Miracle-dz/UniFAR-FTUs huggingface dataset:
Edge preserving multiscale image decomposition with customized domain transform filters

In this paper, a multiscale image decomposition method based on domain transform is proposed. The domain transform is a high speed edge preserving smoothing method and can be used to many image processing applications. However, it is highly sensitive to noise. The proposed method is based on filters used in the domain transform but is designed to be robust to noise by employing a multiscale method. An optimization problem is formulated to obtain desired domain-transformed output. As expected, the method can be used to many applications as the domain transform. We implement edge preserving smoothing for noise-free/noisy images and detail enhancement as possible applications. The results are satisfactory even in the noisy environment.
The center manifold theorem for center eigenvalues with non-zero real parts

We define center manifold as usual as an invariant manifold, tangent to the invariant subspace of the linearization of the mapping defining a continuous dynamical system, but the center subspace that we consider is associated with eigenvalues with small but not necessarily zero} real parts. We prove existence and smoothness of such center manifold assuming that certain inequalities between the center eigenvalues and the rest of the spectrum hold. The theorem is valid for finite-dimensional systems, as well as for infinite-dimensional systems provided they satisfy an additional condition. We show that the condition holds for the Navier-Stokes equation subject to appropriate boundary conditions.
Justification and the four dimensions of power

Abstract This article is a dialogue with Forst on the role of justification in power relations, which is theory building in its own right. The article starts with Forst’s argument that power is a cognitive event that entails reason-giving. Developing this observation, the article explores how reasoning shifts across the four dimensions of power. How different types of power situations elicit different forms of justification in order to obtain compliance from the less powerful. This gives insight into the complex relationship that reason-giving has with structure, dominant ideology, reification, paradigms, discipline, domination and empowerment.
Examining User Acceptance of COPLINK Technologies by Law Enforcement Officers: A Survey Study

This study purports to develop and empirically examine a model for explaining technology acceptance decisions by individual law enforcement officers. Specifically, we describe the research model and hypotheses, detail our study design, and highlight important results from a pretest study that included 42 detectives and police officers from the Tucson Police Department (TPD). Based on the pretest results, our survey instrument exhibited satisfactory validity and reliability. A large-scale empirical examination of the proposed model is currently under way, targeting several hundred police officers and detectives at TPD. Results expected from this large-scale survey will contribute to technology acceptance/adoption research, particularly in law enforcement settings. In addition, findings anticipated from the study will also shed lights on the probable areas that hinder technology acceptance/use, thus providing a necessary foundation upon which effective implementation management strategies and organization intervention mechanisms can be developed to foster technology acceptance and use by individual law enforcement personnel.
A Time-Domain Subspace Technique for Estimating Visual Evoked Potential Latencies

Summary Estimating a visual evoked potential (VEP) from the human brain is challenging since its signal-to-noise ratio (SNR) is generally very low. An optimization and eigen-decompositionbased subspace approach has been investigated and tested to estimate the latencies of visual evoked potential (VEP) signals which are highly corrupted by spontaneous electroencephalogram (EEG) waveforms that can be considered as colored noise. This scheme termed as the generalized subspace approach (GSA) depends on the generalized eigendecomposition of the covariance matrices of the VEP and the colored EEG noise. The subspace algorithm jointly transforms these two correlation matrices into diagonal matrices, which can then be segregated into signal subspace and noise subspace. Enhancement is performed by removing the noise subspace and estimating the clean VEP signal from the remaining signal subspace. Further, GSA has been compared with a third-order correlation (TOC) method, using both realistic simulation and real patient data gathered in a hospital. The simulation results produced by the GSA algorithm show more faithful reproduction of VEP waveforms, and a higher degree of consistencies in detecting the P100, P200, and P300 peaks. Additionally, the results of the real patient data confirm the superiority of GSA over TOC in estimating VEP's P100 latencies, which are used by clinicians to assess the conduction of electrical signals from the subjects' retinas to the visual cortex parts of their brains.
Planktonic Microbial Communities Associated with Fracture-Derived Groundwater in a Deep Gold Mine of South Africa

