Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fast Decision Technique for Hierarchical Hough Transform for Line Detection

Many techniques have been proposed to speedup the performance of classic Hough Transform. These techniques are primarily based on converting the voting procedure to a hierarchy based voting method. These methods use approximate decision-making process. In this paper, we propose a fast decision making process that enhances the speed and reduces the space requirements. Experimental results demonstrate that the proposed algorithm is much faster than a similar Fast Hough Transform.
Improvement of missing genotype imputation through bi-directional parsing of large SNP panels

Such difficult analyses as disease association studies, which aim at mappping genetic variants underlying complex human diseases, rely on high-throughput genotyping techniques. However, a shortcoming of these techniques is the generation of missing calls. Computational inference of missing data represents a challenging alternative to genotyping again the missing regions. In this paper, we present SNPShuttle, an algorithm designed to gain accuracy over a former method described by Roberts and co-authors (2007), NPUTE. Given an SNP panel, NPUTE algorithm infers missing data through a single parse, relying on local similarity within sliding windows. Instead, SNPShuttle scans an SNP panel in an iterative bi-directional way, to resolve missing data with more confidence.
Visual saliency detection based on topographic independent component analysis

A computational model of visual saliency detection is proposed based on topographic independent component analysis. This model consists of three steps: first training basis functions and extracting features which represents complex cell responses by topographic independent component analysis, then estimating feature distributions, and finally calculating self-information and obtaining saliency maps. It is demonstrated by numerical examples that the proposed model could detect saliency regions in some circumstances when previous related model couldn't, and predict human attention fixations better than other models.
Upregulation of Aldose Reductase During Foam Cell Formation as Possible Link Among Diabetes, Hyperlipidemia, and Atherosclerosis

Objective—Aldose reductase (AR) is the rate-limiting enzyme of the polyol pathway. In diabetes, it is related to microvascular complications. We discovered AR expression in foam cells by gene chip screening and hypothesized that it may be relevant in atherosclerosis. Methods and Results—AR gene expression and activity were found to be increased in human blood monocyte-derived macrophages during foam cell formation induced by oxidized LDL (oxLDL, 100 &mgr;g/mL). AR activity as photometrically determined by NADPH consumption was effectively inhibited by the AR inhibitor epalrestat. oxLDL-dependent AR upregulation was further increased under hyperglycemic conditions (30 mmol/L D-glucose) as compared to osmotic control, suggesting a synergistic effect of hyperlipidemia and hyperglycemia. AR was also upregulated by 4-hydroxynonenal, a constituent of oxLDL. Upregulation was blocked by an antibody to CD36. AR inhibition resulted in reduction of oxLDL-induced intracellular oxidative stress as determined by 2′7′-dichlorofluoresceine diacetate (H2DCFDA) fluorescence, indicating that proinflammatory effects of oxLDL are partly mediated by AR. Immunohistochemistry showed AR expression in CD68+ human atherosclerotic plaque macrophages. Conclusions—These data show that oxLDL-induced upregulation of AR in human macrophages is proinflammatory in foam cells and may represent a potential link among hyperlipidemia, atherosclerosis, and diabetes mellitus.
epsilon-Kernel Coresets for Stochastic Points

With the dramatic growth in the number of application domains that generate probabilistic, noisy and uncertain data, there has been an increasing interest in designing algorithms for geometric or combinatorial optimization problems over such data. In this paper, we initiate the study of constructing $\epsilon$-kernel coresets for uncertain points. We consider uncertainty in the existential model where each point's location is fixed but only occurs with a certain probability, and the locational model where each point has a probability distribution describing its location. An $\epsilon$-kernel coreset approximates the width of a point set in any direction. We consider approximating the expected width (an \expkernel), as well as the probability distribution on the width (an \probkernel) for any direction. We show that there exists a set of $O(1/\epsilon^{(d-1)/2})$ deterministic points which approximate the expected width under the existential and locational models, and we provide efficient algorithms for constructing such coresets. We show, however, it is not always possible to find a subset of the original uncertain points which provides such an approximation. However, if the existential probability of each point is lower bounded by a constant, an exp-kernel\ (or an fpow-kernel) is still possible. We also construct an quant-kernel coreset in linear time. Finally, combining with known techniques, we show a few applications to approximating the extent of uncertain functions, maintaining extent measures for stochastic moving points and some shape fitting problems under uncertainty.
Identification of FOXP1 Deletions in Three Unrelated Patients with Mental Retardation and Significant Speech and Language Deficits

