Miracle-dz/UniFAR-FTUs huggingface dataset:
Reducing Parameter Space for Word Alignment

This paper presents the experimental results of our attemps to reduce the size of the parameter space in word alignment algorithm. We use IBM Model 4 as a baseline. In order to reduce the parameter space, we pre-processed the training corpus using a word lemmatizer and a bilingual term extraction algorithm. Using these additional components, we obtained an improvement in the alignment error rate.
Interleukin-4 can be a key positive regulator of inflammatory arthritis.

OBJECTIVE Development of arthritis in the K/BxN mouse model depends on the induction of high titers of antibodies against the enzyme glucose-6-phosphate isomerase (GPI), promoted by CD4(+) T cells expressing a GPI-specific transgenic T cell receptor (TCR). This study was undertaken to determine whether this strong autoantibody response depends on T cell differentiation to the Th1 or Th2 phenotype. METHODS The roles of Th cell-biasing cytokines were investigated by introducing the interleukin-4 (IL-4) and IL-12-specific subunit p35 (IL-12p35)-knockout mutations into the K/BxN model and evaluating the impact of these deficiencies on disease. The IL-4-expressing cell types in K/BxN mice were revealed by crossing in a knockin alteration, which resulted in green fluorescent protein expression controlled by endogenous IL-4 gene-regulatory elements. Transfer experiments permitted the identification of the IL-4-producing cell type required for arthritis, and quantitative reverse transcriptase-polymerase chain reaction allowed for determination of the cytokine profile of K/BxN T cells. RESULTS While IL-12p35 appeared dispensable for the development of arthritis, IL-4 was crucial for full development of disease. The GPI-reactive TCR of standard K/BxN mice induced the transcriptional activation of the IL-4 locus in CD4(+) T cells and eosinophils, and CD4(+) T cells were the obligatory source of IL-4 for disease. However, the cytokine profile of K/BxN T cells revealed that K/BxN arthritis is not a "pure" Th2 disease. CONCLUSION The K/BxN model, although not a classic Th2 disease, depends critically on IL-4. The potential of IL-4 to promote inflammatory arthritis should be considered when proposing therapies for rheumatoid arthritis aimed at biasing T cells toward IL-4 production.
The reason I jump : the inner voice of a thirteen-year-old boy with autism

'Composed by a writer still with one foot in childhood, and whose autism was at least as challenging and life-defining as our son's, THE REASON I JUMP was a revelatory godsend. Reading it felt as if, for the first time, our own son was talking to us about what was happening inside his head. ' Written by Naoki Higishida when he was only thirteen, this remarkable book explains the often baffling behaviour of autistic children and shows the way they think and feel - such as about the people around them, time and beauty, noise, and themselves. Naoki abundantly proves that autistic people do possess imagination, humour and empathy, but also makes clear, with great poignancy, how badly they need our compassion, patience and understanding. David Mitchell and his wife have translated Naoki's book so that it might help others dealing with autism, and generally illuminate a little-understood condition. Like The Diving Bell and the Butterfly, it gives us an exceptional chance to enter the mind of another and see the world from a strange and fascinating perspective. The book also features eleven original illustrations, inspired by Naoki's words, by the artistic duo Kai and Sunny.
Building an Information System for a Distributed Testbed

This paper describes an information system designed to support the large volume of monitoring information generated by a distributed testbed. This monitoring information is produced by several subsystems and consists of status and performance data that needs to be federated, distributed, and stored in a timely and easy to use manner. Our approach differs from existing approaches because it federates and distributes information at a low architectural level via messaging; a natural match to many of the producers and consumers of information. In addition, a database is easily layered atop the messaging layer for consumers that want to query and search the information. Finally, a common language to represent information in all layers of the information system makes it significantly easier for users to consume information. Performance data shows that this approach meets the significant needs of FutureGrid and would meet the needs of other infrastructures.
Family Impact Analysis: Application to Child Custody Determination.

