Miracle-dz/UniFAR-FTUs huggingface dataset:
Annotation and Classification of Light Verbs and Light Verb Variations in Mandarin Chinese

Light verbs pose an a challenge in linguistics because of its syntactic and semantic versatility and its unique distribution different from regular verbs with higher semantic content and selectional resrictions. Due to its light grammatical content, earlier natural language processing studies typically put light verbs in a stop word list and ignore them. Recently, however, classification and identification of light verbs and light verb construction have become a focus of study in computational linguistics, especially in the context of multi-word expression, information retrieval, disambiguation, and parsing. Past linguistic and computational studies on light verbs had very different foci. Linguistic studies tend to focus on the status of light verbs and its various selectional constraints. While NLP studies have focused on light verbs in the context of either a multi-word expression (MWE) or a construction to be identified, classified, or translated, trying to overcome the apparent poverty of semantic content of light verbs. There has been nearly no work attempting to bridge these two lines of research. This paper takes this challenge by proposing a corpus-bases study which classifies and captures syntactic-semantic difference among all light verbs. In this study, we first incorporate results from past linguistic studies to create annotated light verb corpora with syntactic-semantics features. We next adopt a statistic method for automatic identification of light verbs based on this annotated corpora. Our results show that a language resource based methodology optimally incorporating linguistic information can resolve challenges posed by light verbs in NLP.
NFκB and AP-1 Drive Human Myometrial IL8 Expression

The uterine expression of the chemokine IL8 increases dramatically with the onset of labour both at term and preterm. The IL8 promoter contains binding sites for the transcription factors nuclear factor-kappa B (NFκB), activator protein-1 (AP-1), and CCAAT/enhancer-binding protein (CEBP). In this study we investigated the roles of these transcription factors in IL1B regulation of the IL8 gene in human myometrium. Using chromatin immune precipitation (ChIP) assay, we showed that each of NFκB, CEBP, and AP-1 binds to the IL8 promoter upon IL1B stimulation. To examine the relative importance of each site in IL8 gene expression, site-directed mutagenesis of each of these sites was performed. We found that the NFκB site was essential for basal and IL1B-stimulated gene expression. Mutation of the AP-1 site reduced both basal and IL1B-stimulated expression but to a lesser extent. Mutation of the CEBP site had no effect upon basal expression but eliminated the IL1B response. Small interfering RNA (siRNA) silencing of NFκB abolished the IL8 response to IL1B significantly; siRNA against AP-1 reduced it to a lesser extent whilst knockdown of CEBP enhanced the response. Our data confirms a central and essential role for NFκB in regulation of IL8 in human myometrium.
Purification and Properties of Polygalacturonase Produced by Thermophilic Fungus Thermoascus aurantiacus CBMAI-756 on Solid-State Fermentation

Polygalacturonases are enzymes involved in the degradation of pectic substances, being extensively used in food industries, textile processing, degumming of plant rough fibres, and treatment of pectic wastewaters. Polygalacturonase (PG) production by thermophilic fungus Thermoascus aurantiacus on solid-state fermentation was carried out in culture media containing sugar cane bagasse and orange bagasse in proportions of 30% and 70% (w/w) at 45°C for 4 days. PG obtained was purified by gel filtration and ion-exchange chromatography. The highest activity was found between pH 4.5 and 5.5, and the enzyme preserved more than 80% of its activity at pH values between 5.0 and 6.5. At pH values between 3.0 and 4.5, PG retained about 73% of the original activity, whereas at pH 10.0 it remained around 44%. The optimum temperature was 60–65°C. The enzyme was completely stable when incubated for 1 hour at 50°C. At 55°C and 60°C, the activity decreased 55% and 90%, respectively. The apparent molecular weight was 29.3 kDa, K m of 1.58 mg/mL and V max of 1553.1 μmol/min/mg. The presence of Zn+2, Mn+2, and Hg+2 inhibited 59%, 77%, and 100% of enzyme activity, respectively. The hydrolysis product suggests that polygalacturonase was shown to be an endo/exoenzyme.
B Cells Promote Tumor Progression via STAT3 Regulated-Angiogenesis

The role of B cells in cancer and the underlying mechanisms remain to be further explored. Here, we show that tumor-associated B cells with activated STAT3 contribute to tumor development by promoting tumor angiogenesis. B cells with or without Stat3 have opposite effects on tumor growth and tumor angiogenesis in both B16 melanoma and Lewis Lung Cancer mouse models. Ex vivo angiogenesis assays show that B cell-mediated tumor angiogenesis is mainly dependent on the induction of pro-angiogenic gene expression, which requires Stat3 signaling in B cells. Furthermore, B cells with activated STAT3 are mainly found in or near tumor vasculature and correlate significantly with overall STAT3 activity in human tumors. Moreover