Miracle-dz/UniFAR-FTUs huggingface dataset:
Inverse amplitude method and chiral zeros

The inverse amplitude method has previously been successfully applied to $\pi\pi$ scattering in order to extend the range of applicability of chiral perturbation theory. However, in order to take the chiral zeros into account systematically, the previous derivation of the inverse amplitude method has to be modified. It is shown how this can be done to both one and two loops in the chiral expansion. In the physical region, the inclusion of these chiral zeros has very little significance, whereas they become essential in the sub-threshold region. Finally, the crossing properties of the inverse amplitude method are investigated in the sub-threshold region.
Simulation of the Explosion and the Interaction Effect between Smoke and Military Targets in the Battlefield

Simulation of explosive smoke generation and interaction between smoke and military targets in real time rendering of battlefield scene are studied. Numerical solution of Navier-Stokes equation of impressible gas is used to solve smoke field. Appropriate way of adding vortex particles is exploded to makes the smoke effect more realistic. Three dimensional Gaussian filter is used to density field of smoke in order to avoid scattered smoke flow. The reasonable parameters of the Gaussian filter are tried out for better smoke effect. The interaction effect between smoke and mobile military targets are simulated. Octree structure based voxelization is adopted to interactive computing for high computational efficiency. Proxy geometry is gained after a set of planes vertical to sight line intersecting with the edges of the smoke field cube. And then smoke and battlefield scene are synthesized. Research results of this paper can be applied to battlefield simulation and game scene rendering.
Theoretical Methods Dealing with Slow Dynamics

The traditional strategy for dealing with slow dynamics is summarized. Direct application of this strategy to supercooled liquids and glasses gives rise to problems. Two types of reduced description, namely, microcanonical and canonical versions of dynamical density functional theories, are explained. The non-equilibrium projector technique is used to develop this canonical reduced description. Some speculative proposals as regards how to deal with the barrier crossing regime are outlined.
In Search of How People Change: Applications to Addictive Behaviors

Abstract How people intentionally change addictive behaviors with and without treatment is not well understood by behavioral scientists. This article summarizes research on self‐initiated and professionally facilitated change of addictive behaviors using the key transtheoretical constructs of stages and processes of change. Modification of addictive behaviors involves progression through five stages—precontemplation, contemplation, preparation, action, and maintenance—and individuals typically recycle through these stages several times before termination of the addiction. Multiple studies provide strong support for these stages as well as for a finite and common set of change processes used to progress through the stages. Research to date supports a transtheoretical model of change that systematically integrates the stages with processes of change from diverse theories of psychotherapy.
Automatic frame reduction of Wireless Capsule Endoscopy video

Wireless Capsule Endoscopy (WCE) is a non-invasive colour imaging technique that has been introduced for the screening of the gastrointestinal tract and especially the small intestine. WCE is performed by a wireless swallowable endoscopic capsule that transmits more than 50,000 video frames per examination. The visual inspection of the resulting video is a highly time-consuming task even for the experienced gastroenterologist. In this paper we propose a novel WCE video summarization approach which is subsequently evaluated using real world patient data. The proposed approach aims to the reduction of the number of the video frames to be visually inspected so as to enable significant reduction in the video assessment time. It is based on clustering using symmetric non-negative matrix factorization initialized by the fuzzy c-means algorithm and supported by non-negative Lagrangian relaxation to extract a subset of video scenes containing the most representative frames from an entire examination. Real world patient data that display abnormal findings at several sites in the small intestine were annotated by expert gastroenterologists in order to experimentally evaluate the proposed approach. The results demonstrate that the suggested approach leads to significant reduction of the total number of frames in the input video without losing critical information related to the abnormal regions of the small intestine.
A Relationship: Word Alignment, Phrase Table, and Translation Quality

In the last years, researchers conducted several studies to evaluate the machine translation quality based on the relationship between word alignments and phrase table. However, existing methods usually employ ad-hoc heuristics without theoretical support. So far, there is no discussion from the aspect of providing a formula to describe the relationship among word alignments, phrase table, and machine translation performance. In this paper, on one hand, we focus on formulating such a relationship for estimating the size of extracted phrase pairs given one or more word alignment points. On the other hand, a corpus-motivated pruning technique is proposed to prune the default large phrase table. Experiment proves that the deduced formula is feasible, which not only can be used to predict the size of the phrase table, but also can be a valuable reference for investigating the relationship between the translation performance and phrase tables based on different links of word alignment. The corpus-motivated pruning results show that nearly 98% of phrases can be reduced without any significant loss in translation quality.
Design and Analysis of Capacitive MEMS Viscometric Sensor for CGM

