Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of Cell Component Production by Growth Rate in the Group B Streptococcus

ABSTRACT Group B Streptococcus (GBS) is the leading cause of bacterial sepsis and meningitis among neonates. While the capsular polysaccharide (CPS) is an important virulence factor of GBS, other cell surface components, such as C proteins, may also play a role in GBS disease. CPS production by GBS type III strain M781 was greater when cells were held at a fast (1.4-h mass-doubling time [td]) than at a slow (11-htd) rate of growth. To further investigate growth rate regulation of CPS production and to investigate production of other cell components, different serotypes and strains of GBS were grown in continuous culture in a semidefined and a complex medium. Samples were obtained after at least five generations at the selected growth rate. Cells and cell-free supernatants were processed immediately, and results from all assays were normalized for cell dry weight. All serotypes (Ia, Ib, and III) and strains (one or two strains per serotype) tested produced at least 3.6-fold more CPS at atd of 1.4 h than at atd of 11 h. Production of beta C protein by GBS type Ia strain A909 and type Ib strain H36B was also shown to increase at least 5.5-fold with increased growth rate (production at atd of 1.4 h versus 11 h). The production of alpha C protein by the same strains did not significantly change with increased growth rate. The effect of growth rate on other cell components was also investigated. Production of group B antigen did not change with growth rate, while alkaline phosphatase decreased with increased growth rate. Both CAMP factor and beta-hemolysin production increased fourfold with increased growth rate. Growth rate regulation is specific for select cell components in GBS, including beta C protein, alkaline phosphatase, beta-hemolysin, and CPS production.
Quasi-dynamic splines

In this work, we propose interactive and physically based animation of one-dimensional deformable models using geometrically exact energy formulation. The proposed mechanical model has a high level of accuracy: it is based on continuous spline support and continuum mechanics media equations. We also detail a new efficient solving scheme, that can automatically switch between dynamic and static during simulation. With this scheme, we want to raise inconsistencies that could show up when human user is interacting with a physical simulation. We finally present a practical example in which the proposed model provides high-quality interaction.
Transient decrease in water diffusion observed in human occipital cortex during visual stimulation

Using MRI, we report the observation of a transient decrease of the apparent diffusion coefficient (ADC) of water in the human brain visual cortex during activation by a black and white 8-Hz-flickering checkerboard. The ADC decrease was small (<1%), but significant and reproducible, and closely followed the time course of the activation paradigm. Based on the known sensitivity of diffusion MRI to cell size in tissues and on optical imaging studies that have revealed changes in the shape of neurons and glial cells during activation, the observed ADC findings have been tentatively ascribed to a transient swelling of cortical cells. These preliminary results suggest a new approach to produce images of brain activation with MRI from signals directly associated with neuronal activation, and not through changes in local blood flow.
SUBTYPING BOYS WITH CONDUCT PROBLEMS: CATEGORICAL AND DIMENSIONAL APPROACHES WITH MULIT-MODAL ASSESSMENT OF PSYCHOPHYSIOLOGY AND BEHAVIOR

Title of dissertation: SUBTYPING BOYS WITH CONDUCT PROBLEMS: CATEGORICAL AND DIMENSIONAL APPROACHES WITH MULIT-MODAL ASSESSMENT OF PSYCHOPHYSIOLOGY AND BEHAVIOR Michael Joseph Crowley, Doctor of Philosophy, 2004 Dissertation directed by: Professor Nathan A. Fox Department of Human Development This study examined the physiological and behavioral profile of a group of clinically referred boys (ages 8-12 years) with severe conduct problems. Cerebral EEG asymmetry, fear potentiated startle and cardiac functioning were assessed along with maternal reports of severe antisocial behavior and behavioral measures of reward seeking, reward dominance, and laboratory aggression. Drawing on research seeking to extend the concept of psychopathy to younger populations, this study implemented the Antisocial Process Screening Device (APSD; Frick & Hare, 2001) an assessment instrument designed to assess psychopathic characteristics in children. Two groups of clinically referred children with externalizing problems were screened from an outpatient psychiatry clinic, one with elevated scores on the APSD (> 25) and a second group with externalizing problems but without elevated scores on the APSD (< 20). A third group of comparison boys was recruited from the community. Findings did not support a fear deficit specific to boys with APSD elevations, but rather suggested under some conditions these children may have exaggerated startle reactivity. High APSD boys sought rewards to a greater extent than other clinically referred externalizing boys on a point-subtraction game, but not more than comparison boys. The point-subtraction game did not differentiate groups of boys on aggressive responding. Boys with elevated APSD scores were rated as displaying greater overt and covert antisocial behavior problems than clinically referred boys without high APSD
Portuguese adults' health status perception

