Miracle-dz/UniFAR-FTUs huggingface dataset:
The Group B Streptococcal C5a Peptidase Is Both a Specific Protease and an Invasin

ABSTRACT The group B streptococcus (GBS) is a major cause of pneumonia, sepsis, and meningitis in neonates and a serious cause of mortality or morbidity in immunocompromised adults. Although these streptococci adhere efficiently and invade a variety of tissue-specific epithelial and endothelial cells, adhesins and invasins are still unknown. All serotypes of GBS studied to date express C5a peptidase (SCPB) on their surface. This investigation addresses the possibility that this relatively large surface protein has additional activities. Rabbit anti-SCPB serum inhibited invasion of lung epithelial A549 cells by the serotype Ia strain O90R, suggesting that SCPB is an invasin. This was confirmed by inserting an in-frame 25-amino-acid deletion into the scpB gene. Invasion of HEp2 and A549 human cell lines was significantly reduced by the mutation. Enzyme-linked immunosorbent assays were used to demonstrate that purified SCPB protein binds directly to HEp2 and A549 cells and also binds the extracellular matrix protein fibronectin. Binding was dose dependent and saturable. These results suggested that SCPB is one of several potential invasins essential for GBS colonization of damaged epithelium.
TEACHER'S CORNER: Structural Equation Modeling With the sem Package in R

R is free, open-source, cooperatively developed software that implements the S statistical programming language and computing environment. The current capabilities of R are extensive, and it is in wide use, especially among statisticians. The sem package provides basic structural equation modeling facilities in R, including the ability to fit structural equations in observed variable models by two-stage least squares, and to fit latent variable models by full information maximum likelihood assuming multinormality. This article briefly describes R, and then proceeds to illustrate the use of the tsls and sem functions in the sem package. The article also demonstrates the integration of the sem package with other facilities available in R, for example for computing polychoric correlations and for bootstrapping.
These conditions affect the capacity for photosynthesis in ways that increase the requirement for protective dissipation of excess light energy (

Why the leaves of many woody species accumulate anthocyanins prior to being shed has long puzzled biologists because it is unclear what effects anthocyanins may have on leaf function. Here, we provide evidence for red-osier dogwood (Cornus stolonifera) that anthocyanins form a pigment layer in the palisade mesophyll layer that decreases light capture by chloroplasts. Measurements of leaf absorbance demonstrated that red-senescing leaves absorbed more light of blue-green to orange wavelengths (495–644 nm) compared with yellow-senescing leaves. Using chlorophyll a fluorescence measurements, we observed that maximum photosystem II (PSII) photon yield of red-senescing leaves recovered from a high-light stress treatment, whereas yellow-senescing leaves failed to recover after 6 h of dark adaptation, which suggests photo-oxidative damage. Because no differences were observed in light response curves of effective PSII photon yield for redand yellow-senescing leaves, differences between redand yellow-senescing cannot be explained by differences in the capacities for photochemical and non-photochemical light energy dissipation. A role of anthocyanins as screening pigments was explored further by measuring the responses PSII photon yield to blue light, which is preferentially absorbed by anthocyanins, versus red light, which is poorly absorbed. We found that dark-adapted PSII photon yield of red-senescing leaves recovered rapidly following illumination with blue light. However, red light induced a similar, prolonged decrease in PSII photon yield in both redand yellow-senescing leaves. We suggest that optical masking of chlorophyll by anthocyanins reduces risk of photo-oxidative damage to leaf cells as they senesce, which otherwise may lower the efficiency of nutrient retrieval from senescing autumn leaves.
On‐road vehicle detection and tracking based on road context and the ambient lighting adaptive framework

