Miracle-dz/UniFAR-FTUs huggingface dataset:
On Statistical Methods in Natural Language Processing

What is a statistical method and how can it be used in natural language processing (NLP)? In this paper, we start from a definition of NLP as concerned with the design and implementation of effective natural language input and output components for computational systems. We distinguish three kinds of methods that are relevant to this enterprise: application methods, acquisition methods, and evaluation methods. Using examples from the current literature, we show that all three kinds of methods may be statistical in the sense that they involve the notion of probability or other concepts from statistical theory. Furthermore, we show that these statistical methods are often combined with traditional linguistic rules and representations. In view of these facts, we argue that the apparent dichotomy between “rule-based” and “statistical” methods is an over-simplification at best.
AKARI observations of circumstellar dust in the globular clusters NGC 104 and NGC 362

We report on preliminary results of AKARI observations of two globular clusters, NGC 104 and NGC 362. Imaging data covering areas of about 10×10 arcmin 2 centered on the two clusters were obtained with the Infrared Camera (IRC) at 2.4, 3.2, 4.1, 7.0, 9.0, 11.0, 15.0, 18.0, and 24.0 μm. We used IRC 11.0νm to 2MASS K s 2 μm flux-density ratio (F 11/F 2) and IRC 24.0 μm to 7.0 μm flux-density ratio (F 24/F 7) as diagnostics of circumstellar dust emission. Dust emissions are mainly detected from variable stars, obviously on the asymptotic giant branch, but some variable stars that reside below the tip of the first-ascending giant branch also show dust emissions. We found eight red sources with the F 24/F 7 ratio being greater than unity in NGC 362. Six out of the eight have no 2MASS counterparts. However, we found no such source in NGC 104. © 2007. Astronomical Society of Japan.
Imaging Dispersion of Myocardial Repolarization, II: Noninvasive Reconstruction of Epicardial Measures

Background—Dispersion of myocardial repolarization supports the development and maintenance of life-threatening arrhythmias. Current noninvasive approaches for detecting substrates with increased dispersion based on ECG measures (eg, QT dispersion) have shown limited success and inconsistencies. The companion article shows that, in contrast, epicardial potentials and derived measures reflect local dispersion of repolarization. Here, using a recently developed ECG imaging method, we evaluate the feasibility of noninvasive reconstruction of such epicardial measures from body-surface ECG data. Methods and Results—Epicardial potentials were recorded with a 224-electrode sock from an open-chest dog during control, regional warming, cooling, and simultaneous adjacent warming and cooling to induce localized changes in myocardial repolarization and regions of increased dispersion. Body-surface potentials were generated from these epicardial potentials in a human torso model. Realistic geometric errors and measurement noise were added to the torso data, which were then used to noninvasively reconstruct epicardial measures of repolarization dispersion (activation recovery intervals [ARIs] and QRST integrals). Repolarization properties were accurately depicted by ECG imaging, including (1) shortened ARIs and increased QRST integrals over the warmed region, (2) prolonged ARIs and decreased QRST integrals over the cooled region, and (3) high gradients of ARIs and QRST integrals over the adjacent warmed and cooled regions. Conclusions—ECG imaging can reconstruct repolarization properties accurately and localize areas of increased dispersion of repolarization in the heart noninvasively. Its clinical significance lies in the possibility of noninvasive risk stratification and in guidance and evaluation of therapy.
A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast

The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME) modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS) approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient response of Mig1 tend to be faster, more extended, and displays an increased cell-to-cell variability.
Design and Control of a 3 D Biped Robot Actuated by Antagonistic Pairs of Pneumatic Muscles

A joint driving mechanism with antagonistic pairs of muscles is supposed to be essential for humans and animals to realize various kinds of locomotion such as walking, running, and jumping. This paper describes design and control of a biped robot “Pneu–Man” whose joints are driven by antagonistic pairs of McKibben artificial muscles. Since the body is welldesigned for walking, required control is surprisingly compact. The experimental results demonstrate the walking performance of Pneu–Man.
Photodynamic therapy with aminolevulinic acid topical solution and visible blue light in the treatment of multiple actinic keratoses of the face and scalp: investigator-blinded, phase 3, multicenter trials.

