Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Aspect Graphs to Control the Recovery and Tracking of Deformable Models

Active or deformable models have emerged as a popular modeling paradigm in computer vision. These models have the exibility to adapt themselves to the image data, o ering the potential for both generic object recognition and non-rigid object tracking. Because these active models are underconstrained, however, deformable shape recovery often requires manual segmentation or good model initialization, while active contour trackers have been able to track only an object's translation in the image. In this paper, we report our current progress in using a part-based aspect graph representation of an object [14] to provide the missing constraints on data-driven deformable model recovery and tracking processes. Appears in International Journal of Pattern Recognition and Arti cial Intelligence, Vol. 11, No. 1, February, 1997, pp 115{142. (special issue containing selected papers from the Workshop on Spatial Computing: Representation, Interpretation and Applications, Curtin University of Technology, Perth, Western Australia, December 2{3, 1995.)
Low complexity closed-form solution to blind joint channel and symbol estimation in MIMO-OFDM

Due to the increasing amount of subscribers and high data rate applications, the mobile networks should evolve to fit the growing demands. To fulfill the requisites imposed by the next generation of wireless systems, the combination of multiple input multiple output (MIMO) system and orthogonal frequency division multiplexing (OFDM) is shown to be the possible solution. In this paper, we propose a low complexity blind receiver known as Frobenius Vector Average Rank One Approximation (FVAROA). Our proposed FVAROA receiver is a closed-form solution, which has a less complex than the classical alternating least squares (ALS) receiver since no iteration is need. The key feature of the proposed FVAROA receiver is in terms of computational complexity which is linear. As shown in the numerical simulations, in terms of Bit Error Rate (BER) and Normalized Mean Square Error (NMSE) of channel estimation, FVAROA can achieve the same accuracy as the state-of-the-art estimation techniques.
Coding and Signal Processing for Multiple-Antenna Transmission Systems : A Review

We describe recent results on multiple-antenna transmission systems. These are known to offer a potential performance, in terms of bit/s/Hz, that cannot be obtained otherwise with present-day technology. We summarize the theoretical performance limits of these systems under the assumptions that the channel gains are known to the receiver, to the transmitter and to the receiver, or to neither. Coding and signal-processing schemes that allow these limits to be approached are finally addressed.
Tool-supported model-driven validation process for system architectures

Designing system architecture is still an error-prone process and a great challenge. The development of complex embedded systems like radar systems is very cost-intensive. Therefore it is important that system architects are supported by appropriate tools. Our UML-based process focuses on validating the architecture against system requirements and analyzing the impacts of requirement or architectural changes. In this paper we present a supporting tool providing automatization possibilities for the validation process. This is a major breakthrough as it reduces the need for repetitive, time consuming and mindless validation process to be conducted manually. The tool is able to handle all the requirements, including the requirements' interconnections with one another, and increase process usability.
Channel bonding in cognitive radio wireless sensor networks

Recently, wireless sensor networks are gaining a lot of attention due to the availability of various low cost sensor devices. For example, Wireless Multimedia Sensor Networks (WMSNs) have lot of new potential applications in different domains including, environmental monitoring, home automation, tracking, health care, just to name a few. Another example is the Body Area Networks (BANs), where different sensors are attached with the patient's body. However, these sensor networks also bring several challenges, such as they are resource constraint, requires application specific QoS requirements, high bandwidth demands, and resistance to interference. In this paper, we argue that wireless sensor nodes with cognitive radio capability, together with channel bonding, can help to address these challenges. In this perspective, we discuss cognitive radio wireless sensor network for hospital environment as a case study. We then discuss the way of spectrum characterization and criteria for channel bonding in such networks. Finally, we highlight issues and challenges, which provides the basis to develop algorithms and protocols for the future cognitive radio wireless sensor network deployments in different application scenarios.
Visual Attention-Guided Approach to Monitoring of Medication Dispensing Using Multi-location Feature Saliency Patterns