Despite recent active research on vision‐based vehicle detection and tracking, its lack of flexibility hindered practical use in real environments. To be practical, adaptation to various illumination conditions is an essential ingredient. We propose a novel adaptation framework that can improve on this current lighting adaptation using a simple road context, feature arbiter, and a proper feature fusion scheme. In real driving environments, self‐supervised online learning can efficiently segment the road and nonroad regions in front of the host vehicle. Classification into these regions is very important to generate regions of interest (ROIs) for potential vehicle position, that is, road context. It improves on system efficiency by reducing noise and processing time. In our global and local lighting models, the feature arbiter selects an appropriate daytime or nighttime detector for each ROI. And finally, an adaptive fusion framework method can robustly track by selecting or removing the distinctive visual attributes. This system was successfully tested on real road data obtained with various ambient lighting conditions. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 283–295, 2008
Linking the Effects of ERP to Organizational Performance: Development and Initial Validation of an Evaluation Method

The present study proposes and tests an adaptable method to evaluate the contribution of an ERP system to organizational performance. Using a process-based approach, the method was developed from a review of the IS evaluation literature, and then validated and refined through an in-depth case study of a manufacturing firm. Its originality lies in the fact that the whole range of performance indicators actually used by managers are integrated in the evaluation of the system.
Scalable Stealth Mode P2P Overlays of Very Small Constant Degree

P2P technology has recently been adopted by Internet-based malware as a fault tolerant and scalable communication medium. Due to its decentralized and self-organizing nature, P2P malware is harder to detect and block, especially if it utilizes specialized techniques for hiding. We analyze a number of hiding strategies through extensive and realistic simulations over a model of the AS-level Internet topology. We show that the most effective strategy to avoid detection is to drastically reduce the maximal number of peers a node communicates with. While overlay networks of a small constant maximal degree are generally considered to be unscalable, we argue that it is possible to design them to be scalable, efficient, and robust. An important implication is that stealth mode P2P malware that is very difficult to discover with state-of-the-art methods is a plausible threat. We discuss algorithms and theoretical results that support the scalability of stealth mode overlays, and we present realistic event-based simulations of a proof-of-concept system. Besides the context of P2P malware, some of our results are of general interest in the area of constant degree overlays in connection with the problem of how to maintain reasonable performance and reliability with the smallest degree possible.
Evaluación psicométrica de un instrumento para la medición de variables asociadas al consumo electrónico en el contexto venezolano

The purpose of this research was statistical test (validity and reliability) of Electronic Consumption Questionnaire, this included following subscales: Perceived Usefulness, Computational Self-efficacy, Consumption Intention, Electronic Consumption, were adapted from Garcia’s model (2007a & 2007b), and make suggest to adapt it a Venezuela context. 214 students answered the questionnaire. The new instrument was named IVACE (Variables associated with Electronic Consumption Inventory), psychometric analysis resulted high reliability level (∝≥ 0.80). Factors analysis showed Consumption Intention and Electronic Consumption scales had a single dimension, the others scales, Perceived Usefulness and Computational Self-efficacy have two dimensions each.
Left-to-Right Hierarchical Phrase-based Machine Translation

Hierarchical phrase-based translation (Hiero for short) models statistical machine translation (SMT) using a lexicalized synchronous context-free grammar (SCFG) extracted from word aligned bitexts. The standard decoding algorithm for Hiero uses a CKY-style dynamic programming algorithm with time complexity O(n3) for source input with n words. Scoring target language strings using a language model in CKY-style decoding requires two histories per hypothesis making it significantly slower than phrase-based translation which only keeps one history per hypothesis. In addition, the size of a Hiero SCFG grammar is typically much larger than phrase-based models when extracted from the same data which also slows down decoding. In this thesis we address these issues in Hiero by adopting a new translation model and decoding algorithm called Left-to-Right hierarchical phrase-based translation (LR-Hiero for short). LR-Hiero uses a constrained form of lexicalized SCFG rules to encode translation, where the target-side is constrained to be prefix-lexicalized. LRHiero uses a decoding algorithm with time complexity O(n2) that generates the target language output in left-to-right manner which keeps only one history per hypothesis resulting in faster decoding for Hiero grammars. The thesis contains the following contributions: • We propose a novel dynamic programming algorithm for the rule extraction phase. Unlike traditional Hiero rule extraction which performs a brute-force search, LR-Hiero rule extraction is linear in the number of rules. • We propose an augmented version of LR-decoding algorithm previously proposed by Watanabe et al. [90]. Our modified LR-decoding algorithm addresses issues related to decoding time and translation quality and is shown to be more efficient than the CKY decoding algorithm in our experimental results. • We extend our LR-decoding algorithm to capture all hierarchical phrasal alignments that are reachable in CKY-style decoding algorithms. • We introduce a lexicalized reordering model to LR-Hiero that significantly improves the translation quality.
Children's Knowledge, Expectation, and Long-term Retention

