions of these professionals are evaluated using a series of regression models controlling for the mitigating effects of government structure, mayoral partisanship, community characteristics, and the personal attributes of the respondents participating in the research. The results suggest that the aggregate influence of organized interests is more pronounced in cities with mayors when compared with cities with council–manager government structures. Furthermore, there is some evidence that the presence of a partisan mayor can increase the aggregate influence of organized interests, as well as mitigate the amount of influence garnered by specific groups. These findings contribute to the study of urban development by offering new insight into the relationship between local politics, organized interests, and land-use policy.
THE VALUATION OF CURRENCY OPTIONS FOR ALTERNATE STOCHASTIC PROCESSES

This paper compares the ability of four valuation models — the Pure Diffusion model of Black-Scholes-Merton, the Absolute Diffusion and Pure Jump models of Cox-Ross, and the mixed Jump-Diffusion model of Merton — to explain the observed behavior of market prices of foreign currency options. The empirical tests are based on a comparison of the pattern of implied volatilities obtained from option market prices and the Black-Scholes-Merton model with those expected theoretically if exchange rates follow the four stochastic processes specified above. The results of the comparison show that the pattern of implied volatilities is most consistent with the mixed Jump-Diffusion model.