Miracle-dz/UniFAR-FTUs huggingface dataset:
Locally linear support vector machines and other local models

The paper introduces various local models for solving machine learning (i.e., data mining) problems. In particular (and, due to their superior results) it focuses on a novel design of locally linear support vector machines classifiers. It presents them as powerful alternatives to the global (over the whole input space) nonlinear classifiers. Locally linear support vector machine (LL SVM) maximizes the margin in the original input features space and it never performs the nonlinear mapping to some kernel induced feature space. In performing such a task it uses only the K closest points to the query data point q. In this way it grasps the local decision function better than the standard global SVM does. This is shown to be a powerful approach when data are unevenly distributed in the input space and when a suitable decision function possesses different nonlinear characteristics in various parts of the input space. Experiments on eleven benchmark data sets display both the superior performance of LL SVMs as well as great performances of other classic locally linear classifiers. In addition, this is the first paper which proves the stability bounds for local SVMs and it shows that they are tighter than the ones for traditional, global, SVM. LL SVM is a natural classifier for multiclass problems which means that it can be easily adopted for solving regression tasks.
Notice of RetractionApplication of improved collocated cokriging

The collocated cokriging is such a method that can simulate primary parameter distribution integrating secondary parameter with high efficiency. However, the problem of variance inflation in sequential Gaussian simulation with collocated cokriging causes the input statistics not be reproduced. In this paper, an improved method is introduced. That is the secondary data is used not only at the location being estimated but also at all conditional data locations. An example in Zaoyuan well pattern of Qinshui Basin is presented. In this example, the porosity is primary parameter and ash content is as secondary parameter. The simulated results from traditional and improved methods are compared. The variance inflation observed in the models built by traditional method does not appear in the models constructed by improved method.
Abenomics and Asset Prices: Is It Case of Self-Fulfilling Expectations?

Asset prices have responded in a surprising way to the announcement of a policy package in late 2012 by Shinzo Abe, then the President of the LDP.The package (henceforth, Abenomics) has placed a central focus on aggressive monetary easing. The yen has weakened by about 20% against the dollar since then. Japanâ€™s stock market has gone up by about 30%. I offer a tentative evaluation of Abenomics in the light of the experience with non-conventional monetary policy (NCM) by major central banks including the Bank of Japan (BOJ).
Performance evaluation of filters in noise removal of fingerprint image

Biometric Identification and Authentication Systems are in need of a quality image in order to aim at a reliable and accuracy result. The quality of the fingerprint is obtained by the noise free images. To get a noise-free fingerprint image, they are applied under the pre-processing and filtering tasks. Especially the Fingerprint Recognition system is demanded by the accuracy factor. This paper made an attempt to evaluate the filtering techniques in the removal of noises such as Random Impulsive Noise, Gaussian Noise, Salt & Pepper Noise, Speckle Noise and Poisson Noise. In this paper, different filtering techniques such as Average Filtering (AF), Median Filtering (MF) and Adaptive Weiner Filtering (AWF) techniques were applied and compared the performance using a statistical approach called the correlation value. We related and compared the Noisy image with the each and every filtered image. We observed the experimental result to identify the better filtering technique.
An evaluation of the EFG growth model in its capacity to predict amino acid requirements in broilers

An experiment imposing the multi continuous phase feeding was carried out to evaluate the EFG(Emman, Fisher and Gous) Growth Model in its capacity to predict amino acid requirements in broilers.Birds were fed using blended summit (247.91g/kg CP, 3200 kcal of ME /kg) and dilution (166.26 g/kgCP, 3200 kcal of ME g/kg ) diets and offered to 2-4 or 8 phases. Two hundred male day-old broilerchicks of two commercial strains (A=Ingham and B = Steggles) were used. The predicted responseswere greater than the observed both gain (g/d) and feed intake (g/d). The discrepancy between theobserved and predicted gain in the strain A and B birds, showed a different pattern, with a markeddifference during the early growing period, with a degree of convergence in the late growing period forthe strain A but the reverse picture for the strain B. This shows that strain characterization is notaccurate due to an inadequate definition of the genotypes by the model. Non agreement betweenpredicted and determined gain and feed intakes provided little benefit in moving towards a morefrequent change in diet to accommodate predicted growth-related changes in amino acid requirements.
Forecast pipe defect size based on modified grey system and guided wave signal recognition with matching pursuit

