Miracle-dz/UniFAR-FTUs huggingface dataset:
Affective and cognitive mediators of the impact of cigarette warning labels.

INTRODUCTION Research conducted by the U.S. Food and Drug Administration to select graphic warning labels for cigarette packs has been challenged as inadequate for demonstrating effects on smokers' beliefs about smoking. The present study tested the prediction that warnings alter risk perceptions and thoughts of quitting indirectly through a cognitive pathway (warning believability) and an affective pathway (worry about health), both of which are important for encouraging smokers to consider quitting. METHODS Using a national Internet panel, individuals who smoke were randomly assigned to view 1 of 3 types of warning labels: basic text only, graphic image with basic text, and graphic image with both basic and additional text elaborating on the reason for the health risk. Analyses were conducted to determine whether cognitive and affective reactions mediated effects on smoking-related outcomes. RESULTS Images influenced perceived risk, immediate desire to smoke, and feelings toward quitting indirectly through affective reactions; elaborated text influenced these outcomes through cognitive believability, with little evidence of direct effects. Believability also enhanced positive feelings toward quitting among smokers who were less worried about health risks due to smoking. CONCLUSIONS The findings indicate that (a) many effects of warnings on smokers' beliefs are mediated rather than direct, (b) both cognitive and affective responses are important mediators, and (c) elaborated text can help to increase effects of images through a cognitive pathway. Warning labels should be designed to maximize effects on these mediators in order to influence smoking outcomes.
Optimized Protocol for Measuring 2-NBDG Uptake as a Cellular Marker of Glycolytic Demand

2 Introdcution . 3–5 Methods and Materials . 5–8 Cell Viability Study . 5 -6 2-NBDG Concentration vs. Cell Viability Study . 6-7 2-NBDG Uptake Study . 7-8 Image Analysis . 8 Results . 9-13 Cell Viability Study . 9 2-NBDG Concentration vs. Cell Viability Study . 10 2-NBDG Uptake Study . 10-13 Discussion and Conclusions . 14-15 Future Directions . 15 Acknowledgements . 16 References . 17-18 Appendices . 19-20 Appendix A: Supplementary Data . 19-20
Crocus Sativus extract effects on serum biochemical profile in dog

Crocus sativus is a grassy, perennial, stem less and bulbous plant which belongs to iridaceae family. The saffron has aphrodisiacs effects and decrease fat and cholesterol. The aim of the current study is to evaluate the serum biochemical changes due to saffron use in dog. For this purpose, 14 male and 14 female mature dogs selected randomly, and kept in separate cages with standard dietary and desired water. The treatment groups were treated with 100 mg/kg and 200 mg/kg oral dosage of saffron daily, for 2 weeks, and in control group placebo was used. The AST, ALT, BUN, creatinine, cholesterol, Na and K levels was evaluated. In treatment groups, there were significant increase in AST, ALT, BUN, Creatinine and significant decrease in Cholesterol and Na and K levels. Saffron extract has significant effects on biochemical profile of dogs, although, more studies needed to indicate its effects on heart, sport, and stress.
Macroinvertebrate drift-benthos trends in a regulated river

Downstream drift plays a fundamental role in the spatial distribution and community structure of lotic macroinvertebrates. We sampled both benthic and drifting macroinvertebrates at 15 sites, in three sections of river with varying flow alteration along the Tongariro River, New Zealand. Our objectives were to examine whether (i) benthic and drift density were linearly related throughout the river, (ii) the presence of dams affected the propen- sity of macroinvertebrates to drift, and (iii) drift propensity was related to benthic periphyton biomass or natural longitudinal patterns down the river. More taxa were collected from the drift than the benthos, although drift and benthic samples were generally taxonomically similar, despite some structural differences. Nonetheless, differ- ences were evident between the major groups when assessing density and relative abundance links between the benthos and drift. The presence of dams did not affect the propensity of macroinvertebrates to drift on the whole, nor was propensity affected by periphyton biomass or distance from source. These results suggest that although altered periphyton biomass in downstream sections in the Tongariro River is altering the composition of benthic and drifting macroinvertebrates, drift propensity is unaffected. However, some deviations from linear relationships between benthic and drift density are evident suggesting these links may be taxon specific.
Design Education via Web-based Virtual Environments Educational Technologies and Design Education