Mental retardation affects 2‐3% of the population and shows a high heritability. Neurodevelopmental disorders that include pronounced impairment in language and speech skills occur less frequently. For most cases, the molecular basis of mental retardation with or without speech and language disorder is unknown due to the heterogeneity of underlying genetic factors. We have used molecular karyotyping on 1523 patients with mental retardation to detect copy number variations (CNVs) including deletions or duplications. These studies revealed three heterozygous overlapping deletions solely affecting the forkhead box P1 (FOXP1) gene. All three patients had moderate mental retardation and significant language and speech deficits. Since our results are consistent with a de novo occurrence of these deletions, we considered them as causal although we detected a single large deletion including FOXP1 and additional genes in 4104 ancestrally matched controls. These findings are of interest with regard to the structural and functional relationship between FOXP1 and FOXP2. Mutations in FOXP2 have been previously related to monogenic cases of developmental verbal dyspraxia. Both FOXP1 and FOXP2 are expressed in songbird and human brain regions that are important for the developmental processes that culminate in speech and language. ©2010 Wiley‐Liss, Inc.
The Relationship between Strategic Planning and Firm Performance

Organizations from both the private and public sector are increasingly embracing the practice of strategic planning in anticipation that this will translate to improved performance. Past studies have mainly focused on the direct relationship between strategic planning and performance and did not give attention to the specific steps that make up the strategic planning process. The manner and extent to which each of the steps is practiced could have implications on the expected strategic planning results. This study examined the relationship between strategic planning and firm performance giving attention to the strategic planning steps. Correlation analysis results indicate the existence of a strong relationship between strategic planning and firm performance. Further, all the strategic planning steps (defining firm’s corporate purpose, scanning of business environment, identification of firm’s strategic issues, strategy choice and setting up of implementation, evaluation and control systems) were found to be positively related to company performance.
Beauty Contests and Iterated Expectations in Asset Markets

In a financial market where traders are risk averse and short lived and prices are noisy, asset prices today depend on the average expectation today of tomorrow's price. Thus (iterating this relationship) the date 1 price equals the date 1 average expectation of the date 2 average expectation of the date 3 price. This will not, in general, equal the date 1 average expectation of the date 3 price. We show how this failure of the law of iterated expectations for average belief can help understand the role of higher-order beliefs in a fully rational asset pricing model. ''… professional investment may be likened to those newspaper competitions in which the competitors have to pick out the six prettiest faces from a hundred photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole; so that each competitor has to pick, not those faces which he himself finds prettiest, but those which he thinks likeliest to catch the fancy of the other competitors, all of whom are looking at the problem from the same point of view. It is not a case of choosing those which, to the best of one's judgement, are really the prettiest, nor even those which average opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practise the fourth, fifth and higher degrees. '' Keynes (1936), page 156. We are grateful to seminar participants at LSE, Bank of England, IMF, Kellogg, Stanford, the Chicago accounting theory conference, the Gerzensee finance meetings, and to participants at the AFA San Diego meetings and our discussant Andrei Shleifer for their comments. We thank Mehul Kamdar for capable research assistance. We are grateful to the editor, Maureen O'Hara, and a referee for their guidance.
Reverse engineering and design recovery: a taxonomy

The key to applying computer-aided software engineering to the maintenance and enhancement of existing systems lies in applying reverse-engineering approaches. However, there is considerable confusion over the terminology used in both technical and marketplace discussions. The authors define and relate six terms: forward engineering, reverse engineering, redocumentation, design recovery, restructuring, and reengineering. The objective is not to create new terms but to rationalize the terms already in use. The resulting definitions apply to the underlying engineering processes, regardless of the degree of automation applied. <<ETX>>
Power System Dynamic State Estimation by Unscented Kalman Filter with Guaranteed Positive Semi-definite State Covariance

In this paper an unscented Kalman filter with guaranteed positive semidefinite state covariance is proposed by calculating the nearest symmetric positive definite matrix in Frobenius norm and is applied to power system dynamic state estimation. The proposed method is tested on NPCC 48-machine 140-bus system and the results validate its effectiveness.
1 Basic Background in 3 D Object Processing

This chapter details the different 3D representation models, commonly used in computer graphics and 3D modeling. We distinguish three main representation schemes: polygonal meshes; surface-based models, such as parametric, implicit and subdivision surfaces; and volumetric models including primitivebased models (superquadric, hyperquadric), voxel representation and constructive solid geometry. For each of these 3D representation schemes, we analyze the advantages and drawbacks in terms of modeling, regarding different applications. The point-based representation, which has been recently introduced in computer graphics, is not within the scope of this book. Recent reviews can be found in Kobbelt and Botsch (2004) and Alexa et al. (2004).
Becoming popular: interpersonal emotion regulation predicts relationship formation in real life social networks