This work aims to develop a method to predict the pipe defect size by modified grey system and guided wave signal recognition with matching pursuit (MP). Firstly, the evolutionary programming using mutations based on the t probability distribution (tEP) is applied to the matching pursuit method. Then, a steel pipe with a notch of different depth is tested by guided wave testing system and the measured signals are decomposed by MP with chirplet atoms and the amplitudes of defect echo are extracted. At last, the signals amplitudes are made to be the original sequence to predict the defect grow by modified grey system. The forecast error of the defect size is analyzed and the error ratio is restricted within 2%-5%. Therefore, this method can effectively estimate the defect size and the steel pipe defect can be quantitatively identified.
Basic Techniques for Creating an Efficient CSP Solver

Many computationally difficult problems from areas like planning and scheduling are easily modelled as constraint satisfaction problems (CSP). In order to have an uniform practical approach of these, a new programming paradigm emerged in the form of constraint programming, providing the opportunity of having declarative descriptions of CSP instances and also obtaining their solutions in reasonable computational time. This paper presents from both theoretical and practical points of view the design of a general purpose CSP solver. The solver we have created is called OmniCS (Omni Constraint Solver) and is freely available at http://omnics.sourceforge. net
The Relation of Perspective-Taking to Gratitude and Envy Among Guatemalan Adolescents

The social emotions gratitude and envy are central to the lives of Guatemalan youth and to their society more broadly. Perspective-taking, the social–cognitive process that allows one to assume another’s point of view, may affect both the experience and expression of gratitude and envy. In this convergent mixed-methods study, perspective-taking was studied in relation to gratitude and envy. Sixty-four Guatemalan adolescents, ages 12–17 (Mage = 13.52 years, SD = 3.66, 53.1% girls), completed scales measuring gratitude, envy, and perspective-taking. For the qualitative portion, they read one gratitude and one envy vignette and completed a series of open-ended questions about the story characters. Two multiple regression analyses revealed that better perspective-takers were more grateful and less envious. Thematic analysis of the open-ended responses uncovered seven levels of perspective-taking. Complex perspective-taking was revealed when adolescents inferred the perspective of both story characters, created positive social outcomes even in situations of envy, and inferred consequences of the interactions. These findings imply that promoting perspective-taking may be one way to decrease envy and promote gratitude in this majority world cultural context. The findings from this study may inform the creation of culturally sensitive social-emotional learning programs that promote well-being through positive interpersonal relationships.
How Might Marijuana Legalization in California Affect Drug Trafficking Revenues and Violence in Mexico

he United States’ demand for illicit drugs creates markets for Mexican drug trafficking organizations (DTOs) and helps foster violence in Mexico. Some government and media sources have reported that Mexican and Colombian DTOs combined earn $18–$39 billion annually in wholesale drug proceeds and 60 percent of all Mexican DTO drug export revenue comes from marijuana. These numbers have been cited to argue that legalizing marijuana in California would reduce Mexican DTOs’ revenues, thereby reducing violence. In a new study funded by RAND International Programs, RAND researchers assessed how marijuana legalization in California might influence DTO revenues and the violence in Mexico. Key study highlights include the following:
A High Slow-Wave Factor Microstrip Structure With Simple Design Formulas and Its Application to Microwave Circuit Design