The concept of a "virtual" environment has emerged from advances in computer networking, image processing, modeling, simulation and multimedia data representation. During the past few years the concept has been intensively employed in Virtual Design Studios (VDSs) for teaching students both design and Internet technology issues. This paper presents the Web-based VDS as an environment for computer mediated and supported design education. The discussion of the principles, the current state, the advantages and the drawbacks of VDSs is based on our experience in organising four studios. The paper concludes with future trends in the development of VDSs. Educational Technologies and Design Education We are witnesses of fundamental changes in the methods and techniques employed to educate and train design students. These changes are the result of an invasion of computer mediated information technologies which meet the evolving needs of our increasingly technological society. The developments in communications, computing and information delivery services decrease the gap between the conventional and distance learning methods. Both methods include two major components: (i) course materials to be delivered to the students; and (ii) communication between students and instructors. Lecturers create multimedia course content and post it on the Internet where it is accessible, for instance, via the World Wide Web (WWW). Students communicate with instructors via e-mail or through a video conference session. These techniques are referred as computer mediated and supported instruction (CMSI) and are being integrated both in basic and distance educational methodology. Russell (1996) has analysed more than 200 works, published between 1928 and 1996, related to both the university classroom and distance education. The results show that generally there are no significant differences in achievement between: (i) students in traditional classes and students in distance-delivered classes; and (ii) distance students at remote sites and distance students within organisational sites where the instructor is present. These results support the development of unified CMSI methods for both types of education. The research done by Verduin and Clark (1991) supports this idea and specifies some criteria when unified methods will work effectively. Comparing distance education to traditional face-to-face instruction, they indicate that teaching and 1Key Centre of Design Computing, University of Sydney, NSW 2006 Australia, email: {simeon, mary}@arch.usyd. edu.au
Resource Allocation for QoS On-Chip Communication

The provision of communication services with well defined performance characteristics has received significant attention in the NoC community because for many applications it is not sufficient or adequate to simply maximize average performance. It is envisioned that complex NoC based architectures will host complex, heterogeneous sets of applications. In a scenario where many applications compete for shared resources, a fair allocation policy that gives each application sufficient resources to meet its delay, jitter and throughput requirements, is critical. Each application, or each part of an application, should obtain exactly those resources needed to accomplish its task, not more nor less. If an application gets too small a share of the resources, it will either fail completely because of a critical deadline miss, or its utility will be degraded, e.g. due to bad video or audio quality. If an application gets more of a resource than needed, the system is over-dimensioned and not cost effective. Moreover, well defined performance characteristics are a prerequisite for efficient composition of components and subsystems into systems [9]. If all subsystems come with QoS properties the system performance can be statically analyzed and, most importantly, the impact of the composition on the performance of individual subsystems can be understood and limited. In the absence of QoS characteristics all subsystems have to be re-verified because the interference with other subsystems may severely affect a subsystems performance and even render it faulty. Thus, QoS is an enabling feature for compositionality.
Differential regulation of symmetry genes and the evolution of floral morphologies

Shifts in flower symmetry have occurred frequently during the diversification of angiosperms, and it is thought that such shifts play important roles in plant–pollinator interactions. In the model developmental system Antirrhinum majus (snapdragon), the closely related genes CYCLOIDEA (CYC) and DICHOTOMA (DICH) are needed for the development of zygomorphic flowers and the determination of adaxial (dorsal) identity of floral organs, including adaxial stamen abortion and asymmetry of adaxial petals. However, it is not known whether these genes played a role in the divergence of species differing in flower morphology and pollination mode. We compared A. majus with a close relative, Mohavea confertiflora (desert ghost flower), which differs from Antirrhinum in corolla (petal) symmetry and pollination mode. In addition, Mohavea has undergone a homeotic-like transformation in stamen number relative to Antirrhinum, aborting the lateral and adaxial stamens during flower development. Here we show that the patterns of expression of CYC and DICH orthologs have shifted in concert with changes in floral morphology. Specifically, lateral stamen abortion in Mohavea is correlated with an expansion of CYC and DICH expression, and internal symmetry of Mohavea adaxial petals is correlated with a reduction in DICH expression during petal differentiation. We propose that changes in the pattern of CYC and DICH expression have contributed to the derived flower morphology of Mohavea and may reflect adaptations to a pollination strategy resulting from a mimetic relationship, linking the genetic basis for morphological evolution to the ecological context in which the morphology arose.
Adaptation to Climate Change in the context of Sustainable Development

Introduction C limate change is one of the all-encompassing global environmental changes likely to have deleterious effects on natural and human systems, economies and infrastructure. The risks associated with it call for a broad spectrum of policy responses and strategies at the local, regional, national and global level. The UNFCCC (United Nations Framework Convention on Climate Change) highlights two fundamental response strategies: mitigation and adaptation. While mitigation seeks to limit climate change by reducing the emissions of GHG (greenhouse gases) and by enhancing 'sink' opportunities, adaptation aims to alleviate the adverse impacts through a wide-range of system-specific actions (Fussel and Klein, 2002). Albeit both mitigation and adaptation measures must be pursued to tackle the climate change problem and to create an effective and inclusive international climate change regime, more attention has been devoted to mitigation in the past, both in scientific research and policy debate. Sensitivity to the issue of adaptation has grown over the last couple of years, particularly after the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report). Adaptation has now emerged as an urgent policy priority, prompting action both within and outside the climate change negotiations (Parry et al. 2005).
Predicting financial market crashes using ghost singularities