This paper examines current changes in child custody determination policies and related programs. Family Impact Analysis, a framework for assessing the impact of legal and social policy on the family, is described as an objective approach of investigating the implementation of family legal policy. The utility of Family Impact Analysis is illustrated by its application to an analysis of child custody policy and a recently developed "mediation counseling" program used in child custody determination cases in the family court services of Hennepin County (Minneapolis), Minnesota.
Predictors of exercise capacity in patients with chronic heart failure

Background Heart failure is a major and growing societal problem characterized by high mortality, frequent hospitalization, reduced quality of life and a complex therapeutic regimen. The six-minute walking test (6-MWT) may serve as a useful and reproducible test for assessing exercise capacity in heart failure patients and has been suggested as a simple, well-tolerated and inexpensive alternative to cardiopulmonary exercise testing (CPET). The CPET and 6-MWT are the most broadly used for assessing functional limitation in patients with heart failure. Echocardiography is well qualified to meet the growing need for noninvasive imaging in the expanding heart failure population. Methods This study included 132 consecutive patients (61 ± 10 years, 45% women) with stable heart failure. All patients underwent 6-MWT and Doppler echocardiographic examination on the same day. Clinical, biochemical and echocardiographic predictors were analyzed to assess predictors of exercise capacity. Patients were divided into two groups based on the 6-MWT distance. The first group comprised patients with limited exercise performance (≤300 m), and the second group, patients with good exercise performance (>300 m). Results In univariate analysis, patients' age [0.931 (0.895–0.968), P < 0.001], arterial hypertension [0.481 (0.239–0.967), P = 0.040], blood urea level [0.860 (0.759–0.975), P = 0.019], New York Heart Association (NYHA) class [0.441 (0.245–0.795), P = 0.006], early diastolic E wave [1.014 (1.000–1.029), P = 0.047], total isovolumic time (t-IVT) [0.868 (0.796–0.947), P = 0.001], Tei index [0.112 (0.028–0.450), P = 0.002], and E′ of left-ventricular (LV) lateral wall [1.188 (1.099–1.400), P = 0.039] independently predicted poor 6-MWT performance (<300 m). In multivariate analysis, only patients' age [0.948 (0.902–0.996), P = 0.034], arterial hypertension [0.351 (0.133–0.922), P = 0.034], and t-IVT [0.828 (0.725–0.946), P = 0.005] independently predicted poor 6-MWT performance (<300 m). Conclusion In chronic stable heart failure patients, in addition to age, systemic hypertension as well as LV asynchrony, as reflected by prolonged t-IVT, are independent predictors of poor exercise capacity.
Autologous serum and plasma rich in growth factors in ophthalmology: preclinical and clinical studies

The use of blood derivatives represents an alternative therapeutic approach that is gaining interest in regenerative medicine due to its potential to stimulate and accelerate tissue healing. Autologous serum eye drops and platelet‐enriched plasma eye drops are being used in the treatment of different ophthalmological disorders. In this review, we summarize the different blood‐derived formulations used in the treatment and care of ocular surface disorders. The biological basis and use of autologous serum and plasma rich in growth factors are deeply evaluated as well as the challenges to be addressed in the future in this new generation of blood‐derived therapies.
Substance, embodiment and domination in an orgasmic community

