Miracle-dz/UniFAR-FTUs huggingface dataset:
Reproducibility of Fibrous Cap Status Assessment of Carotid Artery Plaques by Contrast-Enhanced MRI

Background and Purpose— Reproducibility in identifying the fibrous cap (FC) of carotid artery plaques by noncontrast-enhanced MRI has been shown to be poor. The objective of this study was to assess the reproducibility of multisequence MRI, including contrast-enhanced images, in assessing FC status. Methods— Forty-five symptomatic patients with 30% to 69% carotid artery stenosis underwent a multisequence MRI protocol, which included contrast-enhanced images. FC status (ie, discrimination between fibrotic and/or calcified plaques, plaques with a lipid-rich necrotic core and an intact and thick FC, and plaques with a lipid-rich necrotic core and a thin and/or ruptured FC) was independently assessed by 3 observers of which one also scored all images on a different occasion. Linear weighted kappa coefficients (&kgr;) were calculated as indicators of inter- and intraobserver agreement. Results— On a per-slice basis, interobserver agreement was good (&kgr;=0.60, 0.64, and 0.71), whereas intraobserver agreement was very good (&kgr;=0.86). On a per-plaque basis, interobserver agreement was good (&kgr;=0.64, 0.69, and 0.78), whereas intraobserver agreement was very good (&kgr;=0.96). Conclusion— This study found good interobserver and very good intraobserver agreement in assessing FC status of carotid artery plaques. Future studies are warranted to determine the predictive value of FC status assessment by multisequence MRI, including contrast-enhanced images, on the occurrence of (recurrent) cerebral ischemic events.
Sonic hedgehog maintains the identity of cortical interneuron progenitors in the ventral telencephalon

Fate determination in the mammalian forebrain, where mature phenotypes are often not achieved until postnatal stages of development, has been an elusive topic of study despite its relevance to neuropsychiatric disease. In the ventral telencephalon, major subgroups of cerebral cortical interneurons originate in the medial ganglionic eminence (MGE), where the signaling molecule sonic hedgehog (Shh) continues to be expressed during the period of neuronogenesis. To examine whether Shh regulates cortical interneuron specification, we studied mice harboring conditional mutations in Shh within the neural tube. At embryonic day 12.5, NestinCre:ShhFl/Fl mutants have a relatively normal index of S-phase cells in the MGE, but many of these cells do not co-express the interneuron fate-determining gene Nkx2.1. This effect is reproduced by inhibiting Shh signaling in slice cultures, and the effect can be rescued in NestinCre:ShhFl/Fl slices by the addition of exogenous Shh. By culturing MGE progenitors on a cortical feeder layer, cell fate analyses suggest that Shh signaling maintains Nkx2.1 expression and cortical interneuron fate determination by MGE progenitors. These results are corroborated by the examination of NestinCre:ShhFl/Fl cortex at postnatal day 12, in which there is a dramatic reduction in cell profiles that express somatostatin or parvalbumin. By contrast, analyses of Dlx5/6Cre:SmoothenedFl/Fl mutant mice suggest that cell-autonomous hedgehog signaling is not crucial to the migration or differentiation of most cortical interneurons. These results combine in vitro and ex vivo analyses to link embryonic abnormalities in Shh signaling to postnatal alterations in cortical interneuron composition.
Will the Real Meaning of Affect Please Stand Up?

It is widely believed that affect plays an important role in risk perception, and that such perception is mainly governed by emotional processes. However, upon closer scrutiny it turns out that the belief is based on weak empirical evidence, if the words affect and emotion are interpreted according to their dominating meanings in natural language, and to common usage in psychology at large. Instead, severity of consequences emerges as a major factor in perceived risk, just as it did in a previous analysis of probability/risk vs. consequences (Sjöberg, 1999b, 2000a). The perception of severity of consequences is not the same as emotion, although emotional effects may arise from considering some severe consequences of accidents or the use of certain technologies and facilities. The picture of the public as irrational and emotionally driven painted by the received message on the role of affect is unfortunate and possibly has unwanted policy implications. The word affect should be used to denote emotion; it is then clear that affect/emotion is of only minor importance in risk perception. 1. This paper was supported by a grant from the Bank of Sweden Tercentary Fund (Neglected Risks). Elisabeth Engelberg provided important information on emotion definitions. Henry Montgomery gave valuable comments on the manuscript.
SPPAM-Statistical PreProcessing AlgorithM An approach for the classification of multiple correlated data