This paper presents a study on the design and analysis of capacitively based Micro-Electro-Mechanical Systems (MEMS) sensor for continuous glucose monitoring (CGM) applications. This sensor consists of Parylene diaphragm, which is driven by a magnetic field and situated inside a micro chamber. A biocompatible sensing solution fills the micro chamber, which is separated from its surroundings by a semi permeable membrane. An electrolyte or bio molecule is permeating through the membrane and binds reversibly to the bio compatible sensing solution. This results in a viscosity change of the sensing solution and due to the applied magnetic field causing a detectable change in the Parylene diaphragm which can be measured capacitively. This kind of sensors can be used in continuous glucose monitoring. INTELLISUITE FEM software is used for modeling and simulating of MEMS capacitive Viscometric sensor to optimize design, improve the performance and reduce the time of fabricating process of the devices.
Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

We attempt to demonstrate the effectiveness of multiple points of view toward neural networks. By restricting ourselves to two points of view of a neuron, we propose a new type of information-theoretic method called “cooperation-controlled learning. ” In this method, individual and collective neurons are distinguished from one another, and we suppose that the characteristics of individual and collective neurons are different. To implement individual and collective neurons, we prepare two networks, namely, cooperative and uncooperative networks. The roles of these networks and the roles of individual and collective neurons are controlled by the cooperation parameter. As the parameter is increased, the role of cooperative networks becomes more important in learning, and the characteristics of collective neurons become more dominant. On the other hand, when the parameter is small, individual neurons play a more important role. We applied the method to the automobile and housing data from the machine learning database and examined whether explicit class boundaries could be obtained. Experimental results showed that cooperation-controlled learning, in particular taking into account information on input units, could be used to produce clearer class structure than conventional self-organizing maps.
Testing the Number of Components in Finite Mixture Models

This paper considers likelihood-based testing of the null hypothesis ofm0 components against the alternative of m0 + 1 components in a nite mixture model. The number of components is an important parameter in the applications of nite mixture models. Still, testing the number of components has been a long-standing challenging problem because of its non-regularity. We develop a framework that facilitates the analysis of the likelihood function of nite mixture models and derive the asymptotic distribution of the likelihood ratio test statistic for testing the null hypothesis of m0 components against the alternative of m0 + 1 components. Furthermore, building on this framework, we propose a likelihood-based testing procedure of the number of components. The proposed test, extending the EM approach of Li et al. (2009), does not use a penalty term and is implementable even when the likelihood ratio test is dicult to implement because of non-regularity and computational complexity.
Performance of Multi-antenna Array Assisted MC DS-CDMA Using Downlink Preprocessing Based on Singular Value Decomposition

In this contribution we propose and investigate a transmitter preprocessing scheme for downlink transmission in the multicarrier direct-sequence code-division multiple-access (MC DS-CDMA) systems using multiple base-station antenna arrays and each antenna array using multiple array elements. The transmitter preprocessing scheme is derived based on the singular value decomposition (SVD) approach. Our transmitter preprocessing design motives to support a high number of users by the MC DS-CDMA, to achieve the highest achievable diversity gain and to result in low-complexity detection for the remote mobilestations (MS’s). In this contribution the characteristics of the MC DSCDMA using the proposed transmitter preprocessing is discussed and the bit-error-rate (BER) performance is investigated, when assuming that each subcarrier experiences flat Rayleigh fading. Our study and simulation results show that, for a SVD-assisted MC DS-CDMA system using M transmit antenna arrays and the time (T)-domain spreading sequences of length Ne, the number of users supportable can be as high as MNe contributed by both the T-domain and S-domain. Furthermore, the SVD-assisted MC DS-CDMA system is capable of supporting such a high number of users with near single-user BER performance achieved by a corresponding MC DS-CDMA system supporting only one downlink user.
Recognition of corners of planar pattern image

