Miracle-dz/UniFAR-FTUs huggingface dataset:
In Vivo Validation of Simultaneous Non-Contrast Angiography and intraPlaque Hemorrhage (SNAP) Magnetic Resonance Angiography: An Intracranial Artery Study

Objectives Simultaneous Non-contrast Angiography and intraPlaque hemorrhage (SNAP) technique was recently proposed for joint MRA and intraplaque hemorrhage (IPH) imaging. The purpose of this study is to validate SNAP’s MRA performance in patients with suspected intracranial artery disease. Methods SNAP and time-of-flight (TOF) techniques with matched field of view and resolution were applied on 15 patients with suspected intracranial artery disease. Both techniques were evaluated based on their detection of luminal stenosis of bilateral middle cerebral arteries (MCA) and the delineation of smallest visible branches (SVB) of the MCA. Statistical analysis was conducted on the artery level. Results The SNAP MRA was found to provide similar stenosis detection performance when compared with TOF (Cohen’s κ 0.79; 95% Confidence Interval: 0.56–0.99). For the SVB comparison, SNAP was found to provide significantly better small artery delineation than TOF (p = 0.017). Inter-reader reproducibility for both measurements on SNAP was over 0.7. SNAP also detected IPH lesions on 13% of the patients. Conclusions The SNAP technique’s MRA performance was optimized and compared against TOF for intracranial artery atherosclerosis imaging and was found to provide comparable stenosis detection accuracy. Along with its IPH detection capability, SNAP holds the potential to become a first-line screening tool for high risk intracranial atherosclerosis disease evaluation.
Water relations and microclimate around the upper limit of a cloud forest in Maui, Hawai'i.

The goal of this study was to determine the effects of atmospheric demand on both plant water relations and daily whole-tree water balance across the upper limit of a cloud forest at the mean base height of the trade wind inversion in the tropical trade wind belt. We measured the microclimate and water relations (sap flow, water potential, stomatal conductance, pressure-volume relations) of Metrosideros polymorpha Gaudich. var. polymorpha in three habitats bracketing the cloud forest's upper limit in Hawai'i to understand the role of water relations in determining ecotone position. The subalpine shrubland site, located 100 m above the cloud forest boundary, had the highest vapor pressure deficit, the least amount of rainfall and the highest levels of nighttime transpiration (EN) of all three sites. In the shrubland site, on average, 29% of daily whole-tree transpiration occurred at night, while on the driest day of the study 50% of total daily transpiration occurred at night. While EN occurred in the cloud forest habitat, the proportion of total daily transpiration that occurred at night was much lower (4%). The average leaf water potential (Ψleaf) was above the water potential at the turgor loss point (ΨTLP) on both sides of the ecotone due to strong stomatal regulation. While stomatal closure maintained a high Ψleaf, the minimum leaf water potential (Ψleafmin) was close to ΨTLP, indicating that drier conditions may cause drought stress in these habitats and may be an important driver of current landscape patterns in stand density.
Real Time Drowsiness Detection System using Viola Jones Algorithm

Among the many problems faced by the country, deaths and injuries due to road traffic accidents are extremely common. Driver’s drowsiness is one of the major reasons which lead to these mishaps. In this paper, we are discussing a ‘Real Time Drowsiness Detection System’ which could determine the level of drowsiness of the driver. This system considers both the closing of eyes and yawning as the constraints for determining the degree of drowsiness. Viola Jones Algorithm is used for facial features detection. Primary attention is given to faster detection and processing of data. Driver’s drowsiness will be detected by checking whether the eyes are closed over some particular consecutive frames and similarly it can be checked if the driver is yawning by monitoring the mouth region. If the closing of eyes and yawning indicates that the driver is drowsy then an alarm will be triggered. General Terms Feature Detection, Computer Vision, Machine Learning
Methods of the Qualitative Theory for the Hindmarsh-rose Model: a Case Study - a Tutorial

Homoclinic bifurcations of both equilibria and periodic orbits are argued to be critical for understanding the dynamics of the Hindmarsh–Rose model in particular, as well as of some square-wave bursting models of neurons of the Hodgkin–Huxley type. They explain very well various transitions between the tonic spiking and bursting oscillations in the model. We present the approach that allows for constructing Poincare return mapping via the averaging technique. We show that a modified model can exhibit the blue sky bifurcation, as well as, a bistability of the coexisting tonic spiking and bursting activities. A new technique for localizing a slow motion manifold and periodic orbits on it is also presented.
Non-Rigid Parallax for 3D Linear Motion