We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of ‘ghosts of finite-time singularities’ is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the approximate normal form is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts.
Influence of biomaterial nanotopography on the adhesive and elastic properties of Staphylococcus aureus cells

Despite the well-known beneficial effects of biomaterial nanopatterning on host tissue integration, the influence of controlled nanoscale topography on bacterial colonisation and infection remains unknown. Therefore, the aim of the present study was to determine the nanoscale effect of surface nanopatterning on biomaterial colonisation by S. aureus, utilising AFM nanomechanics and single-cell force spectroscopy (SCFS). Nanoindentation of S. aureus bound to planar (PL) and nanopatterned (SQ) polycarbonate (PC) surfaces suggested two distinct areas of mechanical properties, consistent with a central bacterial cell surrounded by a capsullar component. Nevertheless, no differences in elastic moduli were found between bacteria bound to PL and SQ, suggesting a minor role of nanopatterning in bacterial cell elasticity. Furthermore, SCFS demonstrated increased adhesion forces and work between S. aureus and SQ surfaces at 0 s and 1 s contact times. Although WLC modelling showed similarities in contour lengths for attachment to both surfaces, Poisson analysis suggests increased short-range forces for the S. aureus–SQ interactions. In the case of S. aureus–PL, long-range forces were found to not only be dominant but also repulsive in nature, which may help explain the reduced adhesion forces observed during AFM probing. In conclusion, although surface nanopatterning does not significantly influence the elasticity of attached bacterial cells, it was found to promote the early-adhesion of S. aureus cells to the biomaterial surface.
Microwave coagulation therapy of hepatocellular carcinoma

Microwave is an ultra-short and high-frequency electromagnetic wave with a wavelength range between 1 and 1,000 mm, and a frequency range between 300 and 300,000 MHz. [1,2] The most common frequency of microwave used medically is 2,450, 915, and 433 MHz. [3,4] Hepatocellular carcinoma (HCC) is a common tumor with a dismal prognosis and development of novel therapies were needed for improving the treatment of this disease. [5] Microwave coagulation therapy (MCT) is a relatively novel method of tumor ablation compared with other minimally invasive local therapies for HCC such as high-intensity focused ultrasound, irreversible electroporation, laparoscopic liver resection, percutaneous ethanol injection, radiofrequency ablation (RFA), and stereotactic body radiation therapy. [6] This treatment method offers an easy-to-perform alternative option either in a percutaneous, laparoscopic or open surgical procedure. [7,8] In recent years, MCT has attracted increasing interests from clinicians for the treatment of HCC because this method provides the advantages of minimal invasiveness and safety in humans. [9]
Spectral–spatial feature learning for hyperspectral imagery classification using deep stacked sparse autoencoder

Abstract. Classification of hyperspectral remote sensing imagery is one of the most popular topics because of its intrinsic potential to gather spectral signatures of materials and provides distinct abilities to object detection and recognition. In the last decade, an enormous number of methods were suggested to classify hyperspectral remote sensing data using spectral features, though some are not using all information and lead to poor classification accuracy; on the other hand, the exploration of deep features is recently considered a lot and has turned into a research hot spot in the geoscience and remote sensing research community to enhance classification accuracy. A deep learning architecture is proposed to classify hyperspectral remote sensing imagery by joint utilization of spectral–spatial information. A stacked sparse autoencoder provides unsupervised feature learning to extract high-level feature representations of joint spectral–spatial information; then, a soft classifier is employed to train high-level features and to fine-tune the deep learning architecture. Comparative experiments are performed on two widely used hyperspectral remote sensing data (Salinas and PaviaU) and a coarse resolution hyperspectral data in the long-wave infrared range. The obtained results indicate the superiority of the proposed spectral–spatial deep learning architecture against the conventional classification methods.
Simultaneous on-line Discovery and Improvement of Robotic Skill options