Most machine learning tools work with a single table where each row is an instance and each column is an attribute. Each cell of the table contains an attribute value for an instance. This representation prevents one important form of learning, which is, classification based on groups of correlated records, such as multiple exams of a single patient, internet customer preferences, weather forecast or prediction of sea conditions for a given day. To some extent, relational learning methods, such as inductive logic programming, can capture this correlation through the use of intensional predicates added to the background knowledge. In this work, we propose SPPAM, an algorithm that aggregates past observations in one single record. We show that applying SPPAM to the original correlated data, before the learning task, can produce classifiers that are better than the ones trained using all records.
Improving the Forecasting Power of Volatility Models

Volatility models have been extensively used in risk modeling especially GARCH models under the normal distribution. Although they generate highly significant coefficient estimates, these models are known to have poor forecasting power. It is therefore interesting to develop a different approach of risk modeling to improve forecasting results. By using the generalized t-distribution in modeling the changes in the distribution of stock index returns, the results show a significant improvement in the forecasting power. Moreover, Monte Carlo simulations have confirmed that the index returns are better explained by ARCH-type models.
Modelling Cell Cycle using Different Levels of Representation

Understanding the behaviour of biological systems requires a complex setting of in vitro and in vivo experiments, which attracts high costs in terms of time and resources. The use of mathematical models allows researchers to perform computerised simulations of biological systems, which are called in silico experiments, to attain important insights and predictions about the system behaviour with a considerably lower cost. Computer visualisation is an important part of this approach, since it provides a realistic representation of the system behaviour. We define a formal methodology to model biological systems using different levels of representation: a purely formal representation, which we call molecular level, models the biochemical dynamics of the system; visualisation-oriented representations, which we call visual levels, provide views of the biological system at a higher level of organisation and are equipped with the necessary spatial information to generate the appropriate visualisation. We choose Spatial CLS, a formal language belonging to the class of Calculi of Looping Sequences, as the formalism for modelling all representation levels. We illustrate our approach using the budding yeast cell cycle as a case study.
An Effective Early Warning Scheme against Pollution Dissemination for BitTorrent

BitTorrent is one of the most popular P2P file sharing systems. However, chunk-based file sharing mode makes it difficult to detect content pollution and prevent pollution dissemination during downloading process. In this paper, we propose an early warning scheme against pollution dissemination for BitTorrent. Our idea is to build an early cooperative warning mechanism and rapidly spread alert message among peers in the swarm when pollution is detected at the early stage, which is called "early warning, quickly reacting". The performance evaluation based on fluid model shows the necessity and effectiveness of our scheme, which effectively reduces the traffic abusement and restricts pollution dissemination in BitTorrent-like P2P networks. Another advantage of our solution is that it can handle cheating behaviors made by malicious or unconscious peers, which shows the robustness of our solution.
Corneal-Imaging Calibration for Optical See-Through Head-Mounted Displays

In recent years optical see-through head-mounted displays (OST-HMDs) have moved from conceptual research to a market of mass-produced devices with new models and applications being released continuously. It remains challenging to deploy augmented reality (AR) applications that require consistent spatial visualization. Examples include maintenance, training and medical tasks, as the view of the attached scene camera is shifted from the user's view. A calibration step can compute the relationship between the HMD-screen and the user's eye to align the digital content. However, this alignment is only viable as long as the display does not move, an assumption that rarely holds for an extended period of time. As a consequence, continuous recalibration is necessary. Manual calibration methods are tedious and rarely support practical applications. Existing automated methods do not account for user-specific parameters and are error prone. We propose the combination of a pre-calibrated display with a per-frame estimation of the user's cornea position to estimate the individual eye center and continuously recalibrate the system. With this, we also obtain the gaze direction, which allows for instantaneous uncalibrated eye gaze tracking, without the need for additional hardware and complex illumination. Contrary to existing methods, we use simple image processing and do not rely on iris tracking, which is typically noisy and can be ambiguous. Evaluation with simulated and real data shows that our approach achieves a more accurate and stable eye pose estimation, which results in an improved and practical calibration with a largely improved distribution of projection error.
Quasar Spectral Slope Variability in the Optical Band

We performed a new analysis of B and R light curves of a sample of PG quasars. We confirm the variability-redshift correlation and its explanation in terms of spectral variability, coupled with the increase of rest-frame observing frequency for quasars at high redshift. The analysis of the instantaneous spectral slope for the whole quasar samples indicates both an inter-QSO and an intra-QSO α-luminosity correlation. Numerical simulations show that the latter correlation cannot be entirely due to the addition of the host galaxy emission to a nuclear spectrum of variable luminosity but constant shape, implying a spectral variability of the nuclear component. Changes of accretion rate are also insufficient to explain the amount of spectral variation, while hot spots possibly caused by local disk instabilities can explain the observations.
Fully automatic needle calibration for robotic-assisted puncture on small animals