This paper proposes a new microstrip slow-wave structure. The unit cell comprises a Schiffman section of meander line and a shunt open-circuited stub. No via-holes and ground-plane patterns are required. Simple design formulas can be used to obtain line parameters, such as the characteristic impedance and phase velocity. According to the analysis, the characteristic impedance and slow-wave factor of the proposed slow-wave line can be independently controlled by merely two layout parameters. The proposed uniplanar structure only requires a single-layer substrate and is simply constructed using the conventional printed circuit board manufacturing process. A branch-line and a rat-race coupler were designed and fabricated using the proposed structure to demonstrate its feasibility. Their sizes are only 8.49% and 4.87% of the conventional ones, respectively. This novel slow-wave structure should find wide applications in compact microwave circuits.
MR venography of multiple sclerosis.

BACKGROUND AND PURPOSE The distribution of multiple sclerosis (MS) lesions in the brain follows a specific pattern, with most lesions in the periventricular regions and in the deep white matter; histopathologic studies have shown a perivenous distribution. The aim of this study was to illustrate these distribution patterns in vivo using high-resolution MR venography. METHODS Seventeen MS patients underwent MR imaging at 1.5 T. Venographic studies were obtained with a 3D gradient-echo technique. MS lesions were identified on T2-weighted images, and their shape, orientation, and location were compared with the venous anatomy on the venograms. RESULTS The use of contrast material facilitated the visualization of small veins and increased the number of veins seen. A total of 95 MS lesions could be identified on both the T2-weighted series and the venograms; a central vein was visible in all 43 periventricular lesions and in all but one of the 52 focal deep white matter lesions. The typical ovoid shape and orientation of the long axis of the MS lesions correlated well with the course of these veins. CONCLUSION With MR venography, the perivenous distribution of MS lesions in the brain can be visualized in vivo. The venous anatomy defines the typical form and orientation of these lesions.
A quantitative Pólya's Theorem with corner zeros

Pólya's Theorem says that if <i>p</i> is a homogeneous polynomial in <i>n</i> variables which is positive on the standard <i>n</i>-simplex, and <i>F</i> is the sum of the variables, then for a sufficiently large exponent <i>N, F<sup>N</sup> * p</i> has positive coefficients. Pólya's Theorem has had many applications in both pure and applied mathematics; for example it provides a certificate for the positivity of <i>p</i> on the simplex. The authors have previously given an explicit bound on <i>N</i>, determined by the data of <i>p</i>; namely, the degree, the size of the coefficients and the minimum value of <i>p</i> on the simplex. In this paper, we extend this quantitative Pólya's Theorem to non-negative polynomials which are allowed to have simple zeros at the corners of the simplex.
Immunizing Computer Networks : Getting All the Machines in Your Network to Fight the Hacker Disease

This paper introduces a method of distributed network intru sion detection which scales with the number of computers on a network and is tunable (the probabil ity of detection can be traded off against overhead). Experiments with real network traffic show that t e system has high detection rates for several common routes of intrusion, and low false-positive rates un der normal behavior. The method can easily be extended to accommodate dynamically changing definition s of ormal behavior (for example, adding a host to the network) and to remember known patterns of intru sion.
Csiss – Specialist Meeting on Spatial Data Analysis Software Tools

