Miracle-dz/UniFAR-FTUs huggingface dataset:
An efficient approach for partial Fingerprint Recognition Based on Pores and SIFT Features using fusion methods

SYNOPSIS 1. INTRODUCTION Reliable authentication of people has long been an interesting goal and is becoming more important as the need of security grows. Security is an aspect that is given top priority by organizations, educational institutions, political and government in personal identity and forgery issues. Technologies called biometrics can automate the identification of people by one or more of their distinct physical or behavioral characteristics. They are pattern recognition system which makes personal identification by determining the authenticity of the specific characteristic possessed by the user. Biometrics has come to occupy an increasingly important role in human identification primarily to their universality and uniqueness (Cuntoor et al., 2003). As a result of this evolution, a new breed of techniques and methods for user identity recognition and verification has appeared based on the biometric features that are unique to each individual. Examples of common biometrics used include iris, DNA, voice patterns, facial patterns and fingerprint (Jain et al., 2004). Among these fingerprint is more popular biometric modality and has been used for personal identification for more than 100 years. The popularity is due to the fact that fingerprints never change and no two fingerprints are similar (Pankanti, et al., 2002). It has been proven that even identical twins have different fingerprints. Because of these desirable properties, automated systems for Automatic Fingerprint Recognition System (AFS) have been developed and over the years this interest has increased steadily. Several researchers have probed on using the intricacies of the fingerprint to create a robust and accurate AFS. The AFS combine image processing algorithms with fingerprint impression and map a fingerprint to an individual from a fingerprint database. Currently, there are three types of AFS, namely, minutiae-based, correlation-based, and image-based. In minutiae-based approaches, minutiae (i.e. endings and bifurcations of fingerprint ridges) are extracted and matched to measure the similarity between fingerprints. The correlation-based methods spatially correlate two fingerprint images to compute the similarity between them, while the image-based methods first generate a feature vector from each fingerprint image and then compute their similarity based on the feature vectors. 2 Although fingerprint matching based on minutiae features is a well researched problem in the field of AFS (Ratha and Bolle, 2004; Maltoni et al., 2003), it is still an unsolved problem presenting many research challenges. Most of the existing solution algorithms assume that the two templates are approximately of the same size. This assumption is …
Fast Image Segmentation Based on Single-Parametric Level-Set Approach

An improved level set framework for fast segmentation based on single parameter is presented. The traditional level set methods for image segmentation need inevitably too many parameters adjustment and they have usually lower computationally implementation. To solve this problem, the proposed method improves the C-V PDE model by adding a penalized energy term and replacing the dirac function with the norm of level set function gradient. Besides, only the parameter of the length term is reserved in the model and an evolution criterion is introduced for the value rules of this single parameter. The experimental results of synthesized and biomedical images show that the new method is faster and more robust. Moreover, the new method has more extensive adaptability on account of the zero level set function being set anyplace freely and the single parameter adjustment convenience.
Magnesium Ion-dependent Activation of the RecA Protein Involves the C Terminus*

Optimal conditions for RecA protein-mediated DNA strand exchange include 6–8 mm Mg2+ in excess of that required to form complexes with ATP. We provide evidence that the free magnesium ion is required to mediate a conformational change in the RecA protein C terminus that activates RecA-mediated DNA strand exchange. In particular, a “closed” (low Mg2+) conformation of a RecA nucleoprotein filament restricts DNA pairing by incoming duplex DNA, although single-stranded overhangs at the ends of a duplex allow limited DNA pairing to occur. The addition of excess Mg2+ results in an “open” conformation, which can promote efficient DNA pairing and strand exchange regardless of DNA end structure. The removal of 17 amino acid residues at theEscherichia coli RecA C terminus eliminates a measurable requirement for excess Mg2+ and permits efficient DNA pairing and exchange similar to that seen with the wild-type protein at high Mg2+ levels. Thus, the RecA C terminus imposes the need for the high magnesium ion concentrations requisite in RecA reactions in vitro. We propose that the C terminus acts as a regulatory switch, modulating the access of double-stranded DNA to the presynaptic filament and thereby inhibiting homologous DNA pairing and strand exchange at low magnesium ion concentrations.
Shape matching of digital curves