In vision-based medical applications involving tools attached to a robotic arm, it is essential to be able to accurately localize these tools in the robot end-effector frame. Indeed, inaccurate tool-calibration has a direct impact on the accuracy of the task. In this paper, we introduce a versatile and robust calibration technique to estimate the relative position between the robot end-effector and a needle, independently of the needle length and thickness. Firstly, we propose a new method to calibrate the needle pose using a virtual frame created from pre-defined needle motions. Secondly, we compare the obtained results to a gold standard and show that the proposed calibration method provides an error within 0.35 mm.
The role of predation and food limitation on claims for compensation, reindeer demography and population dynamics

Summary A major challenge in biodiversity conservation is to facilitate viable populations of large apex predators in ecosystems where they were recently driven to ecological extinction due to resource conflict with humans. Monetary compensation for losses of livestock due to predation is currently a key instrument to encourage human–carnivore coexistence. However, a lack of quantitative estimates of livestock losses due to predation leads to disagreement over the practice of compensation payments. This disagreement sustains the human–carnivore conflict. The level of depredation on year‐round, free‐ranging, semi‐domestic reindeer by large carnivores in Fennoscandia has been widely debated over several decades. In Norway, the reindeer herders claim that lynx and wolverine cause losses of tens of thousands of animals annually and cause negative population growth in herds. Conversely, previous research has suggested that monetary predator compensation can result in positive population growth in the husbandry, with cascading negative effects of high grazer densities on the biodiversity in tundra ecosystems. We utilized a long‐term, large‐scale data set to estimate the relative importance of lynx and wolverine predation and density‐dependent and climatic food limitation on claims for losses, recruitment and population growth rates in Norwegian reindeer husbandry. Claims of losses increased with increasing predator densities, but with no detectable effect on population growth rates. Density‐dependent and climatic effects on claims of losses, recruitment and population growth rates were much stronger than the effects of variation in lynx and wolverine densities. Synthesis and applications. Our analysis provides a quantitative basis for predator compensation and estimation of the costs of reintroducing lynx and wolverine in areas with free‐ranging semi‐domestic reindeer. We outline a potential path for conflict management which involves adaptive monitoring programmes, open access to data, herder involvement and development of management strategy evaluation (MSE) models to disentangle complex responses including multiple stakeholders and individual harvester decisions.
Italian Named Entity Recognizer Participation in NER task @ Evalita 09

In this paper, we present our system for Named Entity Recognition (NER), as one of the significantly important preliminary steps prior to main Natural Language Processing tasks, based on Support Vector Machines and feature extraction and selection. The system performed the third best on the task of Italian NER at EVALITA 2009, with an overall F-measure of 81.09, which has less than one percent gap with the best result (82 %).
A Fuzzy Adaptive In-Vehicle Traffic Control Method for Isolated Intersections Using Car-to-Car Communication

Intelligent transportation systems, Traffic control, vehicular ad hoc network (VANET), car-to-car communications,, Fuzzy control system. One of the most important applications of Vehicular Ad-hoc Network (VANET) is the traffic control application. One of these applications is adaptive signal control at the intersections. This paper, using Vehicle to Vehicle (V2V) communication, proposes a virtual (in-vehicle) signal control system. Using Fuzzy control system, it proposes an adaptive signal timing system at isolated intersections without traffic light. After calculating length of cycle and optimum phase setting using Webster equation, this paper uses a fuzzy control system for best decision making for extending green light period in different lanes of intersections. In proposed fuzzy system, in addition to considering the number of stopped and crossing vehicles, intersection emergency state is determined according to the number of emergency vehicles, remaining red light time and emergency coefficient of each vehicle. Simulation results of proposed model clarified the least delay time, queue length and travel duration compared Webster equation.
Sparse scene flow segmentation for moving object detection in urban environments

Modern driver assistance systems such as collision avoidance or intersection assistance need reliable information on the current environment. Extracting such information from camera-based systems is a complex and challenging task for inner city traffic scenarios. This paper presents an approach for object detection utilizing sparse scene flow. For consecutive stereo images taken from a moving vehicle, corresponding interest points are extracted. Thus, for every interest point, disparity and optical flow values are known and consequently, scene flow can be calculated. Adjacent interest points describing a similar scene flow are considered to belong to one rigid object. The proposed method does not rely on object classes and allows for a robust detection of dynamic objects in traffic scenes. Leading vehicles are continuously detected for several frames. Oncoming objects are detected within five frames after their appearance.
Transient increase in neuronal chloride concentration by neuroactive aminoacids released from glioma cells