The vertical distribution and function of terrestrial planktonic microbial communities at depths greater than 600 m remain poorly established. Culture-independent methods using 16S rRNA genes and geochemical approaches were employed to investigate the heterogeneity and potential function of microbial communities residing within fractures at 0.7 to 1.4 kilometers below land surface of Beatrix Au Mine, South Africa. The salinity (26 to 47 mM Cl−), temperature (33 to 40°C) and age (1 to 5 Ma) of these fracture water increased with depth. The δD and δ18O values of fracture water ranged from −44 to −39‰ and from −7 to −4‰ VSMOW, respectively, and exhibited a mixing trend with fracture water collected from the same mine in a previous study where isotopic signatures were indicative of hydrothermal origin. Fracture water from Beatrix Mine was distinct from the groundwater in the overlying Karoo sedimentary strata in terms of its Cl−, He and CH4 concentrations, and its δD and δ18O signatures and from Vaal River (source of service water) in terms of its δD and δ18O signatures. The differences constrain the maximum amount of mixing with service water or shallow groundwater to be less than 4%. The 16S rDNA analyses revealed diverse and numerous novel 16S rRNA genes affiliated with Proteobacteria, Firmicutes, Nitrospira, Chlorobi, Thermus, Candidate Division OP3 and Euryarchaeota. The proportion of each phylum in clone libraries varied markedly among samples and suggests km-scale, spatial heterogeneity in community structures. Potential metabolisms inferred from the presence of 16S rRNA genes are generally consistent with estimates of the available free energy.
Big Social Network Mining for "Following" Patterns

Many social networking sites such as Facebook and Twitter have been used for sharing knowledge and information among social entities. Social entities in these social networks are often linked by some interdependency such as friendship or "following" relationships. Amounts of high volumes of high-value data can be easily collected and generated in these social networking sites. As the size of the social network keeps increasing in the current era of big data, there are many real-life situations in which a social entity wants to find those frequently followed groups of social entities from these big data so that he can follow the same groups. In this paper, we present a big data mining algorithm to discover "following" patterns from these big social network data. Evaluation results show the efficiency and practicality of our algorithm in big social network mining for the "following" patterns.
Approximating the disambiguation of some German nominalizations by use of weak structural, lexical and corpus information

Between classical symbolic word sense disambiguation (wsd) using explicit deep semantic representations of sentences and texts and statistical wsd using word co-occurrence information, there is a recent tendency towards mediating methods. Similar to so-called light-weight semantics (Marek, 2009) we suggest to only make sparse use of semantic information. We describe an approximation model based upon flat underspecified discourse representation structures (FUDRSs, cf. Eberle, 2004) that weighs knowledge about context structure, lexical semantic restrictions and interpretation preferences. We give a catalogue of guidelines for human annotation of texts by corresponding indicators. Using this, the reliability of an analysis tool that implements the model can be tested with respect to annotation precision and disambiguation prediction and how both can be improved by bootstrapping the knowledge of the system using corpus information. For the balanced test corpus considered the recognition rate of the preferred reading is 80-90% (depending on the smoothing of parse errors).
Global Proteomics: Pharmacodynamic Decision Making via Geometric Interpretations of Proteomic Analyses

