Miracle-dz/UniFAR-FTUs huggingface dataset:
IMPROVED CONSTRAINTS ON PRIMORDIAL NON-GAUSSIANITY FOR THE WILKINSON MICROWAVE ANISOTROPY PROBE 5-YEAR DATA

We present constraints on the nonlinear coupling parameter fnl with the Wilkinson Microwave Anisotropy Probe (WMAP) data. We use an updated method based on the spherical Mexican hat wavelet (SMHW) which provides improved constraints on the fnl parameter. This paper is a continuation of a previous work by Curto et al., where several third-order statistics based on the SMHW were considered. In this paper, we use all the possible third-order statistics computed from the wavelet coefficient maps evaluated at 12 angular scales. The scales are logarithmically distributed from 6.9 arcmin to 500 arcmin. Our analysis indicates that fnl is constrained to −18 < fnl < +80 at 95% confidence level (CL) for the combined V+W WMAP map. This value has been corrected by the presence of undetected point sources, which adds a positive contribution of Δfnl = 6 ± 5. Our result excludes at ∼99% CL the best-fitting value fnl = 87 reported by Yadav & Wandelt. We have also constrained fnl for the Q, V, and W frequency bands separately, finding compatibility with zero at 95% CL for the Q and V bands but not for the W band. We have performed some further tests to understand the cause of this deviation which indicate that systematics associated with the W radiometers could be responsible for this result. Finally, we have performed a Galactic north–south analysis for fnl. We have not found any asymmetry, i.e., the best-fitting fnl for the northern pixels is compatible with the best-fitting fnl for the southern pixels.
Flag Manifolds and the Landweber – Novikov Algebra

We investigate geometrical interpretations of various structure maps associated with the Landweber–Novikov algebra S∗ and its integral dual S∗ . In particular, we study the coproduct and antipode in S∗ , together with the left and right actions of S∗ on S∗ which underly the construction of the quantum (or Drinfeld) double D(S∗). We set our realizations in the context of double complex cobordism, utilizing certain manifolds of bounded flags which generalize complex projective space and may be canonically expressed as toric varieties. We discuss their cell structure by analogy with the classical Schubert decomposition, and detail the implications for Poincaré duality with respect to double cobordism theory; these lead directly to our main results for the Landweber– Novikov algebra. AMS Classification numbers Primary: 57R77 Secondary: 14M15, 14M25, 55S25
Resource Allocation Optimization for OFDM-Based Amplify-And-Forward Multi-Relay System

A two-hop relaying system where a source communicates with its destination through multiple relay nodes is studied for capacity maximization. Amplify-and-forward (AF) relaying is adopted for its simplicity. Taking the independent channel transfer function of different subcarriers and links into consideration, we formulate a resource allocation optimization problem for joint subcarrier assignment, subcarrier matching and power allocation of the two-hop transmission. A heuristic suboptimal algorithm which decomposes the joint problem is proposed. First, equal power allocation is assumed in a partial-update manner to help assigning subcarriers to each relay for matching; then optimal power allocation is achieved by joint waterfilling of source and relays under separate power constraints to further increase system capacity. Numerical results show that the proposed algorithm has a near-optimal performance.
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes

Predicated on the increasing abundance of electronic health records, we investi- gate the problem of inferring individualized treatment effects using observational data. Stemming from the potential outcomes model, we propose a novel multi- task learning framework in which factual and counterfactual outcomes are mod- eled as the outputs of a function in a vector-valued reproducing kernel Hilbert space (vvRKHS). We develop a nonparametric Bayesian method for learning the treatment effects using a multi-task Gaussian process (GP) with a linear coregion- alization kernel as a prior over the vvRKHS. The Bayesian approach allows us to compute individualized measures of confidence in our estimates via pointwise credible intervals, which are crucial for realizing the full potential of precision medicine. The impact of selection bias is alleviated via a risk-based empirical Bayes method for adapting the multi-task GP prior, which jointly minimizes the empirical error in factual outcomes and the uncertainty in (unobserved) counter- factual outcomes. We conduct experiments on observational datasets for an inter- ventional social program applied to premature infants, and a left ventricular assist device applied to cardiac patients wait-listed for a heart transplant. In both experi- ments, we show that our method significantly outperforms the state-of-the-art.
Unifying data and control transformations for distributed shared-memory machines