Data from the study “Portuguese Population’s Food Habits and Lifestyles” were used. A national representative sample of 3529 Portuguese adults was interviewed at home between February and April 2009. Health status was evaluated by the EQ-5D (Szende et al. 1997). The EQ visual analogue scale rates the subject's own assessment of their health status (0 = worst imaginable health; 100 = best imaginable health). Physical activity was evaluated by the International Physical Activity Questionnaire (IPAQ; Craig et al. 2003). The present analysis is carried out in 2811 subjects due to incompleteness of 718 records.
Isolated right ventricular apical hypoplasia characterized by computed tomography and echocardiography

Isolated right ventricular apical hypoplasia is an unusual congenital heart disease that has been mentioned in only one report to our knowledge. We describe the case of a 62‐year‐old male patient suffering from recurrent abdominal distention, nausea, and lower extremity edema. The right ventricular morphologic abnormalities as shown by echocardiography and CT were comparable to those of left ventricular apical hypoplasia, suggesting right ventricular apical hypoplasia. However, this speculative diagnosis remains to be confirmed by additional cases. © 2017 Wiley Periodicals, Inc. J Clin Ultrasound 46:82–84, 2018;
Modified generalized method of moments for a robust estimation of polytomous logistic model

The maximum likelihood estimation (MLE) method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM) approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.
Potential of ILRIS3D Intensity Data for Planar Surfaces Segmentation

Intensity value based point cloud segmentation has received less attention because the intensity value of the terrestrial laser scanner is usually altered by receiving optics/hardware or the internal propriety software, which is unavailable to the end user. We offer a solution by assuming the terrestrial laser scanners are stable and the behavior of the intensity value can be characterized. Then, it is possible to use the intensity value for segmentation by observing its behavior, i.e., intensity value variation, pattern and presence of location of intensity values, etc. In this study, experiment results for characterizing the intensity data of planar surfaces collected by ILRIS3D, a terrestrial laser scanner, are reported. Two intensity formats, grey and raw, are employed by ILRIS3D. It is found from the experiment results that the grey intensity has less variation; hence it is preferable for point cloud segmentation. A warm-up time of approximate 1.5 hours is suggested for more stable intensity data. A segmentation method based on the visual cues of the intensity images sequence, which contains consecutive intensity images, is proposed in order to segment the 3D laser points of ILRIS3D. This method is unique to ILRIS3D data and does not require radiometric calibration.
Efficient Medical Image Enhancement using CLAHE Enhancement and Wavelet Fusion

Medical image processing is a challenging field of research since the captured images suffers from the noise and poor contrast. The efficiency of the medical image processing depends on the quality of the captured medical images. Major factors for the low contrast medical images are age of capturing equipments, poor illumination conditions and in-experience of medical staff. Thus, contrast enhancement methods are used for improving the contrast of medical images before being used. In this paper an combination of the contrast limited adaptive histogram equalization (CLAHE) method and the wavelet based Fusion techniques are used for designing the efficient medical image enhancement method. Method is capable of adapting the Fusion rules adaptively for best enhancement results. First CLAHE image enhancement is used for improving the contrast of the medical images. then in second stage 2D Discrete wavelet transformation based adaptive image fusion is used for fusing the original and CLAHE output images. For testing the performance SNR and entropy are calculated and used as parameters. It is found that based on adaptive Fusion the visual content of the medical images are efficiently improved under all kind of capturing environments.
Childhood Physical and Emotional Abuse by a Parent: Transference Effects in Adult Interpersonal Relations

Extending research on transference and the relational self (Andersen & Chen, 2002), female undergraduates with or without a history of physical and emotional abuse by a loved parent participated in an experiment manipulating parental resemblance and threat-relevant interpersonal context in a new person. Transference elicited differences not evident in the control condition between abused and nonabused participants’ responses, with greater rejection expectancy, mistrust, dislike, and emotional indifference reported by abused participants. Immediate implicit affect was more positive in transference than in the control condition regardless of abuse history. Yet, abused participants in transference also reported increased dysphoria that was markedly attenuated when interpersonal threat was primed, and no such pattern occurred among nonabused participants. Evidence that interpersonally guarded and affectively complex responses are triggered in transference among previously abused individuals suggests that this social-cognitive process may underlie long-term interpersonal difficulties associated with parental abuse.
Depth-layer-based multiview image synthesis and coding for interactive z- and x-dimension view switching