The recognition of the internal corners of a planar checkerboard calibration pattern image is very important to camera calibration. An effective approach is proposed to automatically recognize the internal corners of the planar checkerboard calibration pattern image based on the characteristics of local intensity and the grid line architecture of the planar checkerboard pattern image. The proposed procedure consists of the detection of image corners, the recognition of the corners at the intersections of black and white squares and the recognition of the corners at the intersections of two groups of grid lines. Experiments show that the proposed approach obviously reduces the time cost for camera calibration, speeds up calibration process and is especially adapted for automatic calibration based on multiple images.
Book Selection Fuzzy Cluster Analysis: Methods for Classi®cation, Data Analysis and Image Recognition

The author of this book is one of the best known researchers in the ®eld of interior point algorithms for linear programming and other optimisation problems. This is attested to by the long list of references in his own name included in the bibliography, the bibliography was very up to date on publications and the book bene®ts from research results published in 1997. After a chapter of mathematical prerequisites and details of basic concepts, the reader, in Chapter 2, is led through the geometry of convex inequalities introducing many of the principles required for Karmarkar's projective interior point algorithm. This is just one interior point algorithm to be considered in the book, which also sets out to consider the path-following algorithm, the potential reduction algorithm, the primal-dual algorithm (including the predictor-corrector algorithm), and the af®ne scaling algorithm. For these algorithms, the computation of an approximate analytic centre of a polytope speci®ed by inequalities is at the heart of the approach. This subject forms the substance of Chapter 3 with the extension of the algorithms to solve LP problems being described in Chapter 4. As might be expected, the style of the book at this point is very mathematical and the book is not an easy read for the uninitiated. Chapters 5, 6 and 7 cover worst-case analysis, average-case analysis and asymptotic analysis, respectively. These are very abstract chapters and can only be appreciated after detailed study. Chapters 8 and 9 consider other convex and non-convex problems where interior point algorithms can be used. The ®nal chapter, on implementation issues, is one of the most interesting. Here the author starts to relate to practical effectiveness. Presolve and sparsity improvements are discussed ®rst and then numerical aspects of solving linear systems. Later sections consider a higher-order predictor-corrector method, the homogeneous and self-dual method and the optimal basis. After this chapter the reader may not be instantly able to write good interior point code, but will at least have been introduced to some of the major issues involved in the developments of such codes. Some mention of codes is made in the notes to this chapter, but this information gets out of date quickly, so there are omissions. This book is a specialised research book and unlikely to be of interest to the majority of readers of this journal. Although the ®nal chapter considers practical issues, it is perhaps disappointing that nowhere are …
Matching shapes with self-intersections:application to leaf classification

We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The curvature scale space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the curvature scale space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the curvature scale space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.
Semi-global regulation of output synchronization for heterogeneous networks of non-introspective, invertible agents subject to actuator saturation

In this paper, we consider the semi-global regulation of output synchronization problem for heterogeneous networks of invertible linear agents subject to actuator saturation. That is, we regulate the output of each agent according to an a priori specified reference model. The network communication infrastructure provides each agent with a linear combination of its own output relative to that of neighboring agents, and it allows the agents to exchange information about their own internal observer estimates, while some agents have access to their own outputs relative to the reference trajectory.
Do humans have conceptual models about geographic objects? A user study

In this article, we investigate what sorts of information humans request about geographical objects of the same type. For example, Edinburgh Castle and Bodiam Castle are two objects of the same type: “castle. ” The question is whether specific information is requested for the object type “castle” and how this information differs for objects of other types (e.g., church, museum, or lake). We aim to answer this question using an online survey. In the survey, we showed 184 participants 200 images pertaining to urban and rural objects and asked them to write questions for which they would like to know the answers when seeing those objects. Our analysis of the 6,169 questions collected in the survey shows that humans have shared ideas of what to ask about geographical objects. When the object types resemble each other (e.g., church and temple), the requested information is similar for the objects of these types. Otherwise, the information is specific to an object type. Our results may be very useful in guiding Natural Language Processing tasks involving automatic generation of templates for image descriptions and their assessment, as well as image indexing and organization.
Spiral inductor substrate loss modeling in silicon RF ICs

Spiral inductors constructed in silicon IC technologies possess limited quality factors due to series resistive losses, and losses within the semiconducting substrate. A new model for the less understood substrate losses illustrates how these losses can be minimized, providing quality factor increases of up to 230 percent over un-optimized designs.
Analyzing information sharing strategies of users in online social networks