We present a unified approach to locality optimization that employs both data and control transformations. Data transformations include changing the array layout in memory. Control transformations involve changing the execution order of programs. We have developed new techniques for compiler optimizations for distributed shared-memory machines, although the same techniques can be used for sequential machines with a memory hierarchy. Our compiler optimizations are based on an algebraic representation of data mappings and a new data locality model. We present a pure data transformation algorithm and an algorithm unifying data and control transformations. While there has been much work on control transformations, the opportunities for data transformations have been largely neglected. In fact, data transformations have the advantage of being applicable to programs that cannot be optimized with control transformations. The unified algorithm, which performs data and control transformations simultaneously, offers improvement over optimizations obtained by applying data and control transformations separately. The experimental results using a set of applications on a parallel machine show that the new optimizations improve performance significantly. These results are further analyzed using locality metrics with instrumentation and simulation.
Methods for Analyzing Diversity of Microbial Communities in Natural Environments

Difficulties in cultivating most of the microorganisms limit our ability to study microbial ecosystems. Molecular methods are valuable tools for investigating the diversity and structure of bacterial communities. These techniques can be used on culturable as well as non-culturable bacteria. Cultivation independent techniques based on nucleic acids extracted from the environment provide information on community structure and diversity. Analyses of DNA can determine the numbers of different genomes. Ribosomal RNA (rRNA) or rDNA (genes coding for rRNA) fingerprinting, probing and sequencing can be used to detect and identify organisms. The combination of different methods that complement each other is a useful strategy for monitoring changes of microbial communities in natural ecosystems. DOI: http://dx.doi. org/10.4038/cjsbs.v42i1. 5896 Ceylon Journal of Science ( Bio. Sci. ) 42 (1): 19-33, 2013
Surrounding Region Dependence Method For Detection Of Clustered Microcalcifications On Mammograms

Clustered microcalcifications on X-ray mammograms are an important feature in the detection of breast cancer. For the detection of the clustered microcalcification on digitized mammograms, this paper proposes a texture analysis method called the surrounding region dependence method (SRDM), which is a statistical texture analysis based on the second-order histogram in two surrounding regions. Four textural features are extracted from the SRDM. These features are used to classify region of interests (ROIs) into positive ROIs containing clustered microcalcifications and negative ROIs of normal breast tissues. The three-layer backpropagation neural network is employed as a classifier with input data of four textural features. The classification performance of the proposed method is evaluated by using the round-robin method and the receiver operating-characteristics (ROC) analysis.
340-440mW Broadband, High-Efficiency E-Band PA's in InP HBT

Two E-band (71-76GHz and 81-86GHz) solid-state power amplifiers in 250nm InP HBT are reported. The 71-76GHz PA demonstrates 13.3-16.2dB S21 gain and 33GHz bandwidth Pout from 71-81GHz is > 360mW. At 76GHz, 439mW Pout (26.4dBm) is achieved with 12.1dB gain and 26.9% PAE - this corresponds to 1.14W/mm power density. The 81- 86GHz PA demonstrates 12.0-14.3dB S21 gain and 40GHz bandwidth. Output power from 76-86GHz is > 337mW. At 86GHz, 358mW Pout (25.5dBm) is achieved with 10.2dB gain and 23.6% PAE - this corresponds to 0.93W/mm power density. This SSPA utilizes a novel, compact power cell topology developed for multi-finger HBTs, which overcomes the inability of the RF output interconnects and combiners to carry the high DC bias currents required by the InP HBT PA cells in the thin-film microstrip interconnect. This work improves upon the state- of-the-art for InP HBT and GaN HEMT E-Band SSPAs by demonstrating higher simultaneous power by 1.0- 2.0dB and large bandwidths, where PAE is > 15-20% in continuous wave (CW) operation. The size of the PA's is small, both only 1.95mm x 0.88mm.
A query verification scheme for dynamic outsourced databases