The regularity of everyday tasks enables us to reuse existing solutions for task variations. For instance, most door-handles require the same basic skill (reach, grasp, turn, pull), but small adaptations of the basic skill are required to adapt to the variations that exist (e.g. levers vs. knobs). We introduce the algorithm “Simultaneous On-line Discovery and Improvement of Robotic Skills” (SODIRS) that is able to autonomously discover and optimize skill options for such task variations. We formalize the problem in a reinforcement learning context, and use the PIBB algorithm [2] to continually optimize skills with respect to a cost function. SODIRS discovers new subskills, or “skill options”, by clustering the costs of trials, and determining whether perceptual features are able to predict which cluster a trial will belong to. This enables SODIRS to build a decision tree, in which the leaves contain skill options for task variations. We demonstrate SODIRS' performance in simulation, as well as on a Meka humanoid robot performing the ball-in-cup task.
Pretreatment, Analysis, Identification and Preparation of Toxic Compounds Eluted into Body Fluids from Medical and Dental Devices

Selective analysis of toxic compounds in complicated matrix such as body fluids is extremely difficult. This is because unexpected inter - ference admixtures with almost identical retention time in chromatography may co-elute with overlapping. 1t is essential to remove admix- tures byappropriate pretreatment procedures. For that purpose there may be several sorts of pretreatment methods such as liquid-liquid extraction or solid phase extraction (SPE) using column, membrane dialysis filtration ultra-filtration super fluid critical extraction SFE or adsorption using charcoal or other appropriate adsorbents. It has been reported several pretreatment methods for acidic, basic and neutral compounds in biological fluids. Body fluids direct injection column is also available in the market, however this column has restriction of concentration of organic solvent in the eluent up to 20% of methanol (18% of acetonitrile), thus resulting in poor or no elution of strongly hydrophobic compounds on reverse phase. The reason of restriction is prevention of coagulation of denaturated protein in the reversed phase column. Artifact formation must also be considered during pretreatment methods. Artifact formation may cause lower recovery of the compound of interest and may also cause misunderstanding to the researcher, which they may extract unexpected highly strong toxic compound. According to the recent advancement of analytical column fabrication technology, several new columns based on innovated technology are now commercially available. Some of them can be resulted in incompletely residual silanol column, so common ion addition is required for strongly basic or acidic compounds analysis or ion-pair method is required. Ion-pair method is so popular but it often causes to shorten column life by retaining and spoiling the column with ion paring reagent. These columns are also described by comparing conventional columns in this paper.
Multimodal medical case retrieval using Bayesian networks and the Dezert-Smarandache theory

In this paper, we present a Case Based Reasoning (CBR) system for the retrieval of medical cases made up of a series of images with semantic information (such as the patient age, sex and medical history). Indeed, medical experts generally need varied sources of information, which might be incomplete, uncertain and conflicting, to diagnose a pathology. Consequently, we derive a retrieval framework from Bayesian networks and the Dezert-Smarandache theory, which are well suited to handle those problems. The system is designed so that heterogeneous sources of information can be integrated in the system: in particular images, indexed by their digital content, and symbolic information. The method is evaluated on a classified diabetic retinopathy database. On this database, results are promising: the retrieval precision at five reaches 80.5%, which is almost twice as good as the retrieval of single images alone.
The Mortality and Myocardial Effects of Antidepressants Are Moderated by Preexisting Cardiovascular Disease: A Meta-Analysis

Background: Antidepressants (ADs) are commonly prescribed medications, but their long-term health effects are debated. ADs disrupt multiple adaptive processes regulated by evolutionarily ancient biochemicals, potentially increasing mortality. However, many ADs also have anticlotting properties that can be efficacious in treating cardiovascular disease. We conducted a meta-analysis assessing the effects of ADs on all-cause mortality and cardiovascular events in general-population and cardiovascular-patient samples. Methods: Two reviewers independently assessed articles from PubMed, EMBASE, and Google Scholar for AD-related mortality controlling for depression and other comorbidities. From these articles, we extracted information about cardiovascular events, cardiovascular risk status, and AD class. We conducted mixed-effect meta-analyses testing sample type and AD class as moderators of all-cause mortality and new cardiovascular events. Results: Seventeen studies met our search criteria. Sample type consistently moderated health risks. In general-population samples, AD use increased the risks of mortality (HR = 1.33, 95% CI: 1.14-1.55) and new cardiovascular events (HR = 1.14, 95% CI: 1.08-1.21). In cardiovascular patients, AD use did not significantly affect risks. AD class also moderated mortality, but the serotonin reuptake inhibitors were not significantly different from tricyclic ADs (TCAs) (HR = 1.10, 95% CI: 0.93-1.31, p = 0.27). Only “other ADs” were differentiable from TCAs (HR = 1.35, 95% CI: 1.08-1.69). Mortality risk estimates increased when we analyzed the subset of studies controlling for premedication depression, suggesting the absence of confounding by indication. Conclusions: The results support the hypothesis that ADs are harmful in the general population but less harmful in cardiovascular patients.