Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification of the liver disorders data using Multi-Layer adaptive Neuro-Fuzzy inference system

The meaning of classification is assigning data into subsets and clusters which are separated and independent. The data of any subsets have the most similarity to each other and the most difference from the other subsets. In this paper, the classification of the liver disorders data is done with using adaptive Neuro-Fuzzy inference system. In this study, the liver disorders data includes medical and physical information of 345 patients is used to show the Multi-Layer ANFIS performance in data classification and clustering. The dataset is selected from the UCI datasets which is a rich source of heart disease, primary tumor, hepatitis and liver disorders datasets.
hext, a software supporting tree‐based screens for hybrid taxa in multilocus data sets, and an evaluation of the homoplasy excess test

The homoplasy excess test (HET) is a tree‐based screen for hybrid taxa in multilocus nuclear phylogenies. Homoplasy between a hybrid taxon and the clades containing the parental taxa reduces bootstrap support in the tree. The HET is based on the expectation that excluding the hybrid taxon from the data set increases the bootstrap support for the parental clades, whereas excluding non‐hybrid taxa has little effect on statistical node support. To carry out a HET, bootstrap trees are calculated with taxon‐jackknife data sets, that is excluding one taxon (species, population) at a time. Excess increase in bootstrap support for certain nodes upon exclusion of a particular taxon indicates the hybrid (the excluded taxon) and its parents (the clades with increased support). We introduce a new software program, hext, which generates the taxon‐jackknife data sets, runs the bootstrap tree calculations, and identifies excess bootstrap increases as outlier values in boxplot graphs. hext is written in r language and accepts binary data (0/1; e.g. AFLP) as well as co‐dominant SNP and genotype data. We demonstrate the usefulness of hext in large SNP data sets containing putative hybrids and their parents. For instance, using published data of the genus Vitis (˜6,000 SNP loci), hext output supports V. × champinii as a hybrid between V. rupestris and V. mustangensis. With simulated SNP and AFLP data sets, excess increases in bootstrap support were not always connected with the hybrid taxon (false positives), whereas the expected bootstrap signal failed to appear on several occasions (false negatives). Potential causes for both types of spurious results are discussed. With both empirical and simulated data sets, the taxon‐jackknife output generated by hext provided additional signatures of hybrid taxa, including changes in tree topology across trees, consistent effects of exclusions of the hybrid and the parent taxa, and moderate (rather than excessive) increases in bootstrap support. hext significantly facilitates the taxon‐jackknife approach to hybrid taxon detection, even though the simple test for excess bootstrap increase may not reliably identify hybrid taxa in all applications.
Evidence for a Sudden Magnetic Field Reconfiguration in Soft Gamma Repeater 1900+14

We report the detection of large flux changes in the persistent X-ray flux of soft gamma repeater (SGR) 1900+14 during its burst active episode in 1998. Most notably, we find a factor of ~700 increase in the nonburst X-ray flux following the August 27 flare, which decayed in time as a power law. Our measurements indicate that the pulse fraction remains constant throughout this decay. This suggests a global flux enhancement as a consequence of the August 27 flare rather than localized heating. While the persistent flux has since recovered to the preoutburst level, the pulse profile has not. The pulse shape changed to a near sinusoidal profile within the tail of the August 27 flare (in γ-rays), and this effect has persisted for more than 1.5 years (in X-rays). The results presented here suggest that the magnetic field of the neutron star in SGR 1900+14 was significantly altered (perhaps globally) during the giant flare of August 27.
Hierarchical Latent Word Clustering

This paper presents a new Bayesian non-parametric model by extending the usage of Hierarchical Dirichlet Allocation to extract tree structured word clusters from text data. The inference algorithm of the model collects words in a cluster if they share similar distribution over documents. In our experiments, we observed meaningful hierarchical structures on NIPS corpus and radiology reports collected from public repositories.
Freestyle: A Rap Battle Bot that Learns to Improvise