Building relationships is crucial for satisfaction and success, especially when entering new social contexts. In the present paper, we investigate whether attempting to improve others’ feelings helps people to make connections in new networks. In Study 1, a social network study following new networks of people for a 12-week period indicated that use of interpersonal emotion regulation (IER) strategies predicted growth in popularity, as indicated by other network members’ reports of spending time with the person, in work and non-work interactions. In Study 2, linguistic analysis of the tweets from over 8000 Twitter users from formation of their accounts revealed that use of IER predicted greater popularity in terms of the number of followers gained. However, not all types of IER had positive effects. Behavioral IER strategies (which use behavior to reassure or comfort in order to regulate affect) were associated with greater popularity, while cognitive strategies (which change a person’s thoughts about his or her situation or feelings in order to regulate affect) were negatively associated with popularity. Our findings have implications for our understanding of how new relationships are formed, highlighting the important the role played by intentional emotion regulatory processes.
Linear Discriminant Analysis on Brain Computer Interface

This report analyses the application of Linear Discriminant Analysis in Brain Computer Interface technology. It is aimed to obtain an objective evaluation of the discrimination capability achieved when different filtering windows are considered in order to differentiate between three different cerebral activities. In this report the following issues are discussed: quantification of the discrimination capability between the employed cerebral activities, identification of the frequency bands with the highest discrimination power, methodology to weight the amplitude of the previous frequency bands in order to reduce the dimensionality of the feature space and facilitate posterior analysis, without lost of intrinsic characteristics of each cerebral activity, determination of the best preprocess window. Linear Discrimination Analysis is employed in order to reduce the dimensionality of the input feature space; bilateral contrasts between features, inferred from each cerebral activity, are used to determine the discrimination power.
Liquidity Effects and the Monetary Transmission Mechanism

Several recent papers provide strong empirical support for the view that an expansionary monetary policy disturbance generates a persistent decrease in interest rates and a persistent increase in output and employment. Existing quantitative general equilibrium models, which allow for capital accumulation, are inconsistent with this view. There does exist a recently developed class of general equilibrium models which can rationalize the contemporaneous response of interest rates, output, and employment to a money supply shock. However, a key shortcoming of these models is that they cannot rationalize persistent liquidity effects. This paper discusses the basic frictions and mechanisms underlying this new class of models and investigates one avenue for generating persistence. We argue that once a simplified version of the model in Christiano and Eichenbaum (1991) is modified to allow for extremely small costs of adjusting sectoral flow of funds, positive money shocks generate long-lasting, quantitatively significant liquidity effects, as well as persistent increases in aggregate economic activity.
Rules and Discretion with Non-coordinated Monetary and Fiscal Policy

The time inconsistency of optimal monetary policy is due to the effects of tax distortions. Thus, the issue of how to im prove upon the time-consistent suboptimal monetary policy is related to that of the coordination of monetary and fiscal policy. The author s present a model with three players (the central bank, the fiscal au thority, and wage setters) in which distortionary taxes are explicitl y modeled. They show that binding commitments to monetary rules are n ot necessarily welfare improving if monetary and fiscal policy are no t coordinated. They also examine the effects of different degrees of independence of the central bank. Copyright 1987 by Oxford University Press.
Jasmonate-Mediated Induced Volatiles in the American Cranberry, Vaccinium macrocarpon: From Gene Expression to Organismal Interactions

Jasmonates, i.e., jasmonic acid (JA) and methyl jasmonate (MeJA), are signaling hormones that regulate a large number of defense responses in plants which in turn affect the plants’ interactions with herbivores and their natural enemies. Here, we investigated the effect of jasmonates on the emission of volatiles in the American cranberry, Vaccinium macrocarpon, at different levels of biological organization from gene expression to organismal interactions. At the molecular level, four genes (BCS, LLS, NER1, and TPS21) responded significantly to gypsy moth larval feeding, MeJA, and mechanical wounding, but to different degrees. The most dramatic changes in expression of BCS and TPS21 (genes in the sesquiterpenoid pathway) were when treated with MeJA. Gypsy moth-damaged and MeJA-treated plants also had significantly elevated expression of LLS and NER1 (genes in the monoterpene and homoterpene biosynthesis pathways, respectively). At the biochemical level, MeJA induced a complex blend of monoterpene and sesquiterpene compounds that differed from gypsy moth and mechanical damage, and followed a diurnal pattern of emission. At the organismal level, numbers of Sparganothis sulfureana moths were lower while numbers of parasitic wasps were higher on sticky traps near MeJA-treated cranberry plants than those near untreated plants. Out of 11 leaf volatiles tested, (Z)-3-hexenyl acetate, linalool, and linalool oxide elicited strong antennal (EAG) responses from S. sulfureana, whereas sesquiterpenes elicited weak EAG responses. In addition, mortality of S. sulfureana larvae increased by about 43% in JA treated cranberry plants as compared with untreated plants, indicating a relationship among adult preference, antennal sensitivity to plant odors, and offspring performance. This study highlights the role of the jasmonate-dependent defensive pathway in the emissions of herbivore-induced volatiles in cranberries and its importance in multi-trophic level interactions.
Customized Automatic Load Sharing For a Network of Workstations