This paper is dedicated to the development of a computer vision-based system for medication (pills and capsules) identification and counting in order to increase the productivity of medication dispensing and maintain its high safety. The algorithmic basis of the system is the attentive vision approach to robust and fast object detection in images. It consists in time-efficient image analysis by a multi-scale visual attention operator to detect feature-point areas located inside the pill and capsule regions. The attention operator combines a spatial saliency filter with a temporal change (novelty) detector in order to robustly detect salient and object-relevant feature points. The medication recognition algorithm involves a set of image descriptors at the feature-point areas called the multi-location feature-saliency pattern, which fully discriminates between different types of medication. The method detects pills and extracts area-based descriptors without any image pre-segmentation procedure due to the proposed multi-scale attention operator.
Type 1 Diabetes and Coronary Artery Disease Additional information for this article can be found in an online appendix at http://care.diabetesjournals.org. A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

Although the increased risk of premature heart disease in type 1 diabetes has been recognized for some time, the underlying pathogenesis is still poorly understood. The most likely factor, a priori, to account for this increased risk is hyperglycemia. However, despite recent evidence from the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study that prior intensive glycemic control reduces cardiovascular disease (CVD), the epidemiologic association between glycemia and coronary heart disease (CHD) is surprisingly weak. This paradox is a focus of the current review, which also evaluates other major determinants of coronary artery disease (CAD) in type 1 diabetes, including the roles of insulin resistance, cytokines, inflammatory biomarkers, and, briefly, genetic factors. Finally, the clinical implications of this information are discussed. A high occurrence of, and mortality from, CHD in type 1 diabetes has been documented since the late 1970s (1,2). A 1984 registry reported a 10-fold or greater CHD mortality compared with that expected from U.S. national data (3). This very high relative risk, partly reflecting the extremely low CHD death rate in the general young-adult population, was subsequently confirmed by Joslin investigators (4), who reported that those with type 1 diabetes by 55 years of age experienced a sixfold greater cumulative CHD mortality compared with the rate expected using Framingham Study data. The Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) also reported a standardized mortality ratio (SMR) from ischemic heart disease of 9.1 (for men) and 13.5 (for women) for those with a diabetes diagnosis before 30 years of age (5). Two recent prospective epidemiologic studies, the Pittsburgh Epidemiology of Diabetes Complications (EDC) study (6) and Eurodiab (7), a multicenter, clinic-based study in Europe, confirmed these earlier reports and reported an incidence of total coronary events (including electrocardiogram [ECG] changes) …
Ginostra : The Value of Flexibility

We are concerned with land allocation and investment decisions when dealing with partially degraded areas that might be (1) remediated and returned to a more natural state or (2) irreversibly developed. This type of problem seems particularly relevant in Europe where the issue of wilderness conservation is of less concern than the remediation of landscapes which have been altered by previous economic activities. Traditional expected present value analysis will fail to capture the value of investments that might be undertaken sequentially or when certain investments are irreversible. We show how to determine, within a discrete-time, stochastic model, the optimal adaptive development strategy and how to calculate the option value of flexibility. The theoretical model is then applied to Ginostra, a town on Stromboli, an island off the southern coast of Italy. JEL Codes: D81, Q24, Q26 Date of this version: 4/3/2002 V. Bosetti is a Ph.D. Candidate in Computational Mathematics and Operations Research and E. Messina is Professor of Operations Research in the Department of Informatics, both at the Università degli Studi di Milano, Italy. J. M. Conrad is Professor of Applied Economics and Management at Cornell University. Correspondence relating to this manuscript should be addressed to Professor Conrad at 455 Warren Hall, Cornell University, Ithaca, New York, 14853, USA, or by email to JMC16@cornell.edu (Phone: 607 255-7681, Fax: 607 255-9984).
Depth-First Non-Derivable Itemset Mining

