Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring congruence of spatial objects

This article develops and tests an algorithm of spatial congruence based on geometric congruity of two spatial areal objects in the Euclidean plane. Spatial congruence is defined and thus evaluated as an increasing continuous function of congruity in the position, orientation, size, and shape of spatial objects, dependent upon scaling, translation, and rotation. Expansion-based geometric matching is used to seek the best match between the two objects of interest for the examination and differentiation of the congruence effects of their spatial and geometric properties, while the expansion-inflated size effect is deflated or filtered out accordingly. The use of both expansion and deflation not only allows for a trade-off between size and position, both of which are found substitutable for each other in congruence measurement, but also enables the congruence algorithm to be highly sensitive to differences or changes in these properties. Three geographical objects (the states of Texas, Mississippi, and Louisiana) are used to show how trade-offs among the four properties are manipulated by the congruence algorithm in a geographic information system (GIS) environment, ArcGIS®. In addition, three regular geometric objects are used to demonstrate how the congruence algorithm is sensitive even to small changes in each of the four properties of objects. The results show that the proposed congruence algorithm is capable of quantifying the extent of congruity between two spatial objects regardless of how they are related as described in topological relations.
On Compatible Priors for Bayesian Networks

Given a Bayesian network of discrete random variables with a hyper-Dirichlet prior, a method is proposed for assigning Dirichlet priors to the conditional probabilities of structurally different networks. It defines a distance measure between priors which is to be minimized for the assignment process. Intuitively one would expect that if two models priors are to qualify as being 'close' in some sense, then their posteriors should also be nearby after an observation. However one does not know in advance what will be observed next. Thus we are led to propose an expectation of Kullback-Leibler distances over all possible next observations to define a measure of distance between priors. In conjunction with the additional assumptions of global and local independence of the parameters, a number of theorems emerge which are usually taken as reasonable assumptions in the Bayesian network literature. A simple example is given to illustrate the technique.
Novel feature for identification of focal EEG signals with k-Means and fuzzy c-means algorithms

In this paper, a new method for automatic identification of focal electroencephalogram (EEG) signals is proposed. Detection of focal EEG signals locates the epileptogenic area which is an important task for successful surgery. The proposed method is based on empirical mode decomposition (EMD) that uses the ratio of amplitude modulation bandwidth (BAM) and frequency modulation bandwidth (BFM), as a feature for identification of focal EEG signals. The feature average bandwidths ratio (AvgBratio) extracted from analytic intrinsic mode functions (IMFs) is set to input in k-Means and fuzzy c-mean (FCM) unsupervised learning. Statistical test Kruskal-Wallis shows the effective discrimination ability of the feature. The experimental results shows that proposed method is precisely proficient to classify focal and non-focal EEG signals using single narrow frequency band. A comparative analysis of both unsupervised learning techniques is performed by elapsed time, time complexity, and accuracy.
The unified algorithm for detection of potential lesions in dynamic perfusion maps cerebral blood flow, cerebral blood volume and time to peek

This paper presents an unified algorithm that enables detection of lesions in cerebral blood flow (CBF), cerebral blood volume (CBV) and time to peek (TTP) perfusion maps. The algorithm has one adaptive parameter for each type of perfusion map, the rest of algorithm is common for all kinds of perfusion images. There are two steps of the algorithm: in the first step the algorithm detects symmetry axis of a perfusion map (between left and right hemisphere), in the second stage the level of asymmetry in cerebral blood flow, cerebral blood volume or time to peak is measured by detection of regions with different perfusion in both brain hemispheres. Test of the algorithm were performed on a set of 84 different CBF, CBV and TTP images showing or not cerebral blood flow and volume anomalies. The algorithm presented in this publication has achieved satisfactory results. On 85,7% maps asymmetry regions was properly detected.
Privatization and Performance : The Experience of Firms in China

