Miracle-dz/UniFAR-FTUs huggingface dataset:
Gaussian process models for robust regression, classification, and reinforcement learning

Gaussian process models constitute a class of probabilistic statistical models in which a Gaussian process (GP) is used to describe the Bayesian a priori uncertainty about a latent function. After a brief introduction of Bayesian analysis, Chapter 3 describes the general construction of GP models with the conjugate model for regression as a special case (OHagan 1978). Furthermore, it will be discussed how GP can be interpreted as priors over functions and what beliefs are implicitly represented by this. The conceptual clearness of the Bayesian approach is often in contrast with the practical difficulties that result from its analytically intractable computations. Therefore approximation techniques are of central importance for applied Bayesian analysis. Chapter 4 describes Laplace's method, the Expectation Propagation approximation, and Markov chain Monte Carlo sampling for approximate inference in GP models. The most common and successful application of GP models is in regression problems where the noise is assumed to be homoscedastic and distributed according to a normal distribution. In practical data analysis this assumption is often inappropriate and inference is sensitive to the occurrence of more extreme errors (so called outliers). Chapter 5 proposes several variants of GP models for robust regression and describes how Bayesian inference can be approximated in each. Experiments on several data sets are presented in which the proposed models are compared with respect to their predictive performance and practical applicability. Gaussian process priors can also be used to define flexible, probabilistic classification models. Again, exact Bayesian inference is analytically intractable and various approximation techniques have been proposed, but no clear picture has yet emerged, as to when and why which algorithm should be preferred. Chapter 6 presents a detailed examination of the model, focusing on the question which approximation technique is most appropriate by investigating the structure of the posterior distribution. An experimental study is presented which corroborates the theoretical insights. Reinforcement learning deals with the problem of how an agent can optimise its behaviour in a sequential decision process such that its utility over time is maximised. Chapter 7 addresses applications of GPs for model-based reinforcement learning in continuous domains. If the environment's response to the agent's actions can be predicted using GP regression models, probabilistic planning and an approximate policy iteration algorithm can be implemented. A core concept in reinforcement learning is the value function, which describes the long-term strategic value of a state. Using GP models we are able to solve an approximate continuous equivalent of the Bellman equations, and it will be shown how this can be used to estimate value functions.
Permutation Decoding and the Stopping Redundancy Hierarchy of Cyclic and Extended Cyclic Codes

We introduce the notion of the stopping redundancy hierarchy of a linear block code as a measure of the tradeoff between performance and complexity of iterative decoding for the binary erasure channel. We derive lower and upper bounds for the stopping redundancy hierarchy via Lovasz's local lemma (LLL) and Bonferroni-type inequalities, and specialize them for codes with cyclic parity-check matrices. Based on the observed properties of parity-check matrices with good stopping redundancy characteristics, we develop a novel decoding technique, termed automorphism group decoding, that combines iterative message passing and permutation decoding. We also present bounds on the smallest number of permutations of an automorphism group decoder needed to correct any set of erasures up to a prescribed size. Simulation results demonstrate that for a large number of algebraic codes, the performance of the new decoding method is close to that of maximum-likelihood (ML) decoding.
Genome-Wide Search for Splicing Defects Associated with Amyotrophic Lateral Sclerosis (ALS)

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease caused by the degeneration of motor neurons. Although the cause of ALS is unknown, mutations in the gene that produces the SOD1 enzyme are associated with some cases of familial ALS. SOD1 is a powerful antioxidant that protects the body from damage caused by superoxide, a toxic free radical. It has been proposed that defects in splicing of some mRNAs, induced by oxidative stress, can play a role in ALS pathogenesis. Alterations of splicing patterns have also been observed in ALS patients and in ALS murine models, suggesting that alterations in the splicing events can contribute to ALS progression. Using Exon 1.0 ST GeneChips, which allow the definition of alternative splicing events (ASEs) , the SH-SY5Y neuroblastoma cell line has been profiled after treatment with paraquat, which by inducing oxidative stress alters the patterns of alternative splicing. Furthermore, the same cell line stably transfected with wt and ALS mutant SOD has also been profiled. The integration of the two ALS models efficiently moderates ASE false discovery rate, one of the most critical issues in high-throughput ASEs detection. This approach allowed the identification of a total of 14 splicing events affecting respectively both internal coding exons and 5' UTR of known gene isoforms.
Some applications for Newton-Krylov methods with a safeguard for GMRES( m ) ∗