Recently, Kyriakos et al. proposed a Partially Materialized Digest scheme ( PMD ). Their scheme uses separate indexes for the data and the verification information to realize the authenticity and completeness verification in outsourced database. In this paper, we analyze PMD and show the drawbacks in PMD such as the slow update, the collusion and forgery attacks, and no content access control etc. In order to overcome these defects, the idea of designated verifier signature is introduced into query verification, and a secure, efficient query verification scheme for dynamic outsourced databases is proposed based on PMD . The analysis of security and performance shows that the proposed scheme has not only the same advantages with PMD , but also prevents the collusion and forgery attacks as well as enforces content access control. Furthermore, the update speed of the proposed scheme is faster than PMD , the storage cast of the proposed is lower than PMD .
Multilevel Darwinist Brain (MDB): Artificial Evolution in a Cognitive Architecture for Real Robots

The multilevel Darwinist brain (MDB) is a cognitive architecture that follows an evolutionary approach to provide autonomous robots with lifelong adaptation. It has been tested in real robot on-line learning scenarios obtaining successful results that reinforce the evolutionary principles that constitute the main original contribution of the MDB. This preliminary work has lead to a series of improvements in the computational implementation of the architecture so as to achieve realistic operation in real time, which was the biggest problem of the approach due to the high computational cost induced by the evolutionary algorithms that make up the MDB core. The current implementation of the architecture is able to provide an autonomous robot with real time learning capabilities and the capability for continuously adapting to changing circumstances in its world, both internal and external, with minimal intervention of the designer. This paper aims at providing an overview or the architecture and its operation and defining what is required in the path towards a real cognitive robot following a developmental strategy. The design, implementation and basic operation of the MDB cognitive architecture are presented through some successful real robot learning examples to illustrate the validity of this evolutionary approach.
Redistribution of the fibrinogen receptor of human platelets after surface activation

We investigated the whole cell distribution of the platelet membrane receptor for fibrinogen in surface-activated human platelets. Fibrinogen-labeled colloidal gold was used in conjunction with platelet whole mount preparations to visualize directly the fibrinogen receptor. Unstimulated platelets fail to bind fibrinogen, and binding was minimal in the stages of activation immediately following adhesion. The amount of fibrinogen bound per platelet increased rapidly during the shape changes associated with surface activation until 7,600 +/- 500 labels were present at saturation. Maximal binding of fibrinogen was followed by receptor redistribution. During the early stages of spreading, fibrinogen labels were uniformly distributed over the entire platelet surface, including pseudopodia, but the labels become progressively centralized as the spreading process continued. In well spread platelets, labels were found over the central regions, whereas peripheral areas were cleared of receptors. Receptor redistribution during spreading was accompanied by cytoskeletal reorganization such that a direct correlation was seen between the development of specific ultrastructural zones and the distribution of surface receptor sites suggesting a link between the surface receptors and the cytoskeleton. The association of fibrinogen receptors with contractile elements of the cytoskeleton, which permits coordinated receptor centralization, is important to the understanding of the role of fibrinogen in normal platelet aggregation and clot retraction.
A Corpus-Based Study of Accept and Assessment in SWBD-DAMSL

A series of studies have focused on backwards functions in conversation, especially to explore the distinction among backchannel/acknowledgement, accept and yes-answer, while for accept and assessment/appreciation, little attention has been obtained. This paper describes a quantitative investigation into two dialogue acts accept and assessment/appreciation, exhibiting their similarities and differences in the preceding contexts and lexical realization, which is expected to help the automatic detection of dialogue acts.
Distinct Propagation Characteristics of Intraseasonal Variability Over the Tropical West Pacific