We consider the problem of reconstructing the location of a moving 3D point seen from a monocular moving camera. Since the point is movingwhile the camera is moving,then even if the camera motion is known, it is impossible to reconstruct the 3D location of the point under general circumstances. However, we show that if the point is movingalong a straight line, then the parameters of the line (and hence the 3D position of the point at each time instance) can be uniquely recovered, and by linear methods, from at least 5 views. Consequently, we pro-pose a new approach for dealing with dynamic scenes (rich with movingobjects) in which once the camera motion is recovered, the 3D trajectory (straight line) of the moving target can be recovered | even when the moving target consists of a single point.
0 N ov 2 00 3 A formula of total probability with interference term and the Hilbert space representation of Kolmogorovian model

In the previous version of this preprint we demonstrated that the Kolmogorov probability model has a very natural representation in a complex Hilbert space. This representation is based on the well known formula of total probability. The Kolmogorov model should be considered as a contextual probabilistic model: elements of a sigma-field represent not events, but contexts (complexes of physical conditions). To map contexts into quantum states, normalized vectors in a complex Hilbert space, we use probability distributions of two incompatible Kolmogorovian random variables, so called reference variables. Thus in our model quantum representation of the Kolmogorov model is just an image of this model through two fundamental reference variables. In quantum physics we use the position and momentum reference variables. In the previous version the Hilbert space representation was constructed only for dichotomous random varibales on the Kolmogorov space. In this version of the paper we do this for arbitrary random variables with a finite number of values. By constructing the Hilbert space representation of the conventional Kol-mogorov model we demonstrated that there is no crucial difference between " classical " and " quantum " probability as it was supposed by founders of QM. " Quantum " probability is just a very special representation of " classical " probability. In particular, in our approach 1 there is no such a mystical thing as irreducible quantum randomness. However, we do not claim that quantum physics can be reduced to classical physics. The Kolmogorovian prequantum model need not be based on the classical physical space. The basic PRESPACE might have huge dimension (even infinite) and non-Euclidean topology.
A novel destination-based routing protocol (DBRP) in DTNs

In Delay Tolerant Networks (DTNs), the aim of any forwarding/routing protocols is to achieve a high delivery ratio of packets/bundles at the lowest possible bandwidth cost, buffer space and energy. Therefore, finding a protocol which uses less resource to achieve high delivery ratio and low latency is an open research question. This paper proposes a quota-based protocol which confines the number of replicas and forwards them based on the meeting history of nodes. The unique aspect of our protocol is to weight any encounter with the final destination to be much higher than any other node encounter. This aspect of the protocol is based on the idea that regardless of how small an encounter rate with the destination, given a highly correlated movement model (i.e., human behaviour) we will end up with a high delivery ratio. The results of our simulation support this hypothesis.
Noise Propagation and Signaling Sensitivity in Biological Networks: A Role for Positive Feedback

Interactions between genes and proteins are crucial for efficient processing of internal or external signals, but this connectivity also amplifies stochastic fluctuations by propagating noise between components. Linear (unbranched) cascades were shown to exhibit an interplay between the sensitivity to changes in input signals and the ability to buffer noise. We searched for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. Negative feedback can buffer this type of noise, but this buffering comes at the expense of an even greater reduction in signaling sensitivity. By systematically analyzing three-component circuits, we identify positive feedback as a central motif allowing for the buffering of propagated noise while maintaining sensitivity to long-term changes in input signals. We show analytically that noise reduction in the presence of positive feedback results from improved averaging of rapid fluctuations over time, and discuss in detail a particular implementation in the control of nutrient homeostasis in yeast. As the design of biological networks optimizes for multiple constraints, positive feedback can be used to improve sensitivity without a compromise in the ability to buffer propagated noise.
Elastic Modulus of Nanometer Silicon Membrane

In this article, a new method is presented to calculate the in-plane elastic modulus of nanometer silicon membrane. In comparing with the traditional model, it accounts for the discrete nature in the thickness direction of the silicon membrane. In this model, interatomic bonding forces are equivalent to spring forces. A method to obtain the spring constant k is also presented by using lattice dynamics theory. Investigating the obtained in-plane elastic modulus value, it is found that the value is highly dependent on the thickness of the membrane and approaches the bulk value as the thickness increases.
Π-SUPPORTS FOR MODULES FOR FINITE GROUP SCHEMES

We introduce the space Π(G) of equivalence classes of π-points of a finite group scheme G, and associate a subspace Π(G)M to any G-module M . Our results extend to arbitrary finite group schemes G over arbitrary fields k of positive characteristic and to arbitrarily large G-modules the basic results about “cohomological support varieties” and their interpretation in terms of representation theory. In particular, we prove that the projectivity of any (possibly infinite dimensional) G-module can be detected by its restriction along π-points of G. Unlike the cohomological support variety of a G-module M , the invariant M 7→ Π(G)M satisfies good properties for all modules, thereby enabling us to determine the thick, tensor-ideal subcategories of the stable module category of finite dimensional G-modules. Finally, using the stable module category of G, we provide Π(G) with the structure of a ringed space which we show to be isomorphic to the scheme ProjH•(G, k).
Global Macro-Financial Shocks and Expected Default Frequencies in the Euro Area