OBJECTIVE To determine the safety and efficacy of photodynamic therapy (PDT) using 20% wt/vol aminolevulinic acid hydrochloride (hereinafter "ALA") and visible blue light for the treatment of multiple actinic keratoses of the face and scalp. DESIGN Randomized, placebo-controlled, uneven parallel-group study. INTERVENTIONS Patients (N = 243) were randomized to receive vehicle or ALA followed within 14 to 18 hours by PDT. Follow-up visits occurred 24 hours and 1, 4, 8, and 12 weeks following PDT. Target lesions remaining at week 8 were re-treated. MAIN OUTCOME MEASURE Clinical response based on lesion clearing by week 8. RESULTS Most patients in both groups had 4 to 7 lesions. Complete response rates for patients with 75% or more of the treated lesions clearing at weeks 8 and 12 were 77% (128/166) and 89% (133/149), respectively, for the drug group and 18% (10/55) and 13% (7/52), respectively, for the vehicle group (P<.001, Cochran-Mantel-Haenszel general association test). The 95% confidence interval for the difference in response rates at week 8 was 46.9% to 71.0% and at week 12, 65.3% to 86.3%. The week 12 response rate includes 30% of patients who received a second treatment. Most patients experienced erythema and edema at the treated sites, which resolved or improved within 1 to 4 weeks after therapy, and stinging or burning during light treatment, which decreased or resolved by 24 hours after light treatment. CONCLUSION Findings indicate that topical ALA PDT is an effective and safe treatment for multiple actinic keratoses of the face and scalp.
Climate controls on vegetation phenological patterns in northern mid‐ and high latitudes inferred from MODIS data

Recent studies using both field measurements and satellite‐derived‐vegetation indices have demonstrated that global warming is influencing vegetation growth and phenology. To accurately predict the future response of vegetation to climate variation, a thorough understanding of vegetation phenological cycles and their relationship to temperature and precipitation is required. In this paper, vegetation phenological transition dates identified using data from the moderate‐resolution imaging spectroradiometer (MODIS) in 2001 are linked with MODIS land surface temperature (LST) data from the northern hemisphere between 35°N and 70°N. The results show well‐defined patterns dependent on latitude, in which vegetation greenup gradually migrates northward starting in March, and dormancy spreads southward from late September. Among natural vegetation land‐cover types, the growing‐season length for forests is strongly correlated with variation in mean annual LST. For urban areas, the onset of greenup is 4–9 days earlier on average, and the onset of dormancy is about 2–16 days later, relative to adjacent natural vegetation. This difference (especially for urban vs. forests) is apparently related to urban heat island effects that result in both the average spring temperature and the mean annual temperature in urban areas being about 1–3°C higher relative to rural areas. The results also indicate that urban heat island effects on vegetation phenology are stronger in North America than in Europe and Asia. Finally, the onset of forest greenup at continental scales can be effectively described using a thermal time‐chilling model, which can be used to infer the delay or advance of greenup onset in relation to climatic warming at global scale.
Optimizing and Learning Diffusion Behaviors in Complex Network

Many dynamic phenomena can be modeled as a diffusion process. For my dissertation, I study diffusion processes in the area of sustainability, such as how wildlife spreads over a fragmental landscape and how fish spread within a river network, and try to answer two important questions. 1) How to shape the diffusion by using a limited amount of resources, for example how to maximize the spread of birds by preserving a limited number of landscape units? 2) How to model the diffusion process and estimate the parameters of the model using incomplete and noisy observations? This document describes my current research progress and future research directions of answering these two important questions.
Domestication, Genomics and the Future for Banana

Background Cultivated bananas and plantains are giant herbaceous plants within the genus Musa. They are both sterile and parthenocarpic so the fruit develops without seed. The cultivated hybrids and species are mostly triploid (2n = 3x = 33; a few are diploid or tetraploid), and most have been propagated from mutants found in the wild. With a production of 100 million tons annually, banana is a staple food across the Asian, African and American tropics, with the 15 % that is exported being important to many economies. Scope There are well over a thousand domesticated Musa cultivars and their genetic diversity is high, indicating multiple origins from different wild hybrids between two principle ancestral species. However, the difficulty of genetics and sterility of the crop has meant that the development of new varieties through hybridization, mutation or transformation was not very successful in the 20th century. Knowledge of structural and functional genomics and genes, reproductive physiology, cytogenetics, and comparative genomics with rice, Arabidopsis and other model species has increased our understanding of Musa and its diversity enormously. Conclusions There are major challenges to banana production from virulent diseases, abiotic stresses and new demands for sustainability, quality, transport and yield. Within the genepool of cultivars and wild species there are genetic resistances to many stresses. Genomic approaches are now rapidly advancing in Musa and have the prospect of helping enable banana to maintain and increase its importance as a staple food and cash crop through integration of genetical, evolutionary and structural data, allowing targeted breeding, transformation and efficient use of Musa biodiversity in the future.
Mean-Variance Portfolio Selection with Reference Dependent Preferences