We demonstrate a rap battle bot that autonomously learns to freestyle creatively in real time, via a fast new hybrid compositional improvisation model integrating symbolic transduction grammar induction with novel bilingual recursive neural networks. Given that rap and hip hop represent one of music’s most influential recent developments, surprisingly little research has been done in music technology. In true rap battling—the genre’s most difficult form— an appropriate output response must be improvised whenever challenged by some input line of lyrics. As with many musical improvisation tasks, modeling the creative process is complex because it requires compositionality: improvising a good response not only requires making salient associations with the challenge at many overlapping levels of granularity, but simultaneously satisfying contextual preferences across a wide variety of dimensions. Our new real-time system accomplishes this via an efficient, recursive, neurally guided stochastic grammar-based transducer. The neural network is a newly enhanced version of our recently developed TRAAM (transduction recursive auto-associative memory) model. We demonstrate strong connections between music and language processing and learning—the freestyle learning capability arises from exactly the same compositional structure learning model that autonomously learns semantic interpretation / translation models as well as other music improvisation models.
International Biosafety and Biosecurity Challenges: Suggestions for Developing Sustainable Capacity in Low-resource Countries

The increased global demand for improved disease detection and control has resulted in the expansion of diagnostic and research capacity. However, the increase in infectious disease detection capacity has not necessarily been paralleled by an increase in biosafety and biosecurity capacity, particularly in low-resource countries. Low-resource countries face numerous challenges that severely constrain the development, or expansion, of sustainable capacity in biosafety and biosecurity management. This article divides these challenges into nine broad categories: 1) Country-/Region-specific Regulatory Framework and Guidelines or Standards; 2) Biosafety Awareness; 3) Infrastructure; 4) Equipment, Reagents, and Services; 5) Management Processes and Administrative Controls; 6) Biosafety Curricula; 7) Training; 8) Biosafety Associations, Professional Competency, and Credentialing; and 9) Individual Mentoring and Organizational Twinning. Overcoming these challenges requires the collaborative efforts of representatives from the highest levels of local governments, the international biosafety community (e.g., international, regional, and national biosafety associations), and international development partners (e.g., national government agencies and programs, World Health Organization (WHO), World Bank, Food and Agriculture Organization of the United Nations (FAO), and the World Organization for Animal Health (OIE) to identify, fund, and execute solutions for sustainable capacity development. Collaboration is required to develop solutions appropriate for the specific needs and available resources within any given country.
Certification criteria for emulation technology in the australian defence force military avionics context

Emulatin technology promises to provide a means of addressing obsolescence issues in legacy computer processors in the military avionics domains. It has also been suggested that such technology might apply to safety critical and safety related systems in these domains. Numerous companies either have developed or are developing software components that are capable of emulating different legacy computing platforms. The emulators permit the execution of legacy code on newer computing platforms, without change to existing binary executables or data. Subsequent modifications to the legacy code in question may be made using either the legacy development environment and/or with some emulation technologies using a newer development environment. The Defence Science and Technology Organisation (DSTO) is presently working with Northrop Grumman Space Technology (NGST) to develop a concept demonstrator utilising NGST's Reconfigurable Processor for Legacy Applications Code Execution (RePLACE) Emulation Technology for the Royal Australian Navy (RAN) Seahawk Display Generator Unit (DGU). To assess how the Australian Defence Force's (ADF's) Technical Airworthiness Authority (TAA) - the Directorate General Technical Airworthiness (DGTA) might accept emulation technology, DGTA has evaluated emulation architectures and specifically RePLACE in the context of the Seahawk DGU. The evaluation has considered the emulation architecture, including identification of risks largely unique to the technology; as well as application of ADF preferred avionics software assurance and software safety standards to this technology. Evaluation of emulation technology, through exploration of emulation architectures and RePLACE as a case study, has allowed DGTA to define certification and regulatory guidance for the development of emulation technology within the ADF context.
Node localization using Particle Swarm Optimization