Estimation of difference between curves (curve matching) is a useful and often necessary technique in many applications, including: pattern recognition, image object recognition, robotic applications, computational geometry, etc. In this paper, three methods for curve matching using turning functions are presented. While the first two, called plain and polygonal method, are based on a simple adaptation of the existing approaches, the third one, called penalty method, is a new one and tries to overcome some important problems from the first two. The advantages and essential problems of the proposed methods are also discussed. A number of examples are presented to show major differences among the methods and their potential usefulness.
The Additional Information of Bitewing Radiographs in the Detection of Established or Severe Dentinal Decay in 14-Year Olds: A Cross-Sectional Study in Low-Caries Population

Aim. To reveal the additional value of radiographic bitewings (BW) in detection of caries and in comparing the occurrence of clinically undetected severe decay between 14-year olds with and without clinically observed dentinal caries in a low-caries prevalence population. Design. The cross-sectional study used 363 pairs of radiographs read by one examiner without knowledge of the clinical findings. The yield was analyzed on a tooth surface level by cross tabulating the clinical and radiographic information and on an individual level by counting the number of yield surfaces for all subjects. Mann-Whitney U test was used. Results. On a tooth surface level, the contribution of BW was the greatest on the occlusal surfaces of the first molars, where established or severe dentinal decay was registered in BW in 11% of clinically sound surfaces and in 40% of established cavitated enamel lesions. On an individual level, 53% of subjects benefited from BW. The subjects clinically DMFS > 0 benefited more than the clinically DMFS = 0 subjects (P = .004), nearly 60% in relation to 47%, respectively. Conclusions. In a low-caries prevalence population a remarkable portion of both clinically DMFS = 0 and DMFS > 0 14-year olds benefit from BW examination. Most of the benefit is obtained on the occlusal surfaces of the first and the second permanent molars.
Evaluating the Quality of Web-Mined Bilingual Sentences Using Multiple Linguistic Features

We raise the problem of evaluating the quality of bilingual sentences mined from the web, which is critical for such applications as statistical machine translation (SMT) and English as Second Language (ESL) learning. To tackle this problem, we propose a novel method that integrates multiple linguistic features related to spelling, grammar, and alignment, particularly the sentence type feature that indicates if a sentence can be parsed by the Link Grammar Parser (LGP). Promising results are achieved on a bilingual corpus of about 6 million English-Chinese sentences mined from the web, indicating the effectiveness of our proposed method.
Complex cepstrum analysis based on the minimum mean squared error

This paper introduces a novel approach for complex cepstrum analysis. Given initial estimates of complex cepstra and respective instants of glottal closure, the method iteratively optimizes the complex cepstrum and instants of glottal closure so that the mean squared error between natural and reconstructed speech waveforms is minimized. The proposed approach results in a more accurate speech representation based on the complex cepstrum, with no need of windowing or phase unwrapping. Experimental results show that the proposed method produces reconstructed speech with higher segmental signal-to-noise ratio scores when compared with conventional methods of complex cepstrum analysis. Because this approach can derive the complex cepstrum at fixed periods, it can be applied to statistical modeling in parametric speech synthesizers.
Robots as social mediators: coding for engineers

Coding can contribute to robot design by suggesting behavioral benchmarks. These, however, depend on the level of analysis. In illustration, semi-formalized rules are used to investigate child-robot encounters. By using behavior-level codes, we extract information about how children use the robot. This leads to findings about longitudinal changes in how children evaluate its behaviors. Children, we find, use the robot as a social mediator - to prompt synchronized social events. By focusing on a behavioral level, coding can benefit designers of robots, software and sensors
Three models for discriminative machine translation using Global Lexical Selection and Sentence Reconstruction