We study S-shaped utility maximization for the standard portfolio selection problem with one risky and one risk-free asset. We derive a mean-variance criterium of choice, which preserves reference dependence and the reflection effect. Subsequently, we study diversification possibilities and obtain the demand for the risky asset. We close the paper with an alternative interpretation of the criterium in terms of target-based decision making.
Analysis of a dynamic voting algorithm based on regeneration with virtual copies

A consistency control algorithm for replicated data objects in distributed computing systems, called RVC2, has been extensively analyzed. RVC2 is a voting-based algorithm which utilizes a selective regeneration and recovery mechanism for failed copies of data objects. Virtual copies, which record information about the current state of a copy, but which contain no actual data, are used in addition to real copies to reduce network and storage overhead. Empirical results concerning availability, obtained through simulation, are presented. These results show that varying the number of real versus virtual copies, and varying the generation threshold, has no significant impact on availability. The results also suggest that RVC2 is an unnecessarily complex algorithm because regeneration has no significant impact on availability under most circumstances.
A conditional access system with efficient key distribution and revocation for mobile pay-TV systems

Current mobile pay-TV systems have two types of Conditional Access Systems (CAS): group-key-based and public-key systems. The best feature of group-key-based systems is the ability to enjoy the broadcast nature in delivery multimedia contents, while the major advantage of public-key systems is consolidating the security foundation to withstand various attacks, such as collusion attacks. However, the problems of group-key-based systems include collusion attacks, lack of nonrepudiation, and troublesome key distribution. Even worse, the benefit of broadcast efficiency is confined to a group size of no more than 512 subscribers. For public-key systems, the poor delivery scalability is the major shortcoming because the unique private key feature is only suitable for one-to-one delivery. In this article, we introduce a scalable access control scheme to integrate the merits of broadcasting regardless of group size and sound security assurance, including fine-grained access control and collusion attack resistance. For subscriber revocation, a single message is broadcast to the other subscribers to get the updated key, thus significantly boosting subscriber revocation scalability. Due to mobile subscribers' dynamic movements, this article also analyzes the benefit of retransmission cases in our system. Through the performance evaluation and functionality comparison, the proposed scheme should be a decent candidate to enhance the security strength and transmission efficiency in a mobile pay-TV system.
Learning Saliency. An ICA based model using Bernoulli mixtures

In this work, we present a model of both the visual input selection and the gaze orienting behaviour of a human observer undertaking a visual exploration task in a specific scenario. Our input is made of a sequence of gaze-tracked fixations acquired from a custom designed wearable device. We aim at characterising the statistical properties and regularities of the selected visual input. While the structure of the visual context is specified as a linear combination of basis functions, which are independent hence uncorrelated, we show how low level features characterising a scan-path of fixations can be obtained by hidden correlations to the context. Samples from human observers are collected both in free-viewing tasks, in the specified visual scene. These scan-paths show important and interesting dependency from the context. We show that a scan-path, given a database of a visual context, can be suitably induced by a system of filters that can be learned by a two stages model: the independent component analysis (ICA) to gather low level features and a mixtures of Bernoulli distributions identifying the hidden dependencies. Finally these two stages are used to build the cascade of filters.
J ul 2 00 7 KCL-MTH-07-08 From boundary to bulk in logarithmic CFT

The analogue of the charge-conjugation modular invariant for rational logarithmic conformal field theories is constructed. This is done by reconstructing the bulk spectrum from a simple boundary condition (the analogue of the Cardy ‘identity brane’). We apply the general method to the c1,p triplet models and reproduce the previously known bulk theory for p = 2 at c = −2. For general p we verify that the resulting partition functions are modular invariant. We also construct the complete set of 2p boundary states, and confirm that the identity brane from which we started indeed exists. As a by-product we obtain a logarithmic version of the Verlinde formula for the c1,p triplet models. Email: gaberdiel@itp.phys.ethz.ch Email: ingo.runkel@kcl.ac. uk
ICA of functional MRI data: an overview.