Recent advances in developing sensor nodes have made the use of Wireless Sensor Networks (WSNs) possible in many different scenarios, most of them require each node to have some information about its geographical location. This paper presents a two-step distance-based algorithm to sensor network localization carried out in a centralized architecture. The first phase of the algorithm utilizes an improved version of the DV-distance method used to provide coarse position estimates for all the nodes. During the second phase, Particle Swarm Optimization (PSO) is performed to fine tune and obtain accurate estimation of the locations. In the second phase, several techniques are also used to address the main problems of localization such as flip ambiguity, collective translation and error propagation. To evaluate the performance of the algorithm, numerical simulations were performed and the results were compared with similar distance-based methods, namely one-phase simulated annealing (SA), trilateration and simulated annealing (TSA) and semi-definite programming localization (SDP). Results demonstrate that our proposal achieves a significant performance improvement in comparison to other related methods especially in networks with low connectivity.
Key management for high bandwidth secure multicast

This paper brings up a new concern regarding efficient re-keying of large groups with dynamic membership: minimizing the overall time it takes for the key server and the group members to process the re-keying message. Specifically, we concentrate on re-keying algorithms based on the Logical Key Hierarchy (LKH), and minimize the longest sequence of encryptions and decryptions that need to be done in a re-keying operation. We first prove a lower bound on the time required to perform a re-keying operation in this model, then we provide an optimal schedule of re-keying messages matching the above lower bound. In particular, we show that the optimal schedule can be found only when the ariety of the LKH key graph is chosen according to the available communication bandwidth and the users processing power. Our results show that key trees of ariety 3, commonly assumed to be optimal, are not optimal when used in high bandwidth networks, or networks of devices with low computational power like sensor networks.
Optimal Sin Taxes

verse We investigate sin taxes on unhealthy items, such as fatty foods, that people may (by their own reckoning) consume too much of. We employ a standard optimal-taxation framework, but replace the standard assumption that all consumers have 100% self control with an assumption that some consumers may have some degree of self-control problems. We show that imposing taxes on unhealthy items and returning the proceeds to consumers can generally improve total social surplus. Because such taxes counteract over-consumption by consumers with self-control problems while at the same time they naturally redistribute income to consumers with no self-control problems (who consume less), such taxes can even create Pareto improvements. Finally, we demonstrate with some simple numerical examples that even if the population exhibits relatively few self-control problems, optimal taxes can still be large. Acknowledgments: We thank Robert Hall and Robert Barro for helpful discussions of a related shorter paper presented at the AEA meetings in January 2003. For helpful comments, we thank Jonathan Gruber and an anonymous referee, and also Steve Coate, Botond Koszegi, Emmanuel Saez, and seminar participants at Harvard, Yale, Stanford, Cornell, Vanderbilt, North Carolina State, the USC Behavioral Public Finance Conference, the 2003 Association of Public Economic Theory Conference at Duke, the 2004 ASSA meetings, and the Cornell-LSE-MIT Conference on Behavioral Public and Development Economics. For research assistance, we thank Christoph Vanberg and Chris Cotton. For financial support, we thank the National Science Foundation (grants SES-0214043 and SES-0214147), and Rabin thanks the Russell Sage and MacArthur Foundations. Mail: Ted ODonoghue / Department of Economics / Cornell University / 414 Uris Hall / Ithaca, NY 14853-7601. Matthew Rabin / Department of Economics / 549 Evans Hall #3880 / University of California, Berkeley / Berkeley, CA 94720-3880. E-mail: edo1@cornell.edu and rabin@econ.berkeley. edu. CB handles: Puck Boy and Game Boy. Web pages: http://www.people. cornell.edu/pages/edo1/ and http://emlab.berkeley. edu/users/rabin/. Never eat more than you can lift.   Miss Piggy
Efficient Stochastic Local Search for Modularity Maximization