Mining frequent itemsets is one of the main problems in data mining. Much effort went into developing efficient and scalable algorithms for this problem. When the support threshold is set too low, however, or the data is highly correlated, the number of frequent itemsets can become too large, independently of the algorithm used. Therefore, it is often more interesting to mine a reduced collection of interesting itemsets, i.e., a condensed representation. Recently, in this context, the non-derivable itemsets were proposed as an important class of itemsets. An itemset is called derivable when its support is completely determined by the support of its subsets. As such, derivable itemsets represent redundant information and can be pruned from the collection of frequent itemsets. It was shown both theoretically and experimentally that the collection of non-derivable frequent itemsets is in general much smaller than the complete set of frequent itemsets. A breadth-first, Apriori-based algorithm, called NDI, to find all non-derivable itemsets was proposed. In this paper we present a depth-first algorithm, dfNDI, that is based on Eclat for mining the non-derivable itemsets. dfNDI is evaluated on real-life datasets, and experiments show that dfNDI outperforms NDI with an order of magnitude.
The South African economy: Its growth and change

The second edition of this reference book has been completely updated and includes a new chapter on trade unions in South Africa, recent legislation affecting economic growth, the role played by the State in South African affairs through the tricameral system, and the development of the Black States. The authors are not slow to criticize those whom they perceive to be retarding the economic growth of South Africa.
Antispasmodic effects of yarrow (Achillea millefolium L.) extract in the isolated ileum of rat.

Achillea millefolium L. is cultivated in Iran and widely used in traditional medicine for gastrointestinal disorders. The aim of this study was to determine the effect of hydroalcoholic extract of A. millefolium on the contraction and relaxation of isolated ileum in rat. In this experimental study, aerial parts of A. millefolium were extracted by maceration in ethanol 70% for 72 h. Terminal portion of ileum in 100 male Wistar rats was dissected and its contractions were recorded isotonically in an organ bath containing Tyrode solution (37 °C, pH 7.4) under one gram tension. Acetylcholine (1mM) and KCl (60mM) were used to create isotonic contractions. Propranolol and Nω-Nitro-L-arginine methylester hydrochloride (L-NAME) were used to investigate the mechanisms of action prior to giving the extract to the relevant groups. Data were compared by ANOVA and Turkey's post hoc test. The results showed that the ileum contraction was induced by KCl and acetylcholine induced contraction was significantly reduced by A. millefolium extract. The cumulative concentrations of A. millefolium relaxed the KCl and acetylcholine induced contractions (n=14, p<0.001). The inhibitory effect of extract on contraction induced by KCl and acetylcholine was not significantly affected neither by propranolol (1µM) nor by L-NAME (100 µM). There was no significant difference in the rate of relaxation by propranolol and L-NAME between the two groups. In conclusion, A. millefolium can inhibit contraction of smooth muscle of ileum in rat, and it can be used for eliminating intestinal spasms. These results suggest that the relaxatory effect of A. millefolium on ileum contractions can be due to the blockade of voltage dependent calcium channels. In addition, the β-adrenoceptors, cholinergic receptors and nitric oxide production are not powerful actors in inhibitory effect of A. millefolium. So, the nitric oxide and adrenergic systems may also be involved in the antispasmodic effect of A. millefolium.
Selection based detection method for spectrum sensing for cognitive radio

In this paper we describe a selection based detection method for spectrum sensing in cognitive radio which is a combination of both energy detection and covariance absolute value detection method. Comparison is made between energy detection and covariance absolute value methods for different type of input data. It is shown from the simulation results and theoretical analysis that the performance of the selection based method is more insensitive to the type of input data.
Perspective: microarray technology, seeing more than spots.