This article investigates the effects of privatization on corporate performance in China. We focus on two very different industries: the manufacturing industry--the largest (relatively) competitive industry in China--and the basic material industry--the largest industry protected and closely monitored by the central government. We find that privatization to the domestic public has only a small positive effect on corporate performance for the manufacturing industry, but does not have any effect for the basic material industry, suggesting that privatization does not work when competition does not prevail. We also find that privatization to institutions hurts corporate performance for the manufacturing industry, but not for the basic material industry, suggesting that control by legal person shares often means additional layers of bureaucracy and higher agency costs, unless the central government closely monitors the firms, mitigating the agency problems.
The proinflammatory LTB4/BLT1 signal axis confers resistance to TGF-β1-induced growth inhibition by targeting Smad3 linker region

Leukotriene B4 (LTB4) is a potent pro-inflammatory eicosanoid that is derived from arachidonic acid, and its signaling is known to have a tumor-promoting role in several cancer types. In this study, we investigated whether enhanced LTB4 signaling confers resistance to the cytostatic transforming growth factor-β1 (TGF-β1) response. We found that LTB4 pretreatment or ectopic expression of BLT1, a high affinity LTB4 receptor, fully abrogated TGF-β1-induced cell cycle arrest and expression of p15INK4B and p27KIP1. Mechanism study revealed that LTB4-mediated suppression of TGF-β1-induced Smad3 activation and growth inhibition was due to enhanced phosphorylation of Smad3 linker region (pSmad3L) through activation of BLT1-NAD(P)H oxidase (NOX)-reactive oxygen species (ROS)-epidermal growth factor receptor (EGFR)-phosphatidylinositol 3-kinase (PI3-K)-extracellular signal-activated kinase1/2 (ERK1/2)-linked signaling cascade. Furthermore, the LTB4/BLT1 signaling pathway leading to pSmad3L was constitutively activated in breast cancer cells and was correlated with TGF-β1-resistant growth of the cells in vitro and in vivo. In human breast cancer tissues, the expression level of pSmad3L (Thr179) had a positive correlation with BLT1 expression. Collectively, our data demonstrate for the first time that the induction of pSmad3L through BLT1-NOX-ROS-EGFR-PI3K-ERK1/2 signaling pathway is a key mechanism by which LTB4 blocks the anti-proliferative responses of TGF-β1, providing a novel mechanistic insight into the connection between enhanced inflammatory signal and cancer cell growth.
Interest point detection for vision based mobile robot navigation

A problem of interest point detection in camera images, i.e. detection of points with high information content is studied. An overview of existing techniques is given. A modified Harris-Laplace interest point detector is proposed and experimental results are given. Proposed detector generates a smaller number of detected points, resulting in less complex matching. The aim is to use interest point detectors, descriptors and matching for mobile robot navigation.
MASTER'S THESIS Visual Servoing for a Quadcopter Flight Control

In this thesis the potential of visual servoing techniques for vertical take-off and landing (VTOL) UAV platforms is explored. An overview of UAV applications and state-of-theart quadrotors is provided, backed up by the necessary theoretical background. Visual servoing based solutions of the important flight tasks (such as vertical take-off and landing, obstacle avoidance and attitude estimation) are presented. A novel vision based autopilot for vertical take-off and landing is developed, experimentally verified and implemented on a medium-size outdoor quadrotor platform provided by Dr. YangQuan Chen from Utah State University, Center for Self-Organizing Intelligent Systems.
Impact of Functional Constipation on Health-Related Quality of Life in Preschool Children and Their Families in Xi’an, China