Disease and drugs can modulate the concentrations of hundreds of proteins in the blood which can be accurately measured using contemporary proteomic methods. Nevertheless, it is common practice to reduce the plurality of disease and drug effects by a few proteins for the pragmatic purposes of immunoassay development. The vast majority of putative biomarkers discovered by this reductionist approach never reach the clinic for two reasons: the prohibitive time and cost of assay development and the acute risk of a reduced protein panel failing when validated on a broader cross-section of the population. Global Proteomics is an alternate methodology where all blood proteins modulated by disease or drug are used to r esolve pharmacodynamic questions without the time, cost, and risk of developing an immunoassay . The Global Proteomic approach was applied to an Alzheimer study where it was demonstrated that a large panel of plasma proteins is pr edictive of disease severity (as measured by the Mini Mental State Examination). Furthermore, a subset of this panel was shown to be modulated by disease treatment (donepezil), thereby providing a means to quantify response to tr eatment. Finally, to establish that the Global Proteomics methodology has broad utility, it was also applied to a Hypertension study, illustrating that a panel of plasma proteins can also be derived that are corr elated with disease severity (as measured by blood pressure). In par ticular, the Global Proteomics methodology can readily distinguish patients responsive and non-responsive to hypertension therapies. The Global Proteomics approach is based upon a bioinformatics analysis approach which clusters samples by proteomic similarity and then uses a geometric representation of sample similarity to answer common pharmacodynamic questions.
Computing Assortative Mixing by Degree with the s-Metric in Networks Using Linear Programming

Calculation of assortative mixing by degree in networks indicates whether nodes with similar degree are connected to each other. In networks with scale-free distribution high values of assortative mixing by degree can be an indication of a hub-like core in networks. Degree correlation has generally been used to measure assortative mixing of a network. But it has been shown that degree correlation cannot always distinguish properly between different networks with nodes that have the same degrees. The so-called -metric has been shown to be a better choice to calculate assortative mixing. The -metric is normalized with respect to the class of networks without self-loops, multiple edges, and multiple components, while degree correlation is always normalized with respect to unrestricted networks, where self-loops, multiple edges, and multiple components are allowed. The challenge in computing the normalized -metric is in obtaining the minimum and maximum value within a specific class of networks. We show that this can be solved by using linear programming. We use Lagrangian relaxation and the subgradient algorithm to obtain a solution to the -metric problem. Several examples are given to illustrate the principles and some simulations indicate that the solutions are generally accurate.
A test bed for investigating self-x properties in multi-robot societies

In this paper, we introduce a test bed for demonstrating and investigating self-x properties, such as self-optimization and self-organization, within the scope of multi-robot societies under realistic conditions. By doing so, we shift the investigation and demonstration of biologically inspired mechanisms from the simulative point of view to a dynamic and more complex realistic environment. For this purpose, we developed a controlled real-world environment to overcome common problems such as self-localization. Furthermore, we elaborated a concept for a descriptive robotic real-world game. By means of this game, we provide an instrument, which is easily accessible for any kind of audience on the one hand, while it still leaves enough space for an extensive scientific investigation on the other hand.
Phox2a Gene, A6 Neurons, and Noradrenaline Are Essential for Development of Normal Respiratory Rhythm in Mice

Although respiration is vital to the survival of all mammals from the moment of birth, little is known about the genetic factors controlling the prenatal maturation of this physiological process. Here we investigated the role of the Phox2a gene that encodes for a homeodomain protein involved in the generation of noradrenergic A6 neurons in the maturation of the respiratory network. First, comparisons of the respiratory activity of fetuses delivered surgically from heterozygous Phox2a pregnant mice on gestational day 18 showed that the mutants had impaired in vivo ventilation, in vitro respiratory-like activity, and in vitro respiratory responses to central hypoxia and noradrenaline. Second, pharmacological studies on wild-type neonates showed that endogenous noradrenaline released from pontine A6 neurons potentiates rhythmic respiratory activity via α1 medullary adrenoceptors. Third, transynaptic tracing experiments in which rabies virus was injected into the diaphragm confirmed that A6 neurons were connected to the neonatal respiratory network. Fourth, blocking the α1 adrenoceptors in wild-type dams during late gestation with daily injections of the α1 adrenoceptor antagonist prazosin induced in vivo and in vitro neonatal respiratory deficits similar to those observed in Phox2a mutants. These results suggest that noradrenaline, A6 neurons, and the Phox2a gene, which is crucial for the generation of A6 neurons, are essential for development of normal respiratory rhythm in neonatal mice. Metabolic noradrenaline disorders occurring during gestation therefore may induce neonatal respiratory deficits, in agreement with the catecholamine anomalies reported in victims of sudden infant death syndrome.
A reliable cross layer routing scheme (CL-RS) for wireless sensor networks to prolong network lifetime