Machine translation of a source language sentence involves selecting appropriate target language words and ordering the selected words to form a well-formed target language sentence. Most of the previous work on statistical machine translation relies on (local) associations of target words/phrases with source words/phrases for lexical selection. In contrast, in this paper, we present a novel approach to lexical selection where the target words are associated with the entire source sentence (global) without the need for local associations. This technique is used by three models (Bag-of-words model, sequential model and hierarchical model) which predict the target language words given a source sentence and then order the words appropriately. We show that a hierarchical model performs best when compared to the other two models.
Visualisation and analysis of Mars data using ArcOBJECTS

Geographic Information Systems (GIS) are powerful tools for integration of different planetary datasets, e.g. images, spectral data and digital terrain models which are typically given in different formats like ASCII, vector and raster. We are currently involved in a project to import large volumes of data from the recent Mars missions into a planetary GIS database for joint analysis and interpretations.
Structural and Functional Neuroplasticity in Relation to Traumatic Stress

The body's stress response is an essential adaptive and protective mechanism to cope with threatening situations. However, chronic or traumatic stress leads to structural and functional alterations in the traumatized brain. We argue for a building-block effect: Exposure to different types of traumatic events increases the probability of developing posttraumatic stress disorder (PTSD), via incremental enlargement of a fear network. We summarize evidence of brain changes in PTSD, including recent results from research on animal models of stress-related neuroplastic remodeling, with an emphasis on structural and functional changes in the hippocampus, the amygdala, and the medial prefrontal cortex.
Immune Responses in Acute and Convalescent Patients with Mild, Moderate and Severe Disease during the 2009 Influenza Pandemic in Norway

Increased understanding of immune responses influencing clinical severity during pandemic influenza infection is important for improved treatment and vaccine development. In this study we recruited 46 adult patients during the 2009 influenza pandemic and characterized humoral and cellular immune responses. Those included were either acute hospitalized or convalescent patients with different disease severities (mild, moderate or severe). In general, protective antibody responses increased with enhanced disease severity. In the acute patients, we found higher levels of TNF-α single-producing CD4+T-cells in the severely ill as compared to patients with moderate disease. Stimulation of peripheral blood mononuclear cells (PBMC) from a subset of acute patients with peptide T-cell epitopes showed significantly lower frequencies of influenza specific CD8+ compared with CD4+ IFN-γ T-cells in acute patients. Both T-cell subsets were predominantly directed against the envelope antigens (HA and NA). However, in the convalescent patients we found high levels of both CD4+ and CD8+ T-cells directed against conserved core antigens (NP, PA, PB, and M). The results indicate that the antigen targets recognized by the T-cell subsets may vary according to the phase of infection. The apparent low levels of cross-reactive CD8+ T-cells recognizing internal antigens in acute hospitalized patients suggest an important role for this T-cell subset in protective immunity against influenza.
OF STABLE PROCESSES

The primary motivation for this study is a result of P61ya [8] which states that two points starting simultaneously in the plane and performing, independently, simple random walks will meet infinitely often with probability one. Dvoretzky and ErdSs [3] remark that three points starting simultaneously in the plane and performing independent simple random walks will not meet infinitely often; however, on the line they will meet with probability one. On the other hand, four points will not meet infinitely often even in R The purpose of this paper is to consider some similar questions about stable processes. First we ask for what values of a and N will two independent stable processes of index a in R meet? This question can be answered very easily because if X(t) and Y(t are the two processes and they start simultaneously, they will meet if and only if the process X(t) Y(t) returns to the origin. Since X(t) Y(t) is also a stable process of index a and a stable process of index a in R will return to the origin with positive probability (actually with probability one) if and only if a > 1 and N 1, this solves the problem of which values of a and N give rise to processes which will collide. It is also easy to verify that three independent stable processes can never have a simultaneous collision. The next problem is then to find the Hausdorff dimension of the intersection when a > 1 and N 1, i.e. the dimension of the set
T -duality transformation and universal structure of noncritical string field theory