User information sharing is an important behavior in online social networks. Understanding such behavior could help in various applications such as user modeling, information cascade analysis, viral marketing, etc. In this paper, we aim to understand the strategies users employ to make retweet decision. We are interested in investigating whether these strategies in online social network contain significant information about users and can be used to further characterize users. We propose a flexible model that captures a number of behavior signals affecting user's retweet decision. Our empirical results show that the inferred strategies can help increase the performance of retweet prediction.
Hypermethylation of the pl 6 INK 4 a Promoter in Colectomy Specimens of Patients with Long-standing and Extensive Ulcerative Colitis 1 ' 2

Functional inactivation of the />/r/%f"'' gene has been reported to be involved in the development of a variety of human malignancies. Recent evidence shows that transcriptional silencing as a consequence of hypermethylation of CpG islands is the predominant mechanism of pI6'^K4a gene inactivation in sporadic colon cancer. This study sought to identify the significance of pI6INK4" methylation in the colonie epithelium of patients with long-standing ulcerative colitis. A total of 89 tissue samples was retrieved from three colectomy specimens. A methylation-specific PCR assay was applied. The methylation status was compared with his tolÃ3gica) findings and the flow cytometrically determined DNA index. Hypermethylation of the pl6INK4a promoter region was detected in 12.7% of samples that were negative for dysplasia. However, 70.0% of samples with dysplasia and all of the samples with carcinomatous lesions revealed hypermethylation. Hypermethylation of the pÃ¬6lfiK4agene promoter was detected already in 40% of specimens with lesions indefinite for dysplasia and in 13.7% of samples with exclusively diploid cell populations. These results suggest that hypermethylation of thep/o'**'*1 promoter region is a frequent and early occurring event during the process of neoplastic pro gression in ulcerative colitis.
Development of a Selective Medium for the Fungal Pathogen Cylindrocarpon destructans Using Radicicol

The soil-borne ascomycete fungus Cylindrocarpon destructans causes ginseng root rot disease and produces various secondary metabolites such as brefeldin A and radicicol. The slow growth of this fungus compared with other plant pathogenic and saprophytic fungi in soil disturbs isolation of this fungus from soil and infected ginseng. In this study, we developed a selective medium for C. destructans using radicicol produced by this fungus. Supplementing 50 mg/L of radicicol to medium inhibited the mycelia growth of other fungi including Botrytis cinerea, Rhizoctonia solani and Alternaria panax, but did not affect the growth of C. destructans. In addition, conidia germination of other fungal species except for C. destructans was inhibited in submerged culture supplemented with radicicol. This medium provides a very efficient tool for isolating C. destructans and also can be used as an enrichment medium for this fungus.
FPGA Implementation of an LFSR based Pseudorandom Pattern Generator for MEMS Testing

strides in programmable logic density, speed and hardware description language (HDL) have empowered the engineer with the ability to implement high-performance digital functionality within field programmable gate array (FPGA). Linear feedback shift resister (LFSR) has become one of the central elements used in testing and self testing of contemporary complex electronic systems like processors, controllers and integrated circuits (ICs). This paper presents the FPGA implementation of an LFSR based pseudorandom pattern generator. This LFSR has the characteristics of high speed, low power consumption and it is especially suited in processing environment where uniform distribution random numbers are required. A typical application of the pattern generator considered in this work is the testing of micro- electro-mechanical-system (MEMS), where low power consumption is required. Very high speed integrated circuit HDL (VHDL) was used to implement the LFSR on FPGA. A testbench in VHDL was used to verify the correctness of the design. The compiled VHDL code was been synthesized into gate level. Area and timing optimization were done to achieve a very low gate count of 436 and increase the design speed to 178MHz Mentor Graphics and Xilinx ISE 6, electronic design automation (EDA) tool suite and DIGILENT D2SB PROTO BOARD were used for the overall FPGA implementation process.
View-based Consistency for Distributed Shared Memory

This paper proposes a novel View-based Consistency model for Distributed Shared Memory. A view is a set of data objects that a processor has the right to access in a data-race-free program. The View-based Consistency model requires that the data objects of a view are updated only before a processor accesses them. Compared with other memory consistency models, the View-based Consistency model can achieve data selection without user annotation and the performance advantage, though the supporting implementation techniques need to be further explored.