Modelling the link between the global macro-financial factors and firms’ default probabilities constitutes an elementary part of financial sector stress-testing frameworks. Using the Global Vector Autoregressive(GVAR) model and constructing a linking satellite equation for the firm-level Expected Default Frequencies (EDFs), we show how to analyse the euro area corporate sector probability of default under a wide range of domestic and foreign macroeconomic shocks. The results show that, at the euro area aggregate level, the median EDFs react most to shocks to the GDP, exchange rate, oil prices and equity prices. There are some intuitive variations to these results when sector-level EDFs are considered. Overall, the Satellite-GVAR model appears to be a useful tool for analysing plausible global macrofinancial shock scenarios designed for financial sector stress-testing purposes. JEL Classification: C33, F47, G32, G33
Pushing the Power of Stochastic Greedy Ordering Schemes for Inference in Graphical Models

We study iterative randomized greedy algorithms for generating (elimination) orderings with small induced width and state space size — two parameters known to bound the complexity of inference in graphical models. We propose and implement the Iterative Greedy Variable Ordering (IGVO) algorithm, a new variant within this algorithm class. An empirical evaluation using different ranking functions and conditions of randomness, demonstrates that IGVO finds significantly better orderings than standard greedy ordering implementations when evaluated within an anytime framework. Additional order of magnitude improvements are demonstrated on a multi-core system, thus further expanding the set of solvable graphical models. The experiments also confirm the superiority of the MinFill heuristic within the iterative scheme.
Image quality assessment with visual attention

Image quality assessment (IQA) is of great importance for many image processing applications. Some IQA indexes proposed recently more or less try to boost their performance to accord with human subjective evaluation by simulating human visual system (HVS). However, they do not take global salient features into consideration, because of the lack of methods with low computational complexity for simulating visual attention mechanism. This paper proposes a simpler and faster method to extract a saliency map from the reference image, and inserts saliency factors into existing IQA indexes. Experimental results for a set of intuitive examples as well as validation from a database of 982 images with different distortion types show that our improved IQA indexes are much closer to human opinion.
An SCR Inverter with an Integral Battery Charger for Electric Vehicles

A thyristor-based inverter/charger for use in electric passenger vehicles is described, and prototype charger test results are presented. A battery charger is included integral to the inverter by using a subset of the inverter power circuit components. The integral charger employs the inverter commutation components as a resonant ac/dc converter rated at 3.6 kW. The resulting charger provides electrical isolation between the vehicle propulsion battery and ac line and is capable of charging a 25-kWh propulsion battery in 8 h from a 220-V ac line. Charger efficiency and power factor at an output power of 3.6 kW are 86 and 95 percent, respectively. The inverter, when operated with a matching polyphase ac induction motor and nominal 132-V propulsion battery, can provide a peak shaft power of 34 kW (45 hp) during motoring operation and 45 kW (60 hp) during regeneration. Thyristors are employed for the inverter power switching devices and are arranged in an input-commutated topology. This configuration requires only two thyristors to commutate the six main inverter thyristors. The combined ac inverter/charger package weighs 47 kg (103 lb).
Performance of different call admission schemes in a QoS Diffserv domain

Two types of call admission strategies have been proposed for real time support in the Internet: per flow, reservation (i.e., RSVP) based, and measurement based. We evaluate these strategies for a video streaming application. We use a simulation environment (based on a Parsec platform) which supports DiffServ tools as well as QoS routing. In our experiments, we compare the performance of RA-CAC with M-CAC. We show that the selection between these alternatives is influenced by tradeoffs between throughput and delay performance; and that different classes of users may opt for one or the other technique. We also consider a hybrid situation in which both RA-CAC and M-CAC coexist in the network and are reciprocally "protected" by a weighted fair queueing (WFQ) trunk scheduler. A key enabling technology for the M-CAC scheme is QoS routing. We use Q-OSPF not only to find paths that satisfy the quality constraints (delay and bandwidths) but also to advertise current traffic, delay and available bandwidth on all network links. We also use leaky buckets for shaping and policing. Leaky bucket parameters are selected as a function of effective bandwidth, buffer space and end-to-end delay bound. If the traffic (after shaping and policing) conforms to the negotiated traffic profile, and the effective resources are allocated to the connection, the packets are guaranteed delivery within a given worst-case delay bound. In our experiments we verify that when bandwidth and buffers are explicitly allocated (with RA-CAC), the delay bounds are satisfied. The same is not true for M-CAC, where only a statistical allocation is carried out.
Using Binary Logistic Regression to Predict Long-term Effects of Early-Age Home Literacy Environment on Reading Motivation