To examine the influence of prior knowledge on children's immediate and delayed recall of the details of a physical examination, 4- and 6-year-olds received a specially constructed check-up that included some typical, expected medical features (e.g. listening to the heart), while omitting others, and incorporated several atypical, unexpected procedures (e.g. measuring head circumference). Using a combination of open-ended and more specific probes, the children were assessed for their recall of expected and unexpected features that had been included in or omitted from the examination. Expectation based on prior knowledge affected three aspects of performance. First, correct recall of typical features that had been experienced exceeded that of unexpected features. Second, after a 12-week delay, spontaneous incorrect recall of expected-but-omitted features was considerable, with 42% of 4-year-olds and 72% of 6-year-olds making at least one intrusion, and essentially zero for atypical procedures that were unexpected and omitted. Third, when questioned directly about medical procedures not included in the examination, correct denials were high for atypical features, but at chance levels for those that were expected. The positive and negative influences of knowledge raise questions about children's abilities to differentiate clearly between experience and expectation and have implications for understanding their testimony.
The Impact of Exchange Rate Movements on Dumping Activity : Theory and Evidence

This paper develops a real options model to investigate the relationship between exchange rate movements and the occurrence of price dumping. Our results reveal that the effect of exchange rate volatility on the probability of dumping occurrence is ambiguous, depending on the level of exchange rate. The appreciation of the importing country’s currency tends to have a positive impact on the probability of dumping occurrence if the exchange rate level is not too high. However, if the exchange rate level is unusually high, this relationship might lessen or even reverse. By contrast, exchange rate volatility tends to be positively related to the probability of dumping occurrence if the exchange rate level is high or low enough. Otherwise, its positive relationship might weaken. The number of antidumping cases filed from 1980 to 2005 by U.S. firms is used to test the validity of our theoretical results. Our empirical evidence is consistent with the theory. These results suggest that it is essential to take into account the possible asymmetry in investigating the relationship between exchange rate movements and dumping activities. JEL Classification: F13, F31, G13
Teachers' and Students' Cognitional Knowledge for Classroom Teaching and Learning

An emerging image of the teacher as “thoughtful professional” suggests the need for researchers to study teachers’ and students’ cognitions in addition to teacher behavior, student behavior, and student achievement. This article presents an initial conceptualization of how teachers' and students' cognitions and knowledge mediate effective teaching. Subject matter content and teacher and student knowledge are focused on as important dimensions that have often been ignored by researchers on teaching. Students' “cognitional knowledge for classroom learning,” both general and content-specific, is defined as knowledge of the mental processes by which learners acquire knowledge through classroom learning. Teachers’ relevant knowledge includes both the above cognitional knowledge for classroom learning as well as “cognitional knowledge for classroom teaching. ” Examples from research are provided to illustrate teachers' and students' cognitional and metacognitional knowledge for classroom learning and teaching. The conceptualization and examples may serve to stimulate reflection and research by those who study teaching.
Calcium homeostasis in 40 adolescents with beta-thalassemia major: a case-control study of the effects of intramuscular injection of a megadose of cholecalciferol.