There are various Internet applications such as financial transactions, database access are always running on the Internet Server. Those applications must be able to run on multiple servers to accept an ever increasing number of users and networks need the ability to scale the performance to handle large volumes of client requests without creating unwanted delays. So, load sharing concept must be implemented for better performance as well as to increase the ability to handle more number of users. For these reasons, clustering is of wide interest to the enterprise. Clustering enables a group of independent servers to be managed as a single system for higher availability, easier manageability, and greater scalability.
IMF Essays from a Time of Crisis: The International Financial System, Stabilization, and Development

Stanley Fischer served as First Deputy Managing Director of the International Monetary Fund from 1994 to 2001. IMF Essays from a Time of Crisis collects sixteen essays written for the most part during his time at the IMF, each updated with Fischer's later reflections on the issues raised. The IMF drew much criticism for some of its actions during Fischer's tenure, and he vigorously defends the "battlefield medicine" practiced by the IMF during a series of economic crises, which included the problems of economic transition in the former Soviet bloc and the Asian financial crisis. Fischer addresses the subsequent calls for reform of the international financial system and makes the case for the IMF as an international lender of last resort. The first section of essays, "The Role of the IMF and the Reform of the International Financial System," considers the IMF's role in the international financial system in light of the crises of the 1990s. The second section, "Macroeconomic Policy, Stabilization, and Transition," examines such topics as exchange rate regimes, inflation, and Eastern Europe's relation to the European Union. The final section, "Poverty and Development," reflects Fischer's basic belief that economic policies should explicitly target poverty reduction. These engaging and accessible essays will appeal not only to economics students, economists, and policymakers but also to the general reader interested in the international monetary system.
Access Schemes for Mobile Cloud Computing

Mobile Cloud Computing is widely accepted as a concept that can significantly improve the user experience when accessing mobile services. By removing the limitations of mobile devices with respect to storage and computing capabilities and providing a new level of security by a centralized maintenance of security-critical software for e.g. mobile payment applications, it is expected that it will find broad acceptance on the business as well as consumer side. Research indicates [1] that Mobile Cloud Computing will additionally help to make visions of context services become reality. However, Mobile Cloud Computing concepts rely on an always-on connectivity and will need to provide a scalable and - when requested - quality mobile access. ”Intelligent access” schemes meeting these requirements will be discussed in this paper. They exploit the specific information available by the ”Mobile Cloud Controller”, i.e., theusers’ location, context, and requested services, and significantly evolve the Heterogeneous Access Management schemes developed for the traditional heterogeneous access scenarios. In order to evaluate the performance of these intelligent radio access management concepts in the framework of mobile cloud computing, a specialized radio network simulator will be introduced. It will be shown that a Mobile Cloud Controller establishing a Context Management Architecture can provide the requested availability and quality of mobile connectivity.
Fine Motor Skills Predict Maths Ability Better than They Predict Reading Ability in the Early Primary School Years

Fine motor skills have long been recognized as an important foundation for development in other domains. However, more precise insights into the role of fine motor skills, and their relationships to other skills in mediating early educational achievements, are needed to support the development of optimal educational interventions. We explored concurrent relationships between two components of fine motor skills, Fine Motor Precision and Fine Motor Integration, and early reading and maths development in two studies with primary school children of low-to-mid socio-economic status in the UK. Two key findings were revealed. First, despite being in the first 2 years of primary school education, significantly better performance was found in reading compared to maths across both studies. This may reflect the protective effects of recent national-level interventions to promote early literacy skills in young children in the UK that have not been similarly promoted for maths. Second, fine motor skills were a better predictor of early maths ability than they were of early reading ability. Hierarchical multiple regression revealed that fine motor skills did not significantly predict reading ability when verbal short-term memory was taken into account. In contrast, Fine Motor Integration remained a significant predictor of maths ability, even after the influence of non-verbal IQ had been accounted for. These results suggest that fine motor skills should have a pivotal role in educational interventions designed to support the development of early mathematical skills.