Neuronal chloride concentration ([Cl−]i) is known to be dynamically modulated and alterations in Cl− homeostasis may occur in the brain at physiological and pathological conditions, being also likely involved in glioma-related seizures. However, the mechanism leading to changes in neuronal [Cl−]i during glioma invasion are still unclear. To characterize the potential effect of glioma released soluble factors on neuronal [Cl−]i, we used genetically encoded CFP/YFP-based ratiometric Cl-(apical) Sensor transiently expressed in cultured hippocampal neurons. Exposition of neurons to glioma conditioned medium (GCM) caused rapid and transient elevation of [Cl−]i, resulting in the increase of fluorescence ratio, which was strongly reduced by blockers of ionotropic glutamate receptors APV and NBQX. Furthermore, in HEK cells expressing GluR1-AMPA receptors, GCM activated ionic currents with efficacy similar to those caused by glutamate, supporting the notion that GCM contains glutamate or glutamatergic agonists, which cause neuronal depolarization, activation of NMDA and AMPA/KA receptors leading to elevation of [Cl−]i. Chromatographic analysis of the GCM showed that it contained several aminoacids, including glutamate, whose release from glioma cells did not occur via the most common glial mechanisms of transport, or in response to hypoosmotic stress. GCM also contained glycine, whose action contrasted the glutamate effect. Indeed, strychnine application significantly increased GCM-induced depolarization and [Cl−]i rise. GCM-evoked [Cl−]i elevation was not inhibited by antagonists of Cl− transporters and significantly reduced in the presence of anion channels blocker NPPB, suggesting that Cl− selective channels are a major route for GCM-induced Cl− influx. Altogether, these data show that glioma released aminoacids may dynamically alter Cl− equilibrium in surrounding neurons, deeply interfering with their inhibitory balance, likely leading to physiological and pathological consequences.
Retrieval System Architecture Document Representation Document-Query Matching Efficient Query Evaluation Effectiveness Measures Search Engine Technology Web Crawler Web Search Queries Use of Tag Information Use of Linkage Information Use of User Profiles Result Organization Sponsored Search Metasear

The World Wide Web has become the largest information source in recent years, and search engines are indispensable tools for finding needed information from the Web. While modern search engine technology has its roots in text/information retrieval techniques, it also consists of solutions to unique problems arising from the Web such as web page crawling and utilizing linkage information to improve retrieval effectiveness. The coverage of the Web by a single search engine may be limited. One effective way to increase the search coverage of the Web is to combine the coverage of multiple search engines. Systems that do such combination are called metasearch engines. In this chapter, we describe the inner workings of text retrieval systems, search engines, and metasearch
Tomographical scene reconstruction in the active safety car project

Tomographical reconstruction algorithms can be applied to camera based measurements and thus reconstruct the scenery without knowledge about included objects. The latter is interesting in the domain of driver assistance systems that have to monitor the driveway independently from a priori knowledge about possibly appearing objects. The paper presents tomographical background information, the transfer from radiographing to visual light rays and its negative impacts, and some first result obtained by applying the presented algorithm to images of a from view camera.
The in-vitro antibacterial activity of Annona senegalensis, Securidacca longipendiculata and Steganotaenia araliacea - Ugandan medicinal plants.

BACKGROUND Nearly all cultures from ancient times to the present day have used plants as a source of medicines. As a result, different remedies tended to develop in different parts of the world. Current strategies to overcome the global problem of antimicrobial resistance include research in finding new and innovative antimicrobials from plants. OBJECTIVES To determine the antibacterial activity of extracts of Annona senegalensis, Securidacca longipendiculata and Steganotaenia araliacea, plants which are used in Eastern Uganda for the treatment of diarrhea and wound infections. METHODS The root barks of these plants were collected, sun-dried, pounded using pestles and wooden mortars. Water and methanol extracts were derived and screened. Standard cultures of E. coli ATCC 25922, Pseudomonas aeruginosa ATCC 27853, and Staphylococcus aureus ATCC 25923 were used in the study. The antibacterial tests used were the agar well diffusion assays. The minimum inhibitory concentrations (MIC) were determined by cylinder plate technique. RESULTS Extracts of Annona senegalensis, Steganotaenia araliacea and Securidaca longipendiculata showed activity against Staphylococcus aureus. The methanol extract of Securidaca longipediculata was not inhibitory to S.aureus. Steganotaenia araliacea and Securidaca longipediculata (water) extracts were active against all the bacteria tested. The water and methanol extracts of Annona senegalensis did not show inhibitory activity against E. coli. Of the three bacteria studied, Staphylococcus aureus was the most susceptible to the extracts followed by P. aeruginosa. E. coli was least sensitive to the plant extracts. Annona senegalensis had the lowest MIC against Staphylococcus aureus (62.5 mg/ml); while Steganotaenia araliacea had the highest MIC (250 mg/ml) signifying lower activity. CONCLUSIONS The root bark extracts of the three plants showed antibacterial activity, justifying their continued use in treatment of bacterial infections. RECOMMENDATIONS Further studies are required to isolate and characterise the active phytochemical constituents in the plants. Toxicity studies should be done to determine their safety.