This thesis untangles and examines the myriad of social relationships, as they exist in a residential community in San Francisco. The community has a central meditative practice referred to as Orgasmic Meditation, which involves the ritualised stroking of a woman’s clitoris by a male partner in a group setting. Using ethnographic fieldwork and theoretical analysis, the thesis considers issues of embodiment, substance, and domination. The ethnographic evidence supports the argument that understanding the role of the body and embodiment is fundamental to understanding processes of self construction, and of power and domination in a social context. The community examined in this thesis is a so-called ‘transformational’ community; one where individuals can ‘work on themselves’ in order to better fulfil what they understand as their potential. This transformation is facilitated by the ‘movement of energy’ brought about by Orgasmic Meditation. By undertaking this mindful physical practice, the way practitioners understand the constitution of their bodies, and subsequently their social relationships, is transformed. The embodiment and visceral experience of ‘Orgasmic energy’ impacts on the social structuring of the community. Emile Durkheim’s work on religious ‘force’ is used to suggest that in this community, society is Orgasm, and Orgasm is society. The thesis analyses the residential experience of living within the community, practicing Orgasmic Meditation, and being involved with the running of the organisation. Deep immersion in the field site has allowed for a deeper understanding of the phenomenological and visceral experience of the embodied transformation afforded through Orgasmic Meditation and the relationship between a new embodied subjectivity and the hierarchical organisation of the community. The thesis examines the transformation of the organisation over a period of time and how this impacted on the residents. It uses Durkheim, Bourdieu, Douglas, Csordas, and Deleuze and Guattari to examine the relationship between the body and society, and how this is affected by social change. It employs the work of Bataille, and ethnographers who have worked in Melanesia such as Marilyn Strathern, to examine the role of an embodied substance in the constitution of self and other, and in social relationships. Finally, the thesis examines the relationship between the organisation and wider, ‘mainstream’ society, arguing that although there is an attempt at separation and distinction, particularly within new forms of subjectivity encouraged by Orgasmic Meditation, the oscillation, movement and tension between the utopian ideals of the organisation and the established institutions of mainstream society becomes too much to manage for many of the residents, some of whom leave feeling disillusioned. As a contribution to the anthropological literature, this thesis reflects on the role of the body in contexts of power, and how understandings of self and substance influence social form.
Information-theoretic limits of learning the structure of Bayesian networks

In this paper, we study the information-theoretic limits of learning the structure of Bayesian networks, on discrete as well as continuous random variables, from a finite amount of data. We show that under certain parameterizations of the Bayesian network --- the minimum number of samples required to learn the "true" network grows as $\mathcal{O}(M)$ and $\mathcal{O}(S\log M)$ for non-sparse and sparse Bayesian networks respectively --- where $M$ is the number of variables in the network and $S$ is the maximum number of parents of any node in the network. We study various commonly used Bayesian networks, such as Conditional Probability Table (CPT) based networks, Noisy-OR networks, Logistic regression (LR) networks, and Gaussian networks. We identify various important parameters of the conditional distributions that affect the complexity of learning such models, like the maximum inverse probability for CPT networks, the failure probability for Noisy-OR networks, the $\ell_2$ norm of weight vectors for LR networks and the signal and noise parameters for Gaussian networks. We also show that an existing procedure calle SparsityBoost, by Brenner and Sontag, for learning binary CPT networks is information-theoretically optimal in the number of variables.
Information theory and predictability for low-frequency variability

Abstract A predictability framework, based on relative entropy, is applied here to low-frequency variability in a standard T21 barotropic model on the sphere with realistic orography. Two types of realistic climatology, corresponding to different heights in the troposphere, are used. The two dynamical regimes with different mixing properties, induced by the two types of climate, allow the testing of the predictability framework in a wide range of situations. The leading patterns of empirical orthogonal functions, projected onto physical space, mimic the large-scale teleconnections of observed flow, in particular the Arctic Oscillation, Pacific–North American pattern, and North Atlantic Oscillation. In the ensemble forecast experiments, relative entropy is utilized to measure the lack of information in three different situations: the lack of information in the climate relative to the forecast ensemble, the lack of information by using only the mean state and variance of the forecast ensemble, and informati.
Predictor correlation impacts machine learning algorithms: implications for genomic studies