Restarting GMRES, a linear solver frequently used in numerical schemes, is known to suﬀer from stagnation. In this paper, a simple strategy is proposed to detect and avoid stagnation, without modifying the standard GMRES code. Numerical tests with the modiﬁed GMRES( m ), GMRESH( m ) procedure, alone and as part of an inexact Newton procedure with several choices for the forcing term, demonstrate the eﬃciency of the proposed strategy
QUANTIFYING THE ECOLOGICAL SIGNIFICANCE OF MARSH SHADING: THE IMPACT OF PRIVATE RECREATIONAL DOCKS IN COASTAL GEORGIA

Submitted to: Coastal Resources Division Georgia Department of Natural Resources Brunswick, GA Submitted by: Dr. Clark Alexander Skidaway Institute of Oceanography Savannah, GA clark.alexander@skio.usg. edu and Michael Robinson Applied Coastal Research Laboratory Georgia Southern University Savannah, GA mike.robinson@skio.usg. edu 9 August 2006
Intonation modeling for TTS using a joint extraction and prediction approach

This paper presents a joint extraction and prediction framework for intonation modeling. The intonation model is based on a superpositional approach using B ézier curves. The components are attached to minor phrase and accent group. A greedy algorithm performs succesive partitions on training data using linguistic information. The parameters related to each partition are obtained using a global optimization procedure. In this way, the extraction process is closely related to the prediction step, and the final performance is higher. Several experiments are performed to test the hypothesis using a two-step intonation modeling procedure for comparison. Results reveal that the prediction accuracy is higher than the reference method. This approach avoids some parameter extraction steps that can produce additional noise, such as the interpolation step used in some intonation models.
The Aspergillus nidulans CREA protein mediates glucose repression of the ethanol regulon at various levels through competition with the ALCR‐specific transactivator.

Carbon catabolite repression in Aspergillus nidulans is mediated by a negative‐acting protein coded by the creA gene. We have investigated how CREA controls the expression of the ethanol regulon genes. CREA is a major component of the control of this regulon. Its presence in the cell results in a permanent, albeit partial, repression of the alc genes under all physiological growth conditions, even when the fungus is grown on carbon sources considered to be non‐repressing. A crucial step in the control processes is the repression of the positive‐acting specific regulatory gene alcR, by the binding of CREA on its cognate target sites on the alcR promoter. The removal of one of these targets, URSA, results in a 50% derepression of the alcR gene. Furthermore, the presence of this sequence contributes directly to the low alcR expression under nonrepressing conditions and reduces alcR promoter function by at least 100‐fold. CREA acts both on the regulatory gene alcR and directly on the two structural genes alcA and aldA, as glucose repression of the latter genes occurs in strains where alcR transcription is driven by a strong constitutive and derepressed promoter. In vivo and in vitro competition experiments show that CREA acts by competing directly with the binding of the ALCR activator for the same region of the alcR promoter, a region which encompasses overlapping targets for both regulatory proteins. These data are consistent with a model in which the activating and repressing regulatory proteins compete to regulate expression of the ethanol regulon genes.
Activity Recognition using Visual Tracking and RFID