Aim Functional constipation (FC) is one of the common diseases among children. The aim of this study was to investigate the health-related quality of life (HRQOL) in preschool children diagnosed with FC and the impact of the condition on affected families. Methods In this cross-sectional, case-control study, 152 children aged 3–6 years with FC, 176 healthy children aged 3–6 years without FC, and their primary caregivers were selected. Chinese versions of the PedsQLTM 4.0 Generic Core Scale and the Family Impact Module (FIM) were used to assess childhood HRQOL and the impact of FC on family members, respectively. HRQOL scores were compared between children with FC and healthy children. In addition, a multiple step-wise regression with demographic variables of children and their caregivers, family economic status, duration and symptoms of FC, as independent variables, was used to determine factors that influenced HRQOL in children and had impacted caregivers. Results Scores of physical, emotional, social and school functions, and summary scales were significantly lower in children with FC than in healthy children (p < 0.05). Physical, emotional, social, cognitive, and communication scores for caregivers, as well as daily activities and relationships for families of children with FC, were significantly lower than those of caregivers and families with healthy children (p < 0.05). Children’s ages, duration of FC, symptoms of FC, the child-caregiver relationship, family economic status, and caregiver education level emerged as the main factors influencing HRQOL in children, caregivers, and family members. Conclusions FC had a significant impact on HRQOL of affected children and their caregivers, as well as their family functions. Social characteristics of children and caregivers, duration and symptoms of FC and family economic status significantly affected HRQOL of children and caregivers, as well as family functions of children with FC.
Two Centuries of American Macroeconomic Growth From Exploitation of Resource Abundance to Knowledge-Driven Development

This monograph is concerned with the nature of the process of macroeconomic growth that has characterized the U. S. experience, and manifested itself in the changing pace and sources of the continuing rise real output per capita over the course of the past two hundred years. A key observation that emerges from the long-term quantitative economic record is that the proximate sources of increases in real GDP per head in the century between 1889 and 1999 were quite different from those which obtained during the first hundred years of American national experience. Baldly put, the economy's ascent to a position of twentieth century global industrial leadership entailed a transition from growth based upon the interdependent development and extensive exploitation of its natural resources and the substitution of tangible capital for labor, towards a the maintenance of an productivity leadership through rising rates of intangible investment in the formation and exploitation of technological and organizational knowledge. The study's scope is indicated by the following:
Quantitative Structure − Activity Relationship Models for Ready Biodegradability of Chemicals

The European REACH regulation requires information on ready biodegradation, which is a screening test to assess the biodegradability of chemicals. At the same time REACH encourages the use of alternatives to animal testing which includes predictions from quantitative structure− activity relationship (QSAR) models. The aim of this study was to build QSAR models to predict ready biodegradation of chemicals by using different modeling methods and types of molecular descriptors. Particular attention was given to data screening and validation procedures in order to build predictive models. Experimental values of 1055 chemicals were collected from the webpage of the National Institute of Technology and Evaluation of Japan (NITE): 837 and 218 molecules were used for calibration and testing purposes, respectively. In addition, models were further evaluated using an external validation set consisting of 670 molecules. Classification models were produced in order to discriminate biodegradable and nonbiodegradable chemicals by means of different mathematical methods: k nearest neighbors, partial least squares discriminant analysis, and support vector machines, as well as their consensus models. The proposed models and the derived consensus analysis demonstrated good classification performances with respect to already published QSAR models on biodegradation. Relationships between the molecular descriptors selected in each QSAR model and biodegradability were evaluated.
Pleiotrophin antagonizes Brd2 during neuronal differentiation

ABSTRACT Bromodomain-containing protein 2 (Brd2) is a BET family chromatin adaptor required for expression of cell-cycle-associated genes and therefore involved in cell cycle progression. Brd2 is expressed in proliferating neuronal progenitors, displays cell-cycle-stimulating activity and, when overexpressed, impairs neuronal differentiation. Paradoxically, Brd2 is also detected in differentiating neurons. To shed light on the role of Brd2 in the transition from cell proliferation to differentiation, we had previously looked for proteins that interacted with Brd2 upon induction of neuronal differentiation. Surprisingly, we identified the growth factor pleiotrophin (Ptn). Here, we show that Ptn antagonized the cell-cycle-stimulating activity associated with Brd2, thus enhancing induced neuronal differentiation. Moreover, Ptn knockdown reduced neuronal differentiation. We analyzed Ptn-mediated antagonism of Brd2 in a cell differentiation model and in two embryonic processes associated with the neural tube: spinal cord neurogenesis and neural crest migration. Finally, we investigated the mechanisms of Ptn-mediated antagonism and determined that Ptn destabilizes the association of Brd2 with chromatin. Thus, Ptn-mediated Brd2 antagonism emerges as a modulation system accounting for the balance between cell proliferation and differentiation in the vertebrate nervous system.
Inverse method for designing external cloak based on Laplace's equation