MOTIVATION The advent of high-throughput genomics has produced studies with large numbers of predictors (e.g. genome-wide association, microarray studies). Machine learning algorithms (MLAs) are a computationally efficient way to identify phenotype-associated variables in high-dimensional data. There are important results from mathematical theory and numerous practical results documenting their value. One attractive feature of MLAs is that many operate in a fully multivariate environment, allowing for small-importance variables to be included when they act cooperatively. However, certain properties of MLAs under conditions common in genomic-related data have not been well-studied--in particular, correlations among predictors pose a problem. RESULTS Using extensive simulation, we showed considering correlation within predictors is crucial in making valid inferences using variable importance measures (VIMs) from three MLAs: random forest (RF), conditional inference forest (CIF) and Monte Carlo logic regression (MCLR). Using a case-control illustration, we showed that the RF VIMs--even permutation-based--were less able to detect association than other algorithms at effect sizes encountered in complex disease studies. This reduction occurred when 'causal' predictors were correlated with other predictors, and was sharpest when RF tree building used the Gini index. Indeed, RF Gini VIMs are biased under correlation, dependent on predictor correlation strength/number and over-trained to random fluctuations in data when tree terminal node size was small. Permutation-based VIM distributions were less variable for correlated predictors and are unbiased, thus may be preferred when predictors are correlated. MLAs are a powerful tool for high-dimensional data analysis, but well-considered use of algorithms is necessary to draw valid conclusions. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Krogh‐Cylinder and Infinite‐Domain Models for Washout of an Inert Diffusible Solute from Tissue

Models based on the Krogh‐cylinder concept are developed to analyze the washout from tissue by blood flow of an inert diffusible solute that permeates blood vessel walls. During the late phase of washout, the outflowing solute concentration decays exponentially with time. This washout decay rate is predicted for a range of conditions.
Evidence for surface states in pristine and Co-doped ZnO nanostructures: magnetization and nonlinear optical studies

An unexpected presence of ferromagnetic (FM) ordering in nanostructured ZnO has been reported previously. Recently, from our detailed magnetization studies and ab initio calculations, we attributed this FM ordering in nanostructured ZnO to the presence of surface states, and a direct correlation between the magnetic properties and crystallinity of ZnO was observed. In this study, through a systematic sample preparation of both pristine and Co-doped ZnO nanostructures, and detailed magnetization and nonlinear optical (NLO) measurements, we confirm that the observed FM ordering is due to the presence of surface states.
Y‐chromosome variation in South Iberia: Insights into the North African contribution

Population of Pedroches Valley, a hypothetical Berber settlement, located in the northwest portion of Córdoba province (Andalusia, Spain), had been analyzed for its Y‐chromosome diversity. Moreover, to contextualize this population, 127 Y‐chromosomes from a general Andalusia sample and a North African Berber community (Marrakech, Morocco) were also typed. For all samples, 24 single nucleotide polymorphisms of the non‐recombining portion of the Y‐chromosome (NRY) were analyzed and those samples described as belonging to E3b1b‐M81 haplogroup were also typed for 16 Y‐chromosome short tandem repeats. Our Analysis showed low levels of North African E3b1b‐M81 haplogroup in the Pedroches Valley population (1.5%), which is a lower contribution than would be expected. This result rejects the hypothesis of a gradual genetic assimilation of Berber settlers during the Islamic period. Am. J. Hum. Biol., 2009. © 2009 Wiley‐Liss, Inc.
Reliable Accent-Specific Unit Generation With Discriminative Dynamic Gaussian Mixture Selection for Multi-Accent Chinese Speech Recognition

In this paper, we propose a discriminative dynamic Gaussian mixture selection (DGMS) strategy to generate reliable accent-specific units (ASUs) for multi-accent speech recognition. Time-aligned phone recognition is used to generate the ASUs that model accent variations explicitly and accurately. DGMS reconstructs and adjusts a pre-trained set of hidden Markov model (HMM) state densities to build dynamic observation densities for each input speech frame. A discriminative minimum classification error criterion is adopted to optimize the sizes of the HMM state observation densities with a genetic algorithm (GA). To the author's knowledge, the discriminative optimization for DGMS accomplishes discriminative training of discrete variables that is first proposed. We found the proposed framework is able to cover more multi-accent changes, thus reduce some performance loss in pruned beam search, without increasing the model size of the original acoustic model set. Evaluation on three typical Chinese accents, Chuan, Yue and Wu, shows that our approach outperforms traditional acoustic model reconstruction techniques with a syllable error rate reduction of 8.0%, 5.5% and 5.0%, respectively, while maintaining a good performance on standard Putonghua speech.
Full-Chip Model for Leakage-Current Estimation Considering Within-Die Correlation