Design of conventional protocols for wireless sensor networks(WSN) are mainly based on energy management. The solutions for layered protocol of the WSN network are inefficient as sensors network mainly delivers real-time content thus, cross layer communication between layers of the protocol stack is highly required. In this paper, a reliable cross layer routing scheme (CL - RS) is proposed to balance energy to achieve prolonged lifetime through controlled utilization of limited energy. CL - RS considers 2 adjacent layers namely, MAC layer and network layer. Optimization issues are identified in these two layers and solutions are provided to reduce energy consumption thereby increasing network lifetime. To achieve higher energy efficiency MAC layer protocols compromise on packet latency. It is essential to attempt reduce the end-to-end delay and energy consumption using low duty cycle cross layer MAC (CL-MAC). The joint optimization design is formulated as a linear programming problem. The network is partitioned into four request zones to enable increase in network performance by using an appropriate duty cycle and routing scheme. We demonstrate by simulations that the strategy designed by combining (CL - RS) and (CL-MAC) algorithms at each layer significantly increases the network lifetime and a relation exists between the network lifetime maximization and the reliability constraint. We evaluate the performance of the proposed scheme under different scenarios using ns-2. Experimental results shows that proposed scheme outperforms the layered AODV in terms of packet loss ratio, end-to-end delay, control overhead and energy consumption.
Magnitude and time course of microvascular obstruction and tissue injury after acute myocardial infarction.

BACKGROUND Microvascular obstruction within an area of myocardial infarction indicates worse functional recovery and a higher risk of postinfarction complications. After prolonged coronary occlusion, contrast-enhanced MRI identifies myocardial infarction as a hyperenhanced region containing a hypoenhanced core. Because the time course of microvascular obstruction after infarction/reperfusion is unknown, we examined whether microvascular obstruction reaches its full extent shortly after reperfusion or shows significant progression over the following 2 days. METHODS AND RESULTS Seven dogs underwent 90-minute balloon occlusion of the left anterior descending coronary artery (LAD) followed by reflow. Gadolinium-DTPA-enhanced MRI performed at 2, 6, and 48 hours after reperfusion was compared with radioactive microsphere blood flow (MBF) measurements and myocardial staining to define microvascular obstruction (thioflavin S) and infarct size (triphenyltetrazolium chloride, TTC). The MRI hypoenhanced region increased 3-fold during 48 hours after reperfusion (3.2+/-1.8%, 6.7+/-4.4%, and 9.9+/-3.2% of left ventricular mass at 2, 6, and 48 hours, respectively, P<0.03) and correlated well with microvascular obstruction (MBF <50% of remote region, r=0.99 and thioflavin S, r=0.93). MRI hyperenhancement also increased (21.7+/-4.0%, 24.3+/-4.6%, and 28.8+/-5.1% at 2, 6, and 48 hours, P<0.006) and correlated well with infarct size by TTC (r=0.92). The microvascular obstruction/infarct size ratio increased from 13.0+/-4.8% to 22.6+/-8.9% and to 30.4+/-4.2% over 48 hours (P=0.024). CONCLUSION The extent of microvascular obstruction and the infarct size increase significantly over the first 48 hours after myocardial infarction. These results are consistent with progressive microvascular and myocardial injury well beyond coronary occlusion and reflow.
Creating an MTT treebank of Spanish