In this paper, we analyze stochastic local searches and neighborhood strategies for the Modularity Maximization problem. Modularity Maximization was shown relevant in the identification of clusters in complex and social networks. Our experimental analysis shows that 1-neighborhood is a better strategy for the problem as it quickly locates suboptimal partitions. We find 99% near best-known partitions with 94% of frequency in time |V | 1.44 and 95% near best known Q values in sublinear time.
Determinants of Arsenic Metabolism: Blood Arsenic Metabolites, Plasma Folate, Cobalamin, and Homocysteine Concentrations in Maternal–Newborn Pairs

Background In Bangladesh, tens of millions of people have been consuming waterborne arsenic for decades. The extent to which As is transported to the fetus during pregnancy has not been well characterized. Objectives We therefore conducted a study of 101 pregnant women who gave birth in Matlab, Bangladesh. Methods Maternal and cord blood pairs were collected and concentrations of total As were analyzed for 101 pairs, and As metabolites for 30 pairs. Maternal urinary As metabolites and plasma folate, cobalamin, and homocysteine levels in maternal cord pairs were also measured. Household tube well–water As concentrations exceeded the World Health Organization guideline of 10 μg/L in 38% of the cases. Results We observed strong associations between maternal and cord blood concentrations of total As (r = 0.93, p < 0.0001). Maternal and cord blood arsenic metabolites (n = 30) were also strongly correlated: in dimethylarsinate (DMA) (r = 0.94, p < 0.0001), monomethylarsonate (r = 0.80, p < 0.0001), arsenite (As+3) (r = 0.80, p < 0.0001), and arsenate (As+5) (r = 0.89, p < 0.0001). Maternal homocysteine was a strong predictor of %DMA in maternal urine, maternal blood, and cord blood (β = −6.2, p < 0.02; β = −10.9, p < 0.04; and β = −13.7, p < 0.04, respectively). Maternal folate was inversely associated with maternal blood As5+ (β = 0.56, p < 0.05), and maternal cobalamin was inversely associated with cord blood As5+ (β = −1.2, p < 0.01). Conclusions We conclude that exposure to all metabolites of inorganic As occurs in the prenatal period.
A static analysis for quantifying information flow in a simple imperative language

We propose an approach to quantify interference in a simple imperative language that includes a looping construct. In this paper we focus on a particular case of this definition of interference: leakage of information from private variables to public ones via a Trojan Horse attack. We quantify leakage in terms of Shannon's information theory and we motivate our definition by proving a result relating this definition of leakage and the classical notion of programming language interference. The major contribution of the paper is a quantitative static analysis based on this definition for such a language. The analysis uses some non-trivial information theory results like Fano's inequality and the L 1 inequality to provide reasonable bounds for conditional statements. While-loops are handled by integrating a qualitative flow-sensitive dependency analysis into the quantitative analysis.
SUMOylation in Control of Accurate Chromosome Segregation during Mitosis

Posttranslational protein modification by small ubiquitin-related modifier (SUMO) has emerged as an important regulatory mechanism for chromosome segregation during mitosis. This review focuses on how SUMOylation regulates the centromere and kinetochore activities to achieve accurate chromosome segregation during mitosis. Kinetochores are assembled on the specialized chromatin domains called centromeres and serve as the sites for attaching spindle microtubule to segregate sister chromatids to daughter cells. Many proteins associated with mitotic centromeres and kinetochores have been recently found to be modified by SUMO. Although we are still at the early stage of elucidating how SUMOylation controls chromosome segregation during mitosis, a substantial progress has been achieved over the past decade. Furthermore, a major theme that has emerged from the recent studies of SUMOylation in mitosis is that both SUMO conjugation and deconjugation are critical for kinetochore assembly and disassembly. Lastly, we propose a model that SUMOylation coordinates multiple centromere and kinetochore activities to ensure accurate chromosome segregation.
Approximating Solution Probabilities in CSPs