Independent component analysis (ICA) has found a fruitful application in the analysis of functional magnetic resonance imaging (fMRI) data. A principal advantage of this approach is its applicability to cognitive paradigms for which detailed a priori models of brain activity are not available. ICA has been successfully utilized in a number of exciting fMRI applications including the identification of various signal-types (e.g. task and transiently task-related, and physiology-related signals) in the spatial or temporal domain, the analysis of multi -subject fMRI data, the incorporation of a priori information, and for the analysis of complex -valued fMRI data (which has proved challenging for standard approaches). In this paper, we 1) introduce fMRI data and its properties, 2) review the basic motivation for using ICA on fMRI data, and 3) review the current work on ICA of fMRI with some specific examples from our own work. The purpose of this paper is to motivate ICA research to focus upon this exciting application.
MicroRNA-10b Promotes Nucleus Pulposus Cell Proliferation through RhoC-Akt Pathway by Targeting HOXD10 in Intervetebral Disc Degeneration

Aberrant proliferation of nucleus pulposus cell is implicated in the pathogenesis of intervertebral disc degeneration. Recent findings revealed that microRNAs, a class of small noncoding RNAs, could regulate cell proliferation in many pathological conditions. Here, we showed that miR-10b was dramatically upregulated in degenerative nucleus pulposus tissues when compared with nucleus pulposus tissues isolated from patients with idiopathic scoliosis. Moreover, miR-10b levels were associated with disc degeneration grade and downregulation of HOXD10. In cultured nucleus pulposus cells, miR-10b overexpression stimulated cell proliferation with concomitant translational inhibition of HOXD10 whereas restored expression of HOXD10 reversed the mitogenic effect of miR-10b. MiR-10b-mediated downregulation of HOXD10 led to increased RhoC expression and Akt phosphorylation. Either knockdown of RhoC or inhibition of Akt abolished the effect of miR-10b on nucleus pulposus cell proliferation. Taken together, aberrant miR-10b upregulation in intervertebral disc degeneration could contribute to abnormal nucleus pulposus cell proliferation through derepressing the RhoC-Akt pathway by targeting HOXD10. Our study also underscores the potential of miR-10b and the RhoC-Akt pathway as novel therapeutic targets in intervertebral disc degeneration.
Edge-triggering vs. two-phase level-clocking

Level-clocked designs that employ a two-phase, nonoverlapping clocking scheme have the theoretical potential to operate up to twice as fast as edge-triggered designs. We have run experiments that demonstrate, however, that edge-triggering is often just as fast as two-phase clocking, and that the speed potential of two-phase clocking is generally not obtained except when the delay between any two consecutive latches is roughly uniform and close to the maximumgate delay. Moreover, our experiments show that asymmetrical clocking of a two-phase circuit often does not provide any speedup over optimal symmetric clocking schemes. Level-clocking can lead to substantial reductions in the number of storage elements in a circuit, however. Our experiments show that for edge-triggered circuitry that has been retimed to operate with the minimum possible clock period, by replacing each ip-op by a pair of level-sensitive latches and subsequently retiming the resulting two-phase circuit, the number of storage elements can be reduced by up to 38% without increasing the clock period of the nal design or aaecting its I/O speciication. Reductions of greater than 25% were achieved for more than one third of the circuits we tested. Our experiments were performed using Tim, a timing optimization package currently under development at MIT. We ran our tests on MCNC benchmark circuits, AT&T communication circuits, and custom circuitry designed for MIT's Alewife machine.
Peer support critical elements and experiences in supporting the homeless: A qualitative study

Peer supporters are individuals with lived experience and are an integral part of health care systems, providing support to those affected by various phenomena such as homelessness and addictions. However, little is known about the critical elements that underpin peer support interventions. This qualitative study sought to understand the critical elements of intentional peer support with a homeless population, voiced by those who provide and/or receive this support. Twenty-nine participants from 4 different homeless charities in England were interviewed about their experiences of providing/receiving peer support and what they felt were critical factors to its success. Participants defined peer support as an experience-based relationship, built upon mutual understanding, empathy, and support. Thematic analysis was utilised to in developing 6 themes. Results identified peers' persistence in developing unique experience-based relationships, providing social support, role modelling recovery, and peers' motivations were perceived as important factors involved in peer support. It was also found that peers described benefitting from helping, such as, undergoing transformative identity developments that helped them to escape homelessness. Through the retelling of their stories, they create meaning and restructure their autobiography, attributing experiences of homelessness as a catalyst for positive changes in their lives. Limitations and future research are discussed.