We discuss a T-duality transformation for the c=1/2 matrix model for the purpose of studying duality transformations in a possible toy example of nonperturbative frameworks of string theory. Our approach is to first investigate the scaling limit of the Schwinger-Dyson equations and the stochastic Hamiltonian in terms of the dual variables and then compare the results with those using the original spin variables. It is shown that the c=1/2 model in the scaling limit is T-duality symmetric in the sphere approximation. In the case of the standard two-matrix model, however, the duality symmetry is violated when the higher-genus effects are taken into account, due to the nonsymmetrical appearence of global {bold Z}{sub 2} vector fields corresponding to nontrivial homology cycles. Some universal properties of the stochastic Hamiltonians which play an important role in discussing the scaling limit and have been discussed in a previous work by Sugino and Yoneya are refined in both the original and dual formulations. We also report a number of new explicit results for various amplitudes containing macroscopic loop operators. {copyright} {ital 1997} {ital The American Physical Society}
Synthesis of arbitrary-shaped lens antennas for beam-switching applications

Paper describes a successful attempt to design numerically a two-dimensional shaped beam-switching dielectric lens antenna (DLA) with improved angular (scanning) characteristics. Reduction of the directivity degradation for off-axis feeds is achieved thanks to joint optimization of the lens shape and feeding array parameters. Synthesis of the antenna is performed using highly-efficient in-house software based on the Muller Boundary Integral Equations (MBIE) solver and Hybrid Genetic Algorithm (HGA) optimization routine.
Adaptive dynamic surface control of nonlinear systems with perturbed uncertainties in strict-feedback form

Based on the approximation capability of radial basis neural networks and the integral-type Lyapunov function, adaptive dynamic surface control(DSC) is investigated for a class of strict-feedback nonlinear systems with unknown virtual control gain functions. The main advantages of the proposed scheme are that only one parameter is adjusted in the whole backstepping design by using Young's inequality and dynamic surface control, and the computational burden is effectively alleviated. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded, with arbitrary small tracking error by appropriately choosing design constants. Simulation results demonstrate the effectiveness of the proposed method.
Spectral Sensitivity of the Planarian Ocellus

The ocellar potential (OP) of planaria was recorded using microelectrode techniques. The action spectrum and spectral sensitivity of the OP are described. Maximum OP sensitivity was found with 508 nm light. A moderate increase in sensitivity to blue light was observed. This is typical of many invertebrate photoreceptors and was shown, by selective chromatic adaptation, not to indicate the presence of a second pigment.
Differences in the Pathogenicity and Inflammatory Responses Induced by Avian Influenza A/H7N9 Virus Infection in BALB/c and C57BL/6 Mouse Models

Avian influenza A/H7N9 virus infection causes pneumonia in humans with a high case fatality rate. However, virus-induced modulation of immune responses is being recognized increasingly as a factor in the pathogenesis of this disease. In this study, we compared the pathogenicity of A/H7N9 infection in BALB/c and C57BL/6 mouse models, and investigated the putative involvement of proinflammatory cytokines in lung injury and viral clearance. In both mouse strains, A/Anhui/1/2013(H7N9) infection with 106 TCID50 resulted in viral replication in lung, severe body weight loss and acute lung injury. During the early infection stage, infected C57BL/6 mice exhibited more severe lung injury, slower recovery from lung damage, less effective viral clearance, higher levels of interlukine (IL)-6, monocyte chemotactic protein (MCP)-1, and IL-1β, and lower levels of tumor necrosis factor (TNF)-α and interferon (IFN)-γ than infected BALB/c mice. These results suggest that TNF-α and IFN-γ may help suppress viral gene expression and increase viral clearance, and that IL-6 and MCP-1 may contribute to lung injury in A/H7N9-infected individuals. In addition, lung damage and the distribution of virus antigen in tissues were similar in young and middle-aged mice. These results suggest that the more serious lung injury in middle-aged or older H7N9 cases is not mainly caused by differences in viral replication in the lung but probably by a dysregulated immune response induced by underlying comorbidities. These results indicate that the extent of dysregulation of the host immune response after H7N9 virus infection most probably determines the outcome of H7N9 virus infection.
Circulating FGF21 Is Liver Derived and Enhances Glucose Uptake During Refeeding and Overfeeding