Heuristics for variable and value ordering have proven useful in searching for solutions to constraint satisfaction problem (CSPs). A well-known heuristic guides the search by ordering values based on an estimate of the number of solutions for the problem. In this paper, we introduce a new estimation method that approximates the probability that a given variable/value combination is part of a global solution to a CSP. The method is a natural extension of a method introduced by Dechter and Pearl and we show that it performs better on average. We compare the new method with two existing methods on problems of varying degrees of hardness and show that the approximations for each method become considerably less accurate as problem difficulty increases and as a result the utility of each of the methods as value ordering heuristics decreases significantly.
Object detection based on BING in optical remote sensing images

High-resolution remote sensing images (RSIs) have been adopted in satellites, RSIs processing in satellites will enable new multimedia applications, such as situational awareness. In this paper, we have developed an object detection framework exploiting objectness measurement in which binarized normed gradient (BING) is used to detect some particular objects in RSIs more efficiently. Specifically, we (a) use BING to encode closed boundaries of objects and then obtain a group of candidate regions. The group can narrow down the search space of object detection, accelerating the traditional process of sliding window; and (b) employ a more robust feature descriptor. The feature is obtained by combining the pyramid of histograms of orientation gradients (PHOG) with Elliptic Fourier Transform so as to detect multiscale objects effectively; and (c) apply an SVM classifier to detect particular objects. Experiments show that the proposed framework has achieved an 85.1% average detection precision, 35.1% higher than the HOG-SVM using the same dataset.
Soliton solutions for the mean curvature flow

We consider soliton solutions of the mean curvature flow, i.e., solutions which move under the mean curvature flow by a group of isometries of the ambient manifold. Several examples of solitons on manifolds are discussed. Moreover we present a local existence result for rotating solitons. We also prove global existence and stability for perturbed initial data close to a local soliton.
A Fast Timing-Accurate MPSoC HW / SW Co-Simulation Platform based on a Novel Synchronization Scheme

Fast and accurate full-system simulation is needed for MPSoC design space exploration to achieve tight time-to-market design goals. In the field of full-system simulation, transaction level modeling with SystemC and traditional instruction set simulators (e.g. M5) based on C/C++ have their own advantages, separately. In this paper, a novel method for synchronizing M5 and SystemC modules is proposed to achieve fast and timing-accurate co-simulation. This method adopts event-driven scheduling and object-oriented programming technology. With this method, an MPSoC full-system co-simulation platform, which allows modeling the architecture at multiple levels of abstraction, is presented. The fast abstract model of M5 and timing-accurate model of SystemC has been used for hardware framework. On the other hand, a lightweight MPI library is implemented for communication of software applications. The simulation result shows that the novel scheme can obtain a fast simulation speed with no expense on simulation precision. Additionally a parallel MUSIC algorithm is designed which evaluates the validation of the MPSoC platform.
Control and learning of ambience by an intelligent building

Modern approaches to the architecture of living and working environments emphasize the dynamic reconfiguration of space and function to meet the needs, comfort, and preferences of its inhabitants. Although it is possible for a human operator to specify a configuration explicitly, the size, sophistication, and dynamic requirements of modern buildings demands that they have autonomous intelligence that could satisfy the needs of its inhabitants without human intervention. We describe a multiagent framework for such intelligent building control that is deployed in a commercial building equipped with sensors and effectors. Multiple agents control subparts of the environment using fuzzy rules that link sensors and effectors. The agents communicate with one another by asynchronous, interest-based messaging. They implement a novel unsupervised online real-time learning algorithm that constructs a fuzzy rule-base, derived from very sparse data in a nonstationary environment. We have developed methods for evaluating the performance of systems of this kind. Our results demonstrate that the framework and the learning algorithm significantly improve the performance of the building.