In an interactive multiview image navigation system, a user requests switches to adjacent views as he observes the static 3D scene from different viewpoints. In response, the server transmits encoded data to enable client- side decoding and rendering of the requested viewpoint images. It is clear that there exists correlation between consecutive requested viewpoint images that can be exploited to lower transmission rate. In previous works, this is done using a pixel-based synthesis and coding approach for view-switch along the x-dimension (horizontal camera motion): given texture and depth maps of the previous view, texture pixels are individually shifted horizontally to the newly requested view, each according to its disparity value, via depth-image-based rendering (DIBR). Unknown pixels in the disoccluded region in the new view (pixels not visible in the previous view) are either inpainted, or intra-coded and transmitted by server for reconstruction at decoder. In this paper, to enable efficient view-switch along the z-dimension (camera motion into / out of the scene), we propose an alternative layer-based synthesis and coding approach. Specifically, we first divide each multiview image into depth layers, where adjacent pixels with similar depth values are grouped to the same layer. During a view-switch into the scene, spatial region in a layer is enlarged via super-resolution, where the scale factor is determined by the distance between the layer and the camera. On the other hand, during a view-switch out of the scene, spatial region in a layer is shrunk via low-pass filtering and down-sampling. Due to high quality reconstruction of depth layers in the new view via rescaling, coding and transmission of a depth layer in the new view by server is necessary only in the rare case when the quality of layer-based reconstruction is poor, saving transmission rate. Experiments show that our layer-based approach can reduce bit-rate by up to 35% compared to previous pixel-based approach.
Using an Automatic Approach to Classify Reflective Language Learning Skills of ESL Students

This paper reports and discusses on a project about designing a digital tool to support Chinese undergraduate students in reflecting on their English language (L2) learning experience. The tool namely ACTIVE was developed primarily based on a classification framework called A-S-E-R and Latent Semantic Analysis. It can automatically classify reflective L2 learning skills into four elements with each divided into four hierarchical levels. This paper begins by presenting the background of the study, followed by the details of methods of automatic classification and performance evaluation. The results of the project indicate that the computer-generated ratings for students' reflection are comparable to human ratings.
Learning from Doing Participatory Rural Research: Lessons from the Peak District National Park

Understanding the socio-economic and environmental implications of rural change requires the active participation of many research disciplines and stakeholders. However, it remains unclear how to best integrate participatory and biophysical research to provide information useful to land managers and policy makers. This paper presents findings of a RELU scoping study that has formulated and applied a research framework based on stakeholder participation and adaptive learning to model rural change in the Peak District National Park in the north of England. The paper describes a learning process that integrates different types of knowledge to produce future scenarios that describe possible economic and environmental changes due to a national review of burning practices on heather moorland and blanket bogs. We stress the need for using social network analysis to structure stakeholder engagement and outline how a range of participatory approaches can facilitate more inclusive environmental planning and policy development.
Sequence Analysis and Potentials of the Native RbcS Promoter in the Development of an Alternative Eukaryotic Expression System Using Green Microalga Ankistrodesmus convolutus

The availability of highly active homologous promoters is critical in the development of a transformation system and improvement of the transformation efficiency. To facilitate transformation of green microalga Ankistrodesmus convolutus which is considered as a potential candidate for many biotechnological applications, a highly-expressed native promoter sequence of ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit (AcRbcS) has been used to drive the expression of β-glucuronidase (gusA) gene in this microalga. Besides the determination of the transcription start site by 5′-RACE, sequence analysis revealed that AcRbcS promoter contained consensus TATA-box and several putative cis-acting elements, including some representative light-regulatory elements (e.g., G-box, Sp1 motif and SORLIP2), which confer light responsiveness in plants, and several potential conserved motifs (e.g., CAGAC-motif, YCCYTGG-motifs and CACCACA-motif), which may be involved in light responsiveness of RbcS gene in green microalgae. Using AcRbcS promoter::gusA translational fusion, it was demonstrated that this promoter could function as a light-regulated promoter in transgenic A. convolutus, which suggested that the isolated AcRbcS promoter was a full and active promoter sequence that contained all cis-elements required for developmental and light-mediated control of gene expression, and this promoter can be used to drive the expression of heterologous genes in A. convolutus. This achievement therefore advances the development of A. convolutus as an alternative expression system for the production of recombinant proteins. This is the first report on development of gene manipulation system for unicellular green alga A. convolutus.
Investigation of the approximation accuracy of the TP model transformation through the prototypical aeroelastic wing and the TORA system