In this paper, we present an efficient technique for finding the mean and variance of the full-chip leakage of a candidate design, while considering logic structures and both die-to-die and within-die (WID) process variations, and taking into account the spatial correlation due to WID variations. Our model uses a ldquorandom-gaterdquo concept to capture high-level characteristics of a candidate chip design, which are sufficient to determine its leakage. These high-level characteristics include information about the process, the standard cell library, and expected design characteristics. We show empirically that, for large gate count, the set of all chip designs that share the same high-level characteristics have approximately the same leakage, with very small error. Therefore, our model can be used as either an early or a late estimator of leakage, with high accuracy. In its simplest form, we show that full-chip-leakage estimation reduces in finding the area under a scaled version of the WID channel length autocorrelation function, which can be done in constant time.
An ultra-low-power front-end neural interface with automatic gain for uncalibrated monitoring

This paper presents a dynamic front-end towards achieving unsupervised single-neuron activity monitoring. By implementing at the front-end, an automatic gain control that is optimized for neural signal dynamics, subsequent processing can be achieved without the need for calibration. The system uses three amplification stages (low-noise first stage, variable-gain second stage and high-gain third stage), a tuneable high-pass filter, and a feedback loop to tune the variable gain. The circuit has been implemented in a commercially-available 0.18 μm CMOS technology with total power consumption between 1.79 and 1.95 μW. The front-end achieves a variable gain from 52 to 86.4 dB with 3 kHz bandwidth and a high-pass filter that is tuneable from 100-300 Hz. The input referred noise is 9.66 μV with a total harmonic distortion of under 1%.
Navigation aiding stick for the visually impaired

One of the major challenges faced by the blind during mobility is obstacle avoidance and navigation. In this paper, the design of a simple, cost effective cane has been discussed which will help the user in avoiding obstacles as well as in navigation. An array of ultrasonic sensors and standalone GPS receiver with magnetometer has been interfaced with Arduino board for obstacle detection and navigation respectively. The sensor interface and the algorithms for obstacle detection and navigation have been discussed.
Evaluation of the treatment of non‐melanoma skin cancers by surgical excision

A retrospective study of all non‐melanoma skin cancers excised by two dermatologists at a private practice in 2004 (excluding Mohs microscopic surgery cases) was conducted. Two hundred and forty‐one patients were treated, with a total of 453 tumours excised. The overall incomplete excision rate was 2.2% (10/453). For basal cell cancers, the incomplete excision rate was 1.54% (5/324) and for squamous cell cancers including Bowen's disease the incomplete excision rate was 3.9% (5/129). The majority of repairs were primary closures (82.6%). Although a significant proportion of the tumours were from the head and neck region (45.9%), this study demonstrated that careful patient selection, experience of the surgeon and adherence to recommended excision margins can achieve a favourable incomplete excision rate.
LOSSLESS COMPRESSION BASED ON JPEG 2000 FOR EFFICIENT TRANSMISSION OF HIGH RESOLUTION COLOR AERIAL IMAGES Graduate Student :

Aerial image collections have experienced exponential growth in size in recent years. These high resolution images are often viewed at a variety of scales. When an image is displayed at reduced scale, maximum quantization step sizes for visually lossless quality become larger. However, previous visually lossless coding algorithms quantize the image with a single set of quantization step sizes, optimized for display at the full resolution level. This implies that if the image is rendered at reduced resolution, there are significant amounts of extraneous information in the codestream. Thus, in this paper, we propose a method which effectively incorporates multiple quantization step sizes, for various display resolutions, into the JPEG2000 framework. If images are browsed from a remote location, this method can significantly reduce bandwidth usage by only transmitting the portion of the codestream required for visually lossless reconstruction at the desired resolution. Experimental results for high resolution color aerial images are presented.