" Estimates suggest that 80% of all digital data generated today include geospatial referencing. This enables integration of vast stores of diverse information. At the same time, the magnitude and complexity of data sets that can be brought together through their common geospatial links present an extraordinary challenge for information science – How do we transform these data into information and subsequently into knowledge? " MacEachren and Kraak (2001) 1. Requirements As data collection methods expand, data volumes multiply and the expectations of data users increase, graphics offer some promise for those aiming to generate information from data and knowledge from information. Graphical theory and principles exist for communicating information and generating knowledge from data sets of limited size, using representational methods of limited scope. New techniques that can be applied to our new data sets can draw upon some of this wisdom. But we need to develop methods that take advantage of the evolving computational possibilities and appropriate methodologies for evaluation of these burgeoning possibilities (see MacEachren & Kraak, 2001). The software tool developer plays a vital role in the advancement of our knowledge and implementation of novel techniques. Utilising technological advances to the advantage of the spatial sciences the tool developer is pivotal in liaising between the requirements of the spatial scientists, the developments of the computer scientists and the established theory of the cognitive scientists, cartographers and information visualizers. Tools may be 'operational prototypes', described by MacDougal (1992) as " a program that operates only when I use it ". Such software fulfils the communication objective. However, the development of robust demonstrators, that use appropriate new representational methods and means of interaction driven by requirement, opportunity and theory allows us to both communicate and evaluate the possibilities that arise. In the words of Unwin (1999) " until you have the tools available to you in a usable form you cannot be sure how effective they will be in practice ". The rapid development of demonstrator prototypes enables us to advance geovisualization by generating various representations and forms of interaction, undertaking evaluation in various user-centred scenarios and educating the community by disseminating evolving ideas about the use of graphics in research. This is particularly true when such software is flexible enough to permit development and extension. 2. Approaches The interface between human and computer is often uneasy, particularly as we try to undertake social science research by responsibly …
Dramatic Presence

Let us consider the presentation by computers of rich, highly interactive worlds that are inhabited by dynamic and complex characters, and shaped by aesthetically pleasing stories. We shall call this interactive drama, and we believe that it requires strong characters, aesthetic presentation, and long-term dramatic structure. This paper describes an experiment designed to help us understand how to create interactive drama. Three principal questions are addressed. One, how does it feel to be immersed in a dramatic virtual world filled with characters and story? Two, what is required of the characters (actors) in such a virtual world? Three, what is required of the story and its director? We present an introduction to interactive drama, summarize the Oz system designed to create and present such experiences, and describe our experiment in detail. Finally, drawing from the experiment, we suggest several hypotheses about interactive drama.
Bayesian analysis of constant elasticity of variance models: Research Articles

This paper focuses on the estimation of some models in finance and in particular, in interest rates. We analyse discretized versions of the constant elasticity of variance (CEV) models where the normal law showing up in the usual discretization of the diffusion part is replaced by a range of heavy-tailed distributions. A further extension of the model is to allow the elasticity of variance to be a parameter itself. This generalized model allows great flexibility in modelling and simplifies the model implementation considerably using the scale mixtures representation. The mixing parameters provide a means to identify possible outliers and protect inference by down-weighting the distorting effects of these outliers. For parameter estimation, Bayesian approach is adopted and implemented using the software WinBUGS (Bayesian inference using Gibbs sampler). Results from a real data analysis show that an exponential power distribution with a random shape parameter, which is highly leptokurtic compared with the normal distribution, forms the best CEV model for the data. Copyright © 2006 John Wiley & Sons, Ltd.
Estimating cognitive load during self-regulation of brain activity and neurofeedback with therapeutic brain-computer interfaces

Neurofeedback (NFB) training with brain-computer interfaces (BCIs) is currently being studied in a variety of neurological and neuropsychiatric conditions in an aim to reduce disorder-specific symptoms. For this purpose, a range of classification algorithms has been explored to identify different brain states. These neural states, e.g., self-regulated brain activity vs. rest, are separated by setting a threshold parameter. Measures such as the maximum classification accuracy (CA) have been introduced to evaluate the performance of these algorithms. Interestingly enough, precisely these measures are often used to estimate the subject’s ability to perform brain self-regulation. This is surprising, given that the goal of improving the tool that differentiates between brain states is different from the aim of optimizing NFB for the subject performing brain self-regulation. For the latter, knowledge about mental resources and work load is essential in order to adapt the difficulty of the intervention accordingly. In this context, we apply an analytical method and provide empirical data to determine the zone of proximal development (ZPD) as a measure of a subject’s cognitive resources and the instructional efficacy of NFB. This approach is based on a reconsideration of item-response theory (IRT) and cognitive load theory for instructional design, and combines them with the CA curve to provide a measure of BCI performance.
Survival and Cause of Death among a Cohort of Confirmed Amyotrophic Lateral Sclerosis Cases