Fibroblast growth factor (FGF)21 is an endocrine hormone that is expressed in multiple tissues and functions physiologically to maintain energy homeostasis. FGF21 is being pursued as a therapeutic target for diabetes and obesity because of its rapid and potent effects on improving insulin sensitivity. However, whether FGF21 enhances insulin sensitivity under physiologic conditions remains unclear. Here, we show that liver-derived FGF21 enters the circulation during fasting but also remains present and functional during the early stage of refeeding. After a prolonged fast, FGF21 acts as an insulin sensitizer to overcome the peripheral insulin resistance induced by fasting, thereby maximizing glucose uptake. Likewise, FGF21 is produced from the liver during overfeeding and mitigates peripheral insulin resistance. DIO FGF21 liver-specific knockout, but not FGF21 adipose-specific knockout, mice have increased insulin resistance and decreased brown adipose tissue–mediated glucose disposal. These data are compatible with the concept that FGF21 functions physiologically as an insulin sensitizer under conditions of acute refeeding and overfeeding.
Activity‐dependent regulation of energy metabolism by astrocytes: An update

Astrocytes play a critical role in the regulation of brain metabolic responses to activity. One detailed mechanism proposed to describe the role of astrocytes in some of these responses has come to be known as the astrocyte‐neuron lactate shuttle hypothesis (ANLSH). Although controversial, the original concept of a coupling mechanism between neuronal activity and glucose utilization that involves an activation of aerobic glycolysis in astrocytes and lactate consumption by neurons provides a heuristically valid framework for experimental studies. In this context, it is necessary to provide a survey of recent developments and data pertaining to this model. Thus, here, we review very recent experimental evidence as well as theoretical arguments strongly supporting the original model and in some cases extending it. Aspects revisited include the existence of glutamate‐induced glycolysis in astrocytes in vitro, ex vivo, and in vivo, lactate as a preferential oxidative substrate for neurons, and the notion of net lactate transfer between astrocytes and neurons in vivo. Inclusion of a role for glycogen in the ANLSH is discussed in the light of a possible extension of the astrocyte‐neuron lactate shuttle (ANLS) concept rather than as a competing hypothesis. New perspectives offered by the application of this concept include a better understanding of the basis of signals used in functional brain imaging, a role for neuron‐glia metabolic interactions in glucose sensing and diabetes, as well as novel strategies to develop therapies against neurodegenerative diseases based upon improving astrocyte‐neuron coupled energetics. © 2007 Wiley‐Liss, Inc.
Scalar-tensor gravity in an accelerating universe

We consider scalar-tensor theories of gravity in an accelerating universe. The equations for the background evolution and the perturbations are given in full generality for any parametrization of the Lagrangian, and we stress that apparent singularities are sometimes artifacts of a pathological choice of variables. Adopting a phenomenological viewpoint, i.e., from the observations back to the theory, we show that the knowledge of the luminosity distance as a function of redshift up to z ~ (1-2), which is expected in the near future, severely constrains the viable subclasses of scalar-tensor theories. This is due to the requirement of positive energy for both the graviton and the scalar partner. Assuming a particular form for the Hubble diagram, consistent with present experimental data, we reconstruct the microscopic Lagrangian for various scalar-tensor models, and find that the most natural ones are obtained if the universe is (marginally) closed.