Tropical intraseasonal variability, with the Madden‐Julian oscillation (MJO) as its most prominent mode, exerts extensive influences on global weather extremes. It is found that strong interannual variability of intraseasonal convection exists in the west Pacific (WP), in the form of years with strong eastward propagation (i.e., associated with the MJO) and years with strong westward propagation. Years with strong westward propagation on intraseasonal timescales are dominated by a westward propagating intraseasonal mode (WPIM), which is the second leading intraseasonal mode after the MJO over the tropical WP. Initiated over the central Pacific, the WPIM exhibits slow equatorial westward propagation (5 m/s) with a period of 25 days and a spatial scale of zonal wave number 3–4. Unlike the MJO, the WPIM lacks a significant tilt with height in specific humidity and vertical velocity. A strong anticorrelation is found between MJO and WPIM activity on interannual timescales over the WP. Budget analyses of the moist static energy suggest that both modes are driven by horizontal moist static energy advection and that substantial differences in winter mean large‐scale moisture and zonal winds largely define their distinct propagation behaviors. The WPIM is favored, while the MJO is suppressed when mean equatorial low‐level easterlies between 150°E and 160°W are enhanced and equatorial mean low‐level moisture is reduced near the Dateline and enhanced in the off‐equatorial WP (110°–150°E). While the WPIM bears resemblance to low‐frequency equatorial Rossby waves, a more detailed analysis must be conducted to affirm if they are the same phenomenon.
The Role of Emotion Regulation in the Relationship between Trait Anger and Relational Aggression

ii ACKNOWLEDGMENTS . iii LIST OF TABLES . vi CHAPTER I INTRODUCTION . 1 Trait Anger and Relational Aggression . 3 Emotion Regulation . 5 Emotion Regulation and Relational Aggression . 6 General Negative Affect . 7 The Present Study . 8 CHAPTER II – METHOD. 10 Participants . 10 Instruments . 10 Demographic Questionnaire . 10 Difficulties in Emotion Regulation Scale (DERS) . 10 Self-Report of Aggression and Social Behavior Measure (SRASBM) . 11 Buss-Perry Aggression Questionnaire . 12 Positive and Negative Affect Schedule (PANAS) . 12 Procedure . 13 CHAPTER III RESULTS . 14 v CHAPTER IV – DISCUSSION. 20 Trait Anger and Relational Aggression . 21 Emotion Regulation and Relational Aggression . 22 Limitations and Future Directions . 25 APPENDIX A – STUDY QUESTIONNAIRES . 27 Participant Demographic Questionnaire . 27 Difficulties in Emotion Regulation Scale . 27 Self-Report Measure of Aggression and Social Behavior Measure . 28 Buss-Perry Aggression Questionnaire . 30 The Positive and Negative Affect Schedule . 31 APPENDIX B – IRB CONSENT FORM . 32 REFERENCES . 35
Embodied Practitioner Knowledge: Reconfiguring the Boundary between Science and Meditation

ABSTRACT The scientific study of meditation is a new field of cross-disciplinary investigation that brings together neuroscientists, psychologists, and expert meditators. One might expect that in order to protect their scientific authority and objectivity, scientists who study meditation would try to distance themselves from meditation practitioners; however, a personal practice of meditation was not only accepted among scientists who study meditation, but it was also encouraged. Interviews with thirty scientists who study meditation revealed that this overlap could be explained by a new category of internal boundary practices that facilitated this collaboration: embodied practitioner knowledge. Whereas external boundary practices enable people on either sides of a boundary to work together, internal boundary practices are critical for understanding how individuals who occupy liminal spaces between disparate groups use their own bodies to support the crossing of boundaries. Scientists who both researched and practiced mediation reported that their meditation practice enabled them to translate between two domains that are epistemologically distinct, thus forging new pathways and areas of research. Moreover, meditation practice strengthens authoritative claims for objective knowledge. Embodied practitioner knowledge complements (and is supported by) other boundary practices such as standardized packages, boundary objects, and boundary organizations.
A Probabilistic Model of Referring Expressions for Complex Objects