Introduction Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder. Estimates of survival from disease onset range from 20 to 48 months and have been generated using clinical populations or death records alone. Methods Data on a cohort of ALS cases diagnosed between 2009–2011 were collected as part of the Los Angeles and San Francisco Bay Area Metropolitan ALS Surveillance projects; death records 2009–2013 were linked to these confirmed cases to determine survival post diagnosis and factors associated with survival time. Results There were 618 cases identified and 283 of these died during the follow up time period. Median age at death was 64.3 years, and median survival time post-diagnosis was 2.6 years. Age at diagnosis and year of diagnosis were predictors of survival time in adjusted models; those diagnosed at age 80 or older had shorter survival than those diagnosed at age 50 or younger. Most (92%) had ALS noted as a cause of death. Discussion Survival post-diagnosis may be improved compared with previous reports. Age at diagnosis continues to be the strongest predictor of prognosis; recall case reporting bias may play a role in estimates of survival time.
Cognitive beamforming with cooperative feedback

In cognitive radio networks based on spectrum sharing, cognitive beamforming (CB) enables the multi-antenna secondary user (SU) transmitter to suppress the interference to the primary user (PU) receiver and yet maximize the SU link throughput. In our prior work, a design framework was proposed for realizing CB based on finite-rate cooperative feedback from the PU receiver to the SU transmitter. The above cooperative feedback design is based on the orthogonal CB (OCB) algorithm. Specifically, the beamformer at the SU transmitter attempts to null the interference to the PU receiver by restricting the beamformer to be orthogonal to the SU-to-PU channel direction fed back by the PU receiver. In this paper, a new CB algorithm, called non-orthogonal CB (NOCB), is proposed by relaxing the orthogonality constraint for OCB. The NOCB algorithm computes the SU beamformer based on the feedback from the PU receiver including the quantized channel direction information (CDI) and interference power control (IPC) signal that is designed to regulate the SU transmission power. Furthermore, feedforward of the secondary-link CDI from the SU transmitter to the PU receiver is proposed, which enables more efficient IPC feedback design for the SU receiver and thereby allows larger SU transmission power. The proposed NOCB algorithms with cooperative PU feedback and SU feedforward are shown to substantially improve the SU link performance over the existing OCB designs.
Consolidation therapy of arsenic trioxide alternated with chemotherapy achieves remarkable efficacy in newly diagnosed acute promyelocytic leukemia

Background Currently, all-trans retinoic acid (ATRA) combined with daunorubicin and ATRA combined with arsenic trioxide (ATO) therapies are considered the standard induction therapy regimens for adult patients newly diagnosed with acute promyelocytic leukemia (APL). However, there is no consensus concerning the optimal consolidation and maintenance therapies after induction therapy. In this study, we explored a new therapeutic strategy for APL that may be simple, effective, and safe. Methods The patients in our study were divided into high white blood cell (WBC) group and low WBC group according to the numeration of leukocytes at the first visit. The low WBC group received ATRA and ATO until complete remission (CR), and the high WBC group received anthracycline, ATRA, and ATO until CR. After achieving hematologic CR, ATO was alternated with chemotherapy for consolidation therapy. Three cycles were completed in the 1st year with no maintenance therapy. The patients were followed for a median of 5 years after their initial treatment. Results After induction therapy, the rate of CR for the 18 patients was 100%. The rate of negativity for the PML/RARα fusion gene following induction therapy was 100%. There was no mortality during the treatment. Both the 5-year event-free survival rate and 5-year overall survival rate were 100%. No relapses occurred during the follow-up period. Conclusion This study proposes a novel treatment for APL that is efficient, well-tolerated, and very simple to perform.