Home literacy environment has ubiquitously been investigated against its impact on academic achievement and reading motivation. This study is an investigation of the long-lasting effects of home literacy environment on Moroccan students’ reading motivation. 178 students aged 14-24 were surveyed online to elicit their early-age home literacy experiences and to test them against the odds of their reading motivation. Using data gathered on such environments and experiences, a binary logistic regression inferential test was conducted to test if students who grow up in literacy-rich home environments are more likely to be motivated readers, and vice versa. The purpose of using this test in particular is to find out whether reading motivation can be predicted based on home literacy environment data. The accuracy of prediction of this test can be indicative of its potential to detect and diagnose reading motivation at various academic levels. As far as findings of this study are concerned the BLR test affirms that the odds of reading motivation being tied to HLE factors are significantly high. Using BLR to predict, diagnose, and intervene may help educators, parents, and curricula developers in considering HLE and early-age literacy experiences in policy making and curricula designs.
A Hybrid Web Recommender System Based on Cellular Learning Automata

With the rapid growth of the World Wide Web (WWW), finding useful information from the Internet has become a critical issue. Web recommender systems help users make decisions in this complex information space where the volume of information available to them is huge. Recently, a number of web page recommender systems have been developed to anticipate the information needs of on-line users and provide them with recommendations to facilitate and personalize their navigation. Recent studies show that a web usage recommender system which focuses solely on access history has some problems because sometimes this information is incomplete or incorrect. One common solution to this problem is to incorporate some semantic knowledge about pages being recommended into system. In this paper we exploit this idea to improve the dynamic web recommender system which primarily devised for web recommendation based on web usage and structure data. We propose a hybrid web page recommender system based on asynchronous cellular learning automata with multiple learning automata in each cell which try to identify user's multiple information needs and then assist them to recommend pages to users. The proposed system use web usage data, content and structure of the web site to learn user information needs and predicting user's future requests. Our experiments show that incorporating conceptual relationship of pages with usage data can significantly enhance the quality of recommendations.
A Survey on Clustering Methods and Algorithms

— Clustering is a technique of data mining. It aims at finding natural partitioning of data. Objects are grouped depending on the similar nature they share. Similarity is measured depending on various parameters like number of parameters which are in common or lowest allowed difference between any parameters of an object. Data mining techniques include classification, clustering, mining frequent pattern, and correlation. Out of all these, in few decades clustering has gain wide attention of researchers. Clustering involves grouping of data objects which are similar in nature. This helps in the abstraction process of huge amount of data. Once the abstraction process is complete group of data can be represented in more compact manner. This is nothing but data compression. To describe the objects more precisely it needs to be defined by all the possible and meaningful dimensions. As the number of attributes increases finding similarity between objects become difficult. Thus discovering the distribution pattern of data becomes difficult. This has necessitate to look for meaningful grouping in subspaces i.e. subset of attributes. This paper presents an overview of Clustering-a tool in data mining; its application, its various methods of implementation and challenges to overcome.
Evolutionary origins of novel conchologic growth patterns in tropical American corbulid bivalves

SUMMARY We conducted a combined sclerochronologic and phylogenetic analysis to document patterns and rates of shell accretion in several subclades of related corbulids, and to explore the evolutionary origins of novel conchologic developmental patterns. We found three disparate patterns of valve development in Neogene tropical American corbulid genera. These patterns include growth through primarily radial accretion along the sagittal plane, and two derivative patterns: one characterized by initial deposition of a thin shell followed by valve thickening with little increase in valve height, and another producing a well‐defined nepioconch through a marked change in the primary growth direction. We conducted a species‐level phylogenetic analysis of the taxa surveyed for growth patterns, focusing on the ([Bothrocorbula+Hexacorbula]+Caryocorbula) clade. The phylogenetic distribution of shell growth patterns suggests that this clade is characterized by derivative patterns of growth. Oxygen‐isotope calibrated ontogenetic age estimates of species in the derived Bothrocorbula subclade further suggest that transitions from the ancestral radial (sagittal) growth pattern to a derived pattern of growth are a function of heterochrony (peramorphosis by acceleration). These findings are significant because they link previously observed patterns of morphological constraint with a specific evolutionary process, demonstrate how morphologic constraint and innovation can be interrelated, and serve as a model for understanding the evolution of morphologic diversity in the clade as a whole. Furthermore, this study highlights the utility of sclerochronologic records as an important component of evolutionary developmental research on organisms with accretionary skeletal growth.