This paper presents a probabilistic model both for generation and understanding of referring expressions. This model introduces the concept of parts of objects, modelling the necessity to deal with the characteristics of separate parts of an object in the referring process. This was ignored or implicit in previous literature. Integrating this concept into a probabilistic formulation, the model captures human characteristics of visual perception and some type of pragmatic implicature in referring expressions. Developing this kind of model is critical to deal with more complex domains in the future. As a first step in our research, we validate the model with the TUNA corpus to show that it includes conventional domain modeling as a subset.
Surpassing the theoretical 1-norm phase transition in compressive sensing by tuning the smoothed l0 algorithm

Reconstruction of an undersampled signal is at the root of compressive sensing: when is an algorithm capable of reconstructing the signal? what quality is achievable? and how much time does reconstruction require? We have considered the worst-case performance of the smoothed ℓ0 norm reconstruction algorithm in a noiseless setup. Through an empirical tuning of its parameters, we have improved the phase transition (capabilities) of the algorithm for fixed quality and required time. In this paper, we present simulation results that show a phase transition surpassing that of the theoretical ℓ1 approach: the proposed modified algorithm obtains 1-norm phase transition with greatly reduced required computation time.
Fingerprinting Internet DNS Amplification DDoS Activities

This work proposes a novel approach to infer and characterize Internet-scale DNS amplification DDoS attacks by leveraging the darknet space. Complementary to the pioneer work on inferring Distributed Denial of Service (DDoS) using darknet, this work shows that we can extract DDoS activities without relying on backscattered analysis. The aim of this work is to extract cyber security intelligence related to DNS Amplification DDoS activities such as detection period, attack duration, intensity, packet size, rate and geo- location in addition to various network-layer and flow-based insights. To achieve this task, the proposed approach exploits certain DDoS parameters to detect the attacks. We empirically evaluate the proposed approach using 720 GB of real darknet data collected from a /13 address space during a recent three months period. Our analysis reveals that the approach was successful in inferring significant DNS amplification DDoS activities including the recent prominent attack that targeted one of the largest anti-spam organizations. Moreover, the analysis disclosed the mechanism of such DNS amplification DDoS attacks. Further, the results uncover high-speed and stealthy attempts that were never previously documented. The case study of the largest DDoS attack in history lead to a better understanding of the nature and scale of this threat and can generate inferences that could contribute in detecting, preventing, assessing, mitigating and even attributing of DNS amplification DDoS activities.
Combined turbo equalization and turbo decoding

In this letter, the subject of turbo coding in the presence of an intersymbol interference channel is investigated. An iterative decoder structure is presented, which combines channel equalization and turbo decoding. At each iteration extrinsic information from the channel detector is fed into the turbo decoders, and then their extrinsic information is fed back to the channel detector. Simulation results are presented for a rate 1/2 turbo code with binary phase-shift keying (BPSK) modulation, transmitted over an intersymbol interference (ISI) channel having severe frequency distortion. The performance is about 0.8 dB from the ISI channel capacity at a bit-error rate of 10/sup -5/.
Symmetric Cardinality Constraint with Costs

The symmetric cardinality constraint is described in terms of a set of variables X = {x1, . , xk}, which take their values as subsets of V = {v1, . , vn}. It constraints the cardinality of the set assigned to each variable to be in an interval [lxi , uxi ] and at the same time it restricts the number of occurrences of each value vj ∈ V in the sets assigned to variables in X to be in an other interval [lvj , uvj ]. In this paper we extend the symmetric cardinality constraint with a function which associate with each value of each variable a cost and constraints the global cost of the constraint to the sum of costs associated with assigned values. We also give an algorithm for computing the consistency of a symmetric cardinality constraint with costs and describe filtering methods for this constraint.