The publication in the mid-1990s of a new molecular tool, the DNA microarray, has led to a revolution in the way scientists approach the investigation of gene expression and regulation. This technology has made its impact upon many basic scientific disciplines including cancer biology, developmental biology, toxicology, investigation of growth-factor and hormonal signaling, and the applied areas of disease diagnostics and drug development. The ability to assay thousands of genes simultaneously in a high-throughput manner across RNA samples derived from various biological sources and treatments has increased the need for integration of higher-order statistical analyses and data management schema into molecular biology laboratories. Many investigators are struggling with interpreting large, complex datasets, communicating their findings, and developing strategies for following up numerous potential leads indicated in datasets. This perspective provides an overview of the technology and its impact, as well as strategies for study design, data analysis, and avoidance of potential pitfalls.
Tunable scheduling in a GridRPC framework

Among existing grid middleware approaches, one simple, powerful, and flexible approach consists of using servers available in different administrative domains through the classic client–server or remote procedure call paradigm. Network Enabled Servers (NES) implement this model, also called GridRPC. Clients submit computation requests to a scheduler, whose goal is to find a server available on the grid using some performance metric. The aim of this paper is to give an overview of a NES middleware developed in the GRAAL team called distributed interactive engineering toolbox (DIET) and to describe recent developments around plug‐in schedulers, workflow management, and tools. DIET is a hierarchical set of components used for the development of applications based on computational servers on the grid. Copyright © 2007 John Wiley & Sons, Ltd.
DETECTING ANOMALOUS TRAJECTORIES FROM HIGHWAY TRAFFIC DATA

In this paper we modify our unsupervised anomaly detection algorithm [1,2] and apply it to highway traffic anomaly analysis. We propose a method to identify anomalies under a probabilistic framework. Instead of determining anomalies based on the size of each cluster, they are determined in a probabilistic framework. Moreover, we present our findings on using different features when analyzing real highway vehicle trajectory data. Based on real highway traffic video data we demonstrate that the inclusion of certain features, brings us closer to identifying events that are both anomalous and abnormal (based on driving rules).
Circadian waves of expression of the APRR1/TOC1 family of pseudo-response regulators in Arabidopsis thaliana: insight into the plant circadian clock.

The Arabidopsis pseudo-response regulator, APRR1, has a unique structural design containing a pseudo-receiver domain and a C-terminal CONSTANS motif. This protein was originally characterized as a presumed component of the His-to-Asp phosphorelay systems in Arabidopsis thaliana. Recently, it was reported that APRR1 is identical to the TOC1 gene product, a mutational lesion of which affects the periods of many circadian rhythms in Arabidopsis plants. TOC1 is believed to be a component of the presumed circadian clock (or central oscillator). Based on these facts, in this study four more genes, each encoding a member of the APRR1/TOC1 family of pseudo-response regulators were identified and characterized with special reference to circadian rhythms. It was found that all these members of the APRR1/TOC1 family (APRR1, APRR3, APRR5, APRR7, and APRR9) are subjected to a circadian rhythm at the level of transcription. Furthermore, in a given 24 h period, the APRR-mRNAs started accumulating sequentially after dawn with 2-3 h intervals in the order of APRR9-->APRR7-->APRR5-->APRR3-->APRR1. These sequential events of transcription, termed 'circadian waves of APRR1/TOCI', were not significantly affected by the photoperiod conditions, if any (e.g. both long and short days), and the expression of APRR9 was first boosted always after dawn. Among these APRRs, in fact, only the expression of APRR9 was rapidly and transiently induced also by white light, whereas such light responses of others were very dull, if any. These results collectively support the view that these members of the APRR1/TOC1 family are together all involved in an as yet unknown mechanism underlying the Arabidopsis circadian clock. Here we propose that the circadian waves of the APRR1/TOC1 family members are most likely a molecular basis of such a biological clock in higher plants.
RELATIONSHIP BETWEEN GDP GROWTH AND OIL AND NATURAL GAS CONSUMPTION IN EU COUNTRIES

Crude oil and natural gas, as energy carriers forming the basis of European Union countries energy mix, are nowadays at the heart of policy measurements aiming at lowering their consumption with respect to environmental and security threats associated with them. In this article we used Granger causality test in order to examine whether there exists the possibility of negative consequence related to the implementation of such policy for economic development of the EU countries. Based on results we conclude the persistence of continuing existence of environmental risks in relation to restarting economic growth. The absence of more significant influence of oil and gas consumption on economic growth can be perceived positively.
Nutrition Controls Mitochondrial Biogenesis in the Drosophila Adipose Tissue through Delg and Cyclin D/Cdk4