The main focus of the present study is to investigate the numerical sensitivity of the TP model transformation. To be specific, our goal is to study how the approximation and complexity trade-off property of the TP model transformation depends on the discretization grid density. I INTRODUCTION The TP model form is a dynamic model representation whereupon Linear Matrix Inequality (LMI) based control design techniques (for instance PDC framework) can immediately be executed. It describes the Linear Parameter Varying (LPV) model by a convex combination of linear time invariant (LTI) models, where the convex combination is defined by the weighting functions of each parameter separately. The TP model representation is somewhat similar to the affine decomposition whereupon convex optimization or linear matrix inequality based control design techniques are applicable [6, 11, 20]. The TP model can always be given in the typical affine model form. An important difference between these model forms is that the convex hull of the given dynamic LPV model can readily be determined and analyzed in the TP model representation. Furthermore, the feasibility of the LMI's can be considerably relaxed in this representation via modifying the convex hull of the LPV model. The TP model transformation is a recently proposed numerical method to transform LPV models into TP model form [2, 3]. It is capable of transforming different LPV model representations (such as physical model given by analytic equations, fuzzy, neural network, genetic algorithm based models) into TP model form in a uniform way. In this sense it replaces the analytical derivations and affine decompositions (that could be a very complex or even an unsolvable task), and automatically results in the TP model form. Execution of the TP model transformation takes a few minutes by a regular Personal Computer. The TP model transformation minimizes the number of the LTI components of the resulting TP model. Furthermore, the TP model transformation is capable of resulting different convex hulls of the given LPV model. An important issue of the TP model transformation deals with the determination of the number of discarded singular values that defines the goodness of the approximation. The basic problem is the following: 1. The more dense grid is used during the transformation the more precise basis functions are obtained, i.e., the larger number of grid lines are defined the larger number of elements are resulting, so more precise basis 0-7803-9474-7/05/$20.00 ©2005 IEEE functions are obtained. …
Glutamic acid decarboxylase immunoreactivity in layer IV of barrel cortex of rat and mouse

The morphology and distribution of neurons and terminals that are immunoreactive to glutamic acid decarboxylase (GAD) were investigated in barrel cortex of the rat and mouse. The morphology of the GAD- immunoreactive neurons located in layer IV of the barrel field resembles that of the large, smooth stellate neurons described previously in Golgi studies. Most of the somas of GAD-positive neurons are located along the sides of the barrels. They constitute about 13 to 15% of the total neuronal population in layer IV. The spatial distribution of GAD-positive terminals in layer IV is similar to the distribution of GAD-positive somas. Very few GAD-positive neurons and terminals are found in the septal regions. This unique distribution of GAD immunoreactivity in the barrel cortex may serve as a model to study cortical inhibitory mechanisms.
On the Feature Discovery for App Usage Prediction in Smartphones

With the increasing number of mobile Apps developed, they are now closely integrated into daily life. In this paper, we develop a framework to predict mobile Apps that are most likely to be used regarding the current device status of a smartphone. Such an Apps usage prediction framework is a crucial prerequisite for fast App launching, intelligent user experience, and power management of smartphones. By analyzing real App usage log data, we discover two kinds of features: The Explicit Feature (EF) from sensing readings of built-in sensors, and the Implicit Feature (IF) from App usage relations. The IF feature is derived by constructing the proposed App Usage Graph (abbreviated as AUG) that models App usage transitions. In light of AUG, we are able to discover usage relations among Apps. Since users may have different usage behaviors on their smartphones, we further propose one personalized feature selection algorithm. We explore minimum description length (MDL) from the training data and select those features which need less length to describe the training data. The personalized feature selection can successfully reduce the log size and the prediction time. Finally, we adopt the kNN classification model to predict Apps usage. Note that through the features selected by the proposed personalized feature selection algorithm, we only need to keep these features, which in turn reduces the prediction time and avoids the curse of dimensionality when using the kNN classifier. The results based on a real dataset demonstrate the effectiveness of the proposed framework and show the predictive capability for App usage prediction.