The external cloak is a special device that can make an object outside the cloaking shell invisible. In this paper, the inverse method based on numerical solution of Laplace's equation is applied to design arbitrary shape external cloak, without any knowledge of the coordinate transformation. The performance of the cloak is verified by full-wave simulation. The design method is extended to three dimensional case, which greatly enhances the applicability of external cloak.
The Impact of Racial Identity on the Educational Experiences of Multiracial, College Undergraduates

Title of thesis: “THE IMPACT OF RACIAL IDENTITY ON THE EDUCATIONAL EXPERIENCES OF MULTIRACIAL, COLLEGE UNDERGRADUATES” Corenne Harris, Master of Arts, 2015 Thesis directed by: Professor Tara Brown Teaching & Learning, Policy & Leadership While the impact of racial identity on students’ educational experiences has been studied for years, there has been little such research focused on multiracial individuals. The purpose of this study is to explore how racial identity has shaped the educational experiences of multiracial undergraduates, particularly in their transition to college. Transitioning into college, which often requires entering a very different social and educational environment, can be life changing for students, and racial identity can play a role in how students interact and identify with other students as well as teachers. An interview based qualitative methodology was used to explore the educational experiences of four multiracial undergraduate students. Individual face-to-face interviews were used to learn about the four participants’ experiences. Focusing on multiracial students, who are often left out of the discussion when talking about the impact racial identity has on various educational experiences, will contribute to research on the relationship between racial identity and education. Study findings showed that the participants experienced few, if any, negative effects on their educational experiences, due to their racial identity or how others perceived them, racially. Overall, participants felt that being multiracial was an advantage in terms of connecting with a diverse group of peers in school settings. “THE IMPACT OF RACIAL IDENTITY ON THE EDUCATIONAL EXPERIENCES OF MULTIRACIAL, COLLEGE UNDERGRADUATES”
Transition redshift: new kinematic constraints from supernovae

The transition redshift (deceleration/acceleration) is discussed by expanding the deceleration parameter to first order around its present value. A detailed study is carried out by considering two different parametrizations, q = q0 + q and q = q0 + q1 z(1 + z) -1 , and the associated free parameters (q0, q1 ) are constrained by three different supernovae (SNe) samples. A previous analysis by Riess et al. using the first expansion is slightly improved and confirmed in light of their recent data (Gold07 sample). However, by fitting the model with the Supernova Legacy Survey (SNLS) type Ia sample, we find that the best fit to the redshift transition is Zt = 0.61, instead of z t = 0.46 as derived by the High-z Supernovae Search (HZSNS) team. This result based in the SNLS sample is also in good agreement with the sample of Davis et al., z t = 0.60 +0.28 -0.11 (1σ). Such results are in line with some independent analyses and accommodate more easily the concordance flat model (ACDM). For both parametrizations, the three SNe Ia samples considered favour recent acceleration and past deceleration with a high degree of statistical confidence level. All the kinematic results presented here depend neither on the validity of general relativity nor on the matter-energy contents of the Universe.
A 42–71 GHz 90 nm CMOS injection-locked voltage-controlled oscillator using bulk injection technique