We present a cost effective strategy for the creation of a mid-size fine-grained dependency treebank of surface- and deep-syntactic structures as defined in the Meaning-Text Theory for Spanish. The strategy starts from a small seed dependency corpus, the AnCora corpus, whose annotation is considerably more coarse-grained than our target annotation. We show that this discrepancy can be bridged largely by automatic means, relying upon contextual information and leaving thus minimal work to the annotators. This allows us to develop the resources with limited human effort within a limited period of time. We also propose a preliminary evaluation of the actual amount of work that the annotation process requires.We present a cost effective strategy for the creation of a mid-size fine-grained dependency treebank of surface- and deep-syntactic structures as defined in the Meaning-Text Theory for Spanish. The strategy starts from a small seed dependency corpus, the AnCora corpus, whose annotation is considerably more coarse-grained than our target annotation. We show that this discrepancy can be bridged largely by automatic means, relying upon contextual information and leaving thus minimal work to the annotators. This allows us to develop the resources with limited human effort within a limited period of time. We also propose a preliminary evaluation of the actual amount of work that the annotation process requires.
MULTIPHASE MATERIALS WITH LIGNIN. VI. EFFECT OF CELLULOSE DERIVATIVE STRUCTURE ON BLEND MORPHOLOGY WITH LIGNIN

Polymeric blends of lignin with ethyl cellulose (EC) and cellulose acetate/butyrate (CAB) were prepared by solution casting from dioxane. Fracture surface analysis by scanning electron microscopy revealed phase separation when the lignin content exceeded 10% for blends with EC and 5% in the CAB system. While this phase behavior is as predicted for the EC blends, a greater level of compatibility had been expected for the CAB blend system. Results from both differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA) suggest that the observed phase separation may be a consequence of supermolecular structure development rather than immiscibility. In the case of the EC/lignin blends, the observed T g of lignin was 25 C and 35 C higher than that of the pure component for the 40 and 50 wt. % blend, respectively; and CAB/lignin blends produced conflicting results by DSC and DMTA. Where DSC revealed single T g 's for all blends with up to approximately 20% lignin, and dual transitions for all other compositions, DMTA data reflected single relaxations with variable T g 's throughout. This discrepancy is tentatively explained through the formation of liquid crystal mesophases in the cellulose derivative/lignin blends during solvent evaporation.
Self-esteem Among Young Bisexual Women in Norway: A 13-year Longitudinal Study

ABSTRACT The aim of this study was to investigate the relationships between self-esteem, perception of social acceptance and feeling of loneliness in a sample of young bisexual, lesbian and heterosexual women, including assessing self-esteem longitudinally across 13 years. The analyses were based on self-completed questionnaires from the longitudinal study “Young in Norway” (13 years follow-up, 1992-2005). N=1,598 female participants at baseline and follow-up (45 bisexual women, 21 lesbian women, 1,532 heterosexual women), age 25-32 years at follow-up. At baseline, there were no differences in self-esteem, but at follow-up bisexual women reported lower self-esteem, lower levels of perceived acceptance, and higher levels of loneliness. For bisexual women, self-esteem did not increase from adolescence to adulthood. At follow-up, loneliness had a stronger connection with self-esteem among bisexual women compared to lesbian and heterosexual women. Different mechanisms may be involved in the self-esteem among bisexual, lesbian, and heterosexual women.
A Challenge Problem for the Verification and Validation of Model Transformations

Using patterns originating from the world of object-oriented software development such as design patterns, architectural patterns, and refactoring idioms has considerably simplified the design process of software systems. With the proliferation of Domain-Specific Languages, the generalization of OO patterns is a natural demand. A straightforward idea is to adapt OO patterns with automated tool support to the practice of Domain-Specific Modeling as well. A possible solution for that is using graph transformations to formalize and realize such patterns. One may expect, however, that the patterns are realized such that they are correct and executed exactly as expected. Thus, the verification and validation of the transformations is required. In this paper, we present how one can precisely define the requirements for a model transformation, and how to verify the requirements on the implemented transformations by hand. Since there are no existing solutions at the moment to perform these operations automatically, we provide the presented examples as practical problems to be solved to researchers developing computer-aided verification and validation systems.