UNLABELLED The prevalence of disturbed calcium homeostasis in adolescents with beta thalassemia major (T) varies among different populations. Moreover, the cholecalciferol uptake required to achieve or maintain any given serum 25-hydroxycholecalciferol level is not well known, particularly within ranges of the probable physiologic supply of the vitamin. OBJECTIVES The objectives of the study were to estimate the prevalence of abnormal calcium homeostasis in 40 adolescent thalassemic patients, and to investigate the effect of an IM injection of a mega dose of vitamin D3 on serum 25-hydroxycholecalciferol (25-OH D) concentration and other calcium homeostasis parameters in vitamin D deficient (VDD) thalassemic adolescents, and to compare these results with those for non-thalassemic adolescents with VDD. DESIGN In this prospective study we measured parameters of calcium homeostasis in 40 adolescents with T and 40 matched non-thalassemic (NT) controls. An IM dose (10,000 IU/kg, max 600,000 IU) of cholecalciferol was injected in those with VDD (38 adolescents with thalassemia and 26 non-thalassemic adolescents). Parameters of calcium homeostasis were measured at intervals of 3 months during the course of the study. RESULTS Of the 40 adolescents with T, 2 had hypoparathyroidism and low 25-OH D, and 2 had hypocalcemia with hypophosphatemia, high alkaline phosphatase (ALP), high PTH and serum 25-OH D below ng/ml. The rest of the patients (n=36) had low circulating 25-OH D concentrations with normal serum Ca and PO4 concentrations. Of the 40 non-thalassemic adolescents, 26 had 25-OH D levels below 20 ng/ml (65%). Patients with T and VDD had lower circulating PTH and ALP concentrations compared to non-thalassemic patients with VDD. Significant improvement of symptoms related to vitamin D deficiency was reported in 18 out of 26 of symptomatic T and 12 out of 16 of NT adolescents at 1 to 3 months after the injection. Three months after injecting vitamin D the mean serum 25-OH D concentration was lower in the T group as compared to the NT group but the majority of patients had 25-OH D levels equal to or greater than 20 ng/ml. CONCLUSION Vitamin D deficiency was detected in 100 % of our thalassemic adolescents. An IM injection of a mega dose of cholecalciferol is an effective therapy for treatment of hypovitaminosis D in thalassemic and non-thalassemic adolescents for 3 months but its effects do not persist for 6 months.
Blind separation of a dynamic image source from superimposed reflections

Blind source separation (BSS) has been successfully applied in separation of static images from reflections superimposed on the desired image by a semi-reflective medium. In our previous study [1], we have shown simulation results for the separation of dynamic reflections. Here we further discuss this problem and show results of experimental data for separation of dynamic images. We also illustrate an application concerned with recovery of images acquired through a semi-transparent cloudy medium. This is a more complex problem in that the mixtures are not stationary in space, the mixing coefficients vary in the presence of clouds, and the mixtures involve also multiplicative and convolutive components. We apply the three-dimensional spatio-temporal Sparse ICA (SPICA) method on simulations of linearly mixed moving landscape, contaminated by the interference of clouds. We then incorporate a nonlinear multiplicative interaction and examine its effects on the SNR of the recovered image. We illustrate preliminary promising results.
Performance of an MEG adaptive-beamformer technique in the presence of correlated neural activities: effects on signal intensity and time-course estimates

The influence of temporarily correlated source activities on neuromagnetic reconstruction by adaptive beamformer techniques was investigated. It is known that the spatial filter weight of an adaptive beamformer cannot perfectly block correlated signals. This causes two major influences on the reconstruction results: time course distortions and reductions in reconstructed signal intensities. Our theoretical analysis and numerical experiments both showed that the reduction in signal intensity for sources with a medium degree of correlation is small. The time-course distortion for such sources, however, may be discernible. Our analysis also showed that the magnitude correlation coefficient between two correlated sources can be accurately estimated by using the beamformer outputs. A method of retrieving the original time courses using estimated correlation coefficients was developed. Our numerical experiments demonstrated that reasonably accurate time courses can be retrieved from considerably distorted time courses even when the signal-to-noise ratio is low.
BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches

With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typically, predictors based on machine learning techniques contain three main steps: feature extraction, predictor construction and performance evaluation. Although several Web servers and stand-alone tools have been developed to facilitate the biological sequence analysis, they only focus on individual step. In this regard, in this study a powerful Web server called BioSeq-Analysis (http://bioinformatics.hitsz.edu.cn/BioSeq-Analysis/) has been proposed to automatically complete the three main steps for constructing a predictor. The user only needs to upload the benchmark data set. BioSeq-Analysis can generate the optimized predictor based on the benchmark data set, and the performance measures can be reported as well. Furthermore, to maximize user's convenience, its stand-alone program was also released, which can be downloaded from http://bioinformatics.hitsz. edu.cn/BioSeq-Analysis/download/, and can be directly run on Windows, Linux and UNIX. Applied to three sequence analysis tasks, experimental results showed that the predictors generated by BioSeq-Analysis even outperformed some state-of-the-art methods. It is anticipated that BioSeq-Analysis will become a useful tool for biological sequence analysis.
An enzymatically inactivated hemoglobinase from Necator americanus induces neutralizing antibodies against multiple hookworm species and protects dogs against heterologous hookworm infection

Hookworms digest hemoglobin from erythrocytes via a proteolytic cascade that begins with the aspartic protease, APR‐1. Ac‐APR‐1 from the dog hookworm, Ancylostoma caninum, protects dogs against hookworm infection via antibodies that neutralize enzymatic activity and interrupt blood‐feeding. Toward developing a human hookworm vaccine, we expressed both wild‐type (Na‐APR‐1wt) and mutant (Na‐APR‐1mut—mutagenesis of the catalytic aspartic acids) forms of Na‐APR‐1 from the human hookworm, Necator americanus. Refolded Na‐APR‐1wt was catalytically active, and Na‐APR‐1mut was catalytically inactive but still bound substrates. Vaccination of canines with Na‐APR‐1mut and heterologous challenge with A. caninum resulted in significantly reduced parasite egg burdens (P=0.034) and weight loss (P=0.022). Vaccinated dogs also had less gut pathology, fewer adult worms, and reduced blood loss compared to controls but these did not reach statistical significance. Vaccination with Na‐APR‐1mut induced antibodies that bound the native enzyme in the parasite gut and neutralized enzymatic activity of Na‐APR‐1wt and APR‐1 orthologues from three other hookworm species that infect humans. IgG1 against Na‐APR‐1mut was the most prominently detected antibody in sera from people resident in high‐transmission areas for N. americanus, indicating that natural boosting may occur in exposed humans. Na‐APR‐1mut is now a lead antigen for the development of an antihematophagy vaccine for human hookworm disease. —Pearson, M. S. , Bethony, J. M. , Pickering, D. A. , de Oliveira, L. M. , Jariwala, A. , Santiago, H. , Miles, A. P., Zhan, B. , Jiang, D. , Ranjit, N. , Mulvenna, J., Tribolet, L. , Plieskatt, J., Smith, T. , Bottazzi, M. E. , Jones, K. , Keegan, B. , Hotez, P. J., Loukas, A. An enzymatically inactivated hemoglobinase from Necator americanus induces neutralizing antibodies against multiple hookworm species and protects dogs against heterologous hookworm infection. FASEB J. 23, 3007–3019 (2009). www.fasebj. org
Why did principals and teachers respond differently to curriculum reform?

This article presents the finding of an interim evaluation survey commissioned by the Education Bureau of Hong Kong on the effectiveness of the curriculum reform initiated in 2001. Drawing upon change theories for analysis of the study, the article examines the perceptions of both principals and teachers on the effectiveness of short‐term curriculum development in schools from 2001 to 2006 through self‐administered questionnaire survey as well as focus group interviews. The quantitative survey shows that evaluations from principals were more positive than those of frontline teachers in many aspects of the reform. Data collected from focus group interviews help explain the discrepancy in attitudes of these two stakeholder groups towards the reform. Insufficient knowledge, lack of support and consensus, and top‐down initiation of the reform are the reasons accounting for the different responses to the reform. Strengthening professional development programs and developing a culture of collegiality and collaboration are the strategies recommended to improve the implementation of the curriculum reform in the medium‐term phase (2007–2011).