A wide locking range injection-locked voltage-controlled oscillator (ILVCO) using 90 nm CMOS process is presented in this paper. The ring-based triple-push topology with bulk injection is employed to extend locking range, and the oscillation condition is also easily maintained over tuning range. The measured overall locking range is from 42 to 71 GHz. The proposed ILVCO has locking ranges of 17%, 24.1%, and 24% as the free-running oscillation frequencies are 50, 60, 70 GHz, respectively. The total dc power consumption is from 31 to 44 mW with a supply voltage of 1.2 V. The chip size is 522×788 μm2. This work features wide locking range, good output power flatness, and spurs suppressions as compared previously reported millimeter-wave injection-locked oscillators.
Voice Coding with Opus

In this paper, we describe the voice mode of the Opus speech and audio codec. As only the decoder is standardized, the details in this paper will help anyone who wants to modify the encoder or gain a better understanding of the codec. We go through the main components that constitute the voice part of the codec, provide an overview, give insights, and discuss the design decisions made during the development. Tests have shown that Opus quality is comparable to or better than several state-of-the-art voice codecs, while covering a much broader application area than competing codecs.
Multifractal analysis of Power Markets. Some empirical evidence

This work is intended to offer a comparative analysis of the statistical properties of hourly prices in the day–ahead electricity markets of several countries. Starting from the intermittent nature of typical price fluctuations in many power markets, we will provide evidence that working into a stochastic multifractal analysis framework can be of help to asses typical features of day–ahead market prices.
A Study of the Variation in the Salivary Peptide Profiles of Young Healthy Adults Acquired Using MALDI-TOF MS

A cross-sectional observational study was conducted to evaluate the inter-individual variation in the MALDI-TOF MS peptide profiles of unstimulated whole saliva in a population of 268 systemically healthy adults aged 18–30 yr (150 males and 118 females) with no apparent caries lesions or periodontal disease. Using Spectral Clustering, four subgroups of individuals were identified within the study population. These subgroups were delimited by the pattern of variation in 9 peaks detected in the 2–15 kDa m/z range. An Unsupervised Feature Selection algorithm showed that P-C peptide, a 44 residue-long salivary acidic proline-rich protein, and three of its fragments (Fr. 1–25, Fr. 15–35 and Fr. 15–44) play a central role in delimiting the subgroups. Significant differences were found in the salivary biochemistry of the subgroups with regard to lysozyme and chitinase, two enzymes that are part of the salivary innate defense system (p < 0.001). These results suggest that MALDI-TOF MS salivary peptide profiles may relate information on the underlying state of the oral ecosystem and may provide a useful reference for salivary disease biomarker discovery studies.
Why people use health services.

Aims of the Paper The principal aims of this paper are (1) to increase professional health workers’ knowledge of selected research findings and theory so that they may better understand why and under what conditions people take action to prevent, detect and diagnose disease; and (2) to increase awareness among qualified behavioral scientists about the kinds of behavioral research opportunities and needs that exist in public health. A matter of personal philosophy of the author is that the goal of understanding and predicting behavior should appropriately precede the goal of attempting to persuade people to modify their health practices, even though behavior can sometimes be changed in a planned way without clear understanding of its original causes. Efforts to modify behavior will ultimately be more successful if they grow out of an understanding of causal processes. Accordingly, primary attention will here be given to an effort to understand why people behave as they do. Only then will brief consideration be given to problems of how to persuade people to use health services.
Is Theory Really Ahead of Measurement? Current Real Business Cycle Theories and Aggregate Labor Market Fluctuations

In the l93Os, Dunlop and Tarshis observed that the correlation between hours and wages is close to zero. This classic observation has become a litmus test by which macroeconomic models are judged. Existing real business cycle models fail this test dramatically. Based on this result, we argue that technology shocks cannot be the sole impulse driving post-war U.S. business cycles. We modify prototypical real business cycle models by allowing government spending shocks to influence labor market dynamics in a way suggested by Aschauer (1985), Barro (1981, 1987) and Kormendi (1983), This modification can, in principle, bring the models into closer conformity with the data. While the empirical performance of the models is significantly improved, they still fail to account for the Dunlop-Tarshis observation. Accounting for that observation will require further advances in model development. Consequently, we conclude that theory is behind, not ahead of, business cycle measurement.