Mitochondria are cellular organelles that perform critical metabolic functions: they generate energy from nutrients but also provide metabolites for de novo synthesis of fatty acids and several amino acids. Thus mitochondrial mass and activity must be coordinated with nutrient availability, yet this remains poorly understood. Here, we demonstrate that Drosophila larvae grown in low yeast food have strong defects in mitochondrial abundance and respiration activity in the larval fat body. This correlates with reduced expression of genes encoding mitochondrial proteins, particularly genes involved in oxidative phosphorylation. Second, genes involved in glutamine metabolism are also expressed in a nutrient-dependent manner, suggesting a coordination of amino acid synthesis with mitochondrial abundance and activity. Moreover, we show that Delg (CG6338), the Drosophila homologue to the alpha subunit of mammalian transcription factor NRF-2/GABP, is required for proper expression of most genes encoding mitochondrial proteins. Our data demonstrate that Delg is critical to adjust mitochondrial abundance in respect to Cyclin D/Cdk4, a growth-promoting complex and glutamine metabolism according to nutrient availability. However, in contrast to nutrients, Delg is not involved in the regulation of mitochondrial activity in the fat body. These findings are the first genetic evidence that the regulation of mitochondrial mass can be uncoupled from mitochondrial activity.
Localized glaucomatous change detection within the proper orthogonal decomposition framework.

PURPOSE To detect localized glaucomatous structural changes using proper orthogonal decomposition (POD) framework with false-positive control that minimizes confirmatory follow-ups, and to compare the results to topographic change analysis (TCA). METHODS We included 167 participants (246 eyes) with ≥4 Heidelberg Retina Tomograph (HRT)-II exams from the Diagnostic Innovations in Glaucoma Study; 36 eyes progressed by stereo-photographs or visual fields. All other patient eyes (n = 210) were non-progressing. Specificities were evaluated using 21 normal eyes. Significance of change at each HRT superpixel between each follow-up and its nearest baseline (obtained using POD) was estimated using mixed-effects ANOVA. Locations with significant reduction in retinal height (red pixels) were determined using Bonferroni, Lehmann-Romano k-family-wise error rate (k-FWER), and Benjamini-Hochberg false discovery rate (FDR) type I error control procedures. Observed positive rate (OPR) in each follow-up was calculated as a ratio of number of red pixels within disk to disk size. Progression by POD was defined as one or more follow-ups with OPR greater than the anticipated false-positive rate. TCA was evaluated using the recently proposed liberal, moderate, and conservative progression criteria. RESULTS Sensitivity in progressors, specificity in normals, and specificity in non-progressors, respectively, were POD-Bonferroni = 100%, 0%, and 0%; POD k-FWER = 78%, 86%, and 43%; POD-FDR = 78%, 86%, and 43%; POD k-FWER with retinal height change ≥50 μm = 61%, 95%, and 60%; TCA-liberal = 86%, 62%, and 21%; TCA-moderate = 53%, 100%, and 70%; and TCA-conservative = 17%, 100%, and 84%. CONCLUSIONS With a stronger control of type I errors, k-FWER in POD framework minimized confirmatory follow-ups while providing diagnostic accuracy comparable to TCA. Thus, POD with k-FWER shows promise to reduce the number of confirmatory follow-ups required for clinical care and studies evaluating new glaucoma treatments. (ClinicalTrials.gov number, NCT00221897.).
Australian Tax Reforms: Past and Future

The eminent contributors (including Altshuler, Creedy, Freebairn, Gravelle, Heady, Kalb, Sorensen and Zodrow) investigate the beneficial directions for medium-term tax reform in the light of global developments and lessons from the latest taxation research. In addressing this issue, they review recent advances in both the theoretical and empirical tax literature and reform evidence from individual countries. Topics covered include the impact of taxes on economic performance; international and corporate taxation; personal tax and welfare systems; environmental taxation; and country-specific tax reform experiences.