Computer vision-based articulated human motion tracking is attractive for many applications since it allows unobtrusive and passive estimation of people's activities. Although much progress has been made on human-only tracking, the visual tracking of people that interact with objects such as tools, products, packages, and devices is considerably more challenging. The wide variety of objects, their varying visual appearance, and their varying (and often small) size makes a vision-based understanding of person-object interactions very difficult. To alleviate this problem for at least some application domains, we propose a framework that combines visual human motion tracking with RFID based object tracking. We customized commonly available RFID technology to obtain orientation estimates of objects in the field of RFID emitter coils. The resulting fusion of visual human motion tracking and RFID-based object tracking enables the accurate estimation of high-level interactions between people and objects for application domains such as retail, home-care, workplace-safety, manufacturing and others
Parametric Model Order Reduction by Matrix Interpolation

Abstract In this paper, a new framework for model order reduction of LTI parametric systems is introduced. After generating and reducing several local original models in the parameter space, a parametric reduced-order model is calculated by interpolating the system matrices of the local reduced models. The main task is to find compatible system representations with optimal interpolation properties. Two approaches for this purpose are presented together with several numerical simulations. Zusammenfassung In diesem Beitrag wird ein neuer Rahmen zur Modellordnungsreduktion parametrischer LZI-Systeme vorgestellt. Er sieht zunächst die Reduktion des Originalmodells in einigen Stützstellen des Parameterraums vor. Anschließend wird ein reduziertes parametrisches System generiert, indem die Systemmatrizen der lokalen Reduktionen durch geeignete Transformationen kompatibel gemacht und interpoliert werden. Hierfür werden zwei alternative Verfahren beschrieben, deren Eigenschaften an drei numerischen Testfällen dargestellt werden.
On a weighted Toeplitz operator and its commutant

We study the structure of a class of weighted Toeplitz operators and obtain a description of the commutant of each operator in this class. We make some progress towards proving that the only operator in the commutant which is not a scalar multiple of the identity operator and which commutes with a nonzero compact operator is zero. The proof of the main statement relies on a conjecture which is left as an open problem.
Examination of the macronuclear replication band in Euplotes eurystomus with monoclonal antibodies

A panel of eight monoclonal antibodies (MAbs) was prepared from spleen cells of mice immunized with macronuclear replication bands (RBs) isolated from Euplotes eurystomus. Antibodies were investigated with a solid phase radioimmunoassay (RIA) using either soluble chromatin from isolated RBs or from total macronuclei as antigen. The RIA showed that several MAbs recognized antigens present only in the RB or macronucleus, whereas others recognized antigens present in both structures. Specificity of the MAbs was also examined by indirect immunofluorescence. Antibody C10 recognized an antigen in the rear zone of the RB, whereas MAbs G6 and B2 appeared to stain both the forward and rear zones of the RB. Antibody A7 recognized an epitope distributed throughout the macronucleus except in the RB. Cytochemical studies with degradative enzymes suggested that antigens localized by immunofluorescence were composed of proteins. Immunoblots of SDS PAGE permitted identification of a few proteins that reacted with three of the RB-specific MAbs. Monoclonal antibodies that identify the presence or absence of reactivity of specific proteins in the RB could prove useful in the study of chromatin structure and the mechanism of chromatin replication.
Evidence for size and sex‐specific dispersal in a cooperatively breeding cichlid fish

African Great Lake cichlid populations are divided into thousands of genetic subpopulations. The low gene flow between these subpopulations is thought to result from high degrees of natal philopatry, heavy predation pressure, and a patchy distribution of preferred habitats. While predation pressure and habitat distribution are fairly straightforward to assess, data on dispersal distances and rates are scarce. In fishes, direct observations of dispersal events are unlikely, but dispersal can be studied using molecular markers. Using seven microsatellite loci, we examined dispersal in the cooperatively breeding cichlid fish, Neolamprologus pulcher. As this species is found in well‐defined groups clustered into subpopulations, we could assess dispersal on a narrow (within subpopulation) and broad (between subpopulation) scale. While fish were generally more related to others in their own subpopulation than they were to fish from other subpopulations, large males diverged from this pattern. Large males were more related to other large males from different subpopulations than they were to large males from their own subpopulation, suggesting more frequent dispersal by large males. Across subpopulations, relatedness between large males was higher than the relatedness among large females; this pattern was not detected in small males and small females. Within a subpopulation, individuals appeared to be preferentially moving away from relatives, and movement was unrestricted by the physical distance between groups. Our results highlight the importance of examining multiple spatial scales when studying individual dispersal biases.
Importance of Parent Talk on the Development of Preterm Infant Vocalizations

OBJECTIVE: To determine the sound environment of preterm infants cared for in the NICU and to test the hypothesis that infants exposed to more adult language will make more vocalizations. METHODS: This was a prospective cohort study of 36 infants who had a birth weight of ≤1250 g. Sixteen-hour recordings of the infant sound environment were made in the NICU from a digital language processor at 32 and 36 weeks' postmenstrual age. Adult word counts, infant vocalizations, and conversational turns were analyzed. RESULTS: Infant vocalizations are present as early as 32 weeks. Both adult word counts per hour and infant vocalizations per hour increase significantly between 32 and 36 weeks. Infant exposure to language as a percentage of time was small but increased significantly. When a parent was present, infants had significantly more conversational turns per hour than when a parent was not present at both 32 and 36 weeks (P < .0001). CONCLUSIONS: Preterm infants begin to make vocalizations at least 8 weeks before their projected due date and significantly increase their number of vocalizations over time. Although infant exposure to language increased over time, adult language accounted for only a small percentage of the sounds to which an infant is exposed in the NICU. Exposure to parental talk was a significantly stronger predictor of infant vocalizations at 32 weeks and conversational turns at 32 and 36 weeks than language from other adults. These findings highlight the powerful impact that parent talk has on the appearance and increment of vocalizations in preterm infants in the NICU.
Feeding and dementia: a systematic literature review.

AIM This paper reports a systematic review of the literature on interventions to promote oral nutritional intake of older people with dementia and feeding difficulty between 1993 and 2003. BACKGROUND Older people with dementia commonly experience difficulty with feeding, especially in the later stages of the condition. This topic and related nursing care was reviewed in 1993 and the conclusion was that there was little research into interventions that nurses could use to alleviate feeding difficulty. METHOD A systematic review of the literature was carried out using the CINAHL, Medline, EMBASE and Cochrane databases and the search terms 'feeding', 'eating' and 'dementia' combined as follows: '(feeding or eating) and (dementia)'. A second search was carried out combining the search terms 'mealtimes' and 'dementia' as follows: 'mealtimes and dementia'. The literature search was carried out on 1 December 2003 and papers were included in the review if retrieved by 31 December 2003. English language papers only were retrieved. RESULTS Sixty-seven papers were retrieved, of which 13 addressed interventions aimed at helping older people with dementia to feed. All studies reported positive outcomes but only one randomized controlled trial was reported. Music was the most common intervention but there were no standardized interventions or outcomes across the studies and none reported the use of power analysis to decide on sample size. There were problems in some studies with confounding variables. CONCLUSIONS Further research is needed into interventions aimed at how nurses can help older people with dementia to feed. There are some promising lines of enquiry, with music being one of these, but future studies need to use adequate samples and to use power calculations and account adequately for confounding variables. There is also a need to standardize interventions and outcomes across such studies to facilitate meta-analysis.
A material model for woven commingled glass-polypropylene composite fabrics using a hybrid finite element approach

Woven fabric composites made from commingled fibreglass and polypropylene fibres have the potential to make lightweight structural parts to replace metal structures in automobiles when competitively produced using thermostamping techniques. To expedite the acceptance of such composites, a credible design tool needs to be available to study the associated manufacturing process. For such a numerical method, a material model is required. Because the tows of the fabric are essentially inextensible, shear is the major deformation mode for assuming the stamped shape. The shear mechanical behaviour of fabric is obtained from a shear-frame test. A finite element model using a combination of truss and 2D solid elements is proposed. The truss elements represent the tows and use a nonlinear material model for capturing the increasing stiffness of the tows with increasing tensile strain. The 2D Solid elements capture the interaction between tows and the viscosity of the resin. The bias-extension test is a valuable test for investigating the shear performance of woven fabric composites. Using the finite element method, the bias-extension test is modelled, analysed and compared experimentally to verify the credibility of the woven-fabric material model.
Quantifying the Local Kinematic Effect in Actuated Plates via Strain Energy Distribution

This article examines the distribution of strain energy in the various component materials of actuated plates and investigates the manner in which the strain energy distribution is influenced by the actuated span-to-thickness ratio and the thickness of the adhesive bond layer. Furthermore, the article investigates the effect of modeling choices (e.g., kinematic assumptions and mesh density) on the predicted magnitude and mode of the dominant strain energy form in each component material. These computed parameters can be used to quantify the overall efficiency of an actuated plate in addition to aiding the understanding of the local mechanics that govern the process. The focus problem consists of a square aluminum plate with a single symmetric pair of surface-mounted piezoceramic actuators that are used to produce in-plane extension or bending in the aluminum plate. The behavior of the actuated plate is examined over a range of plate thicknesses and adhesive bond layer thicknesses by using a series of finite element models that feature different levels of kinematic complexity and different levels of two-dimensional (2-D) mesh density. The results of the study emphasize the need for discrete layer kinematics in determining the magnitude and mode of the dominant strain energy form in each constituent material; however, these computed parameters are shown to be rather insensitive to changes in 2-D mesh density. Most importantly, the study confirms the existence and quantifies the magnitude of the local kinematic effect, whereby a portion of the available actuation energy is diverted to the production of localized transverse shear deformation and transverse normal deformation, thus reducing the amount of actuation energy available to produce in-plane deformation in the structural substrate.
Determinants of Vitamin D Status among Overweight and Obese Puerto Rican Adults

Background/Aims: Low vitamin D status is highly prevalent worldwide, and the major determinants are sun exposure and vitamin D intake. We aimed to measure vitamin D status in a sample of overweight/obese adults in Puerto Rico, an area with plenty of sun exposure, and relate it to vitamin D intake, sun exposure and body composition. Methods: Serum 25(OH)D levels (liquid chromatography-tandem mass spectrometry), body weight and fat (bioimpedance), vitamin D intake and sun exposure (questionnaires) were assessed. Analysis included age-adjusted correlations and multivariate regression. Results: In 98 subjects (66% females; 40–65 years), median serum 25(OH)D levels were 30.7 ng/ml (25–75th percentile 25.0–37.3); 55% had levels >30 ng/ml, 31% had levels between 20 and 30 ng/ml and 14% had levels <20 ng/ml. Total vitamin D intake was 180 IU/day (45–615), and the sun exposure score was 22 (17–27). After adjusting for gender, 25(OH)D levels were significantly correlated with vitamin D intake (r = 0.24, p = 0.018), the sum of sun exposure and vitamin D intake indices (r = 0.34, p = 0.001) and percent body fat (r = –0.25, p = 0.01). After adjusting for age, gender and percent body fat, the sum of sun exposure and vitamin D intake indices remained statistically associated with 25(OH)D levels (β = 1.5, p < 0.01). Conclusions: In this group of overweight and obese individuals, 25(OH)D was significantly related to vitamin D intake, sun exposure and vitamin D intake indices and percent body fat.
Author Entropy: A Metric for Characterization of Software Authorship Patterns

We propose the concept ofauthor entropyand describe how file-level entropy measures may be used to understand and characterize authorship patterns within individual files, as well as across an entire project. As a proof of concept, we compute author entropy for 28,955 files from 33 open-source projects. We explore patterns of author entropy, identify techniques for visualizing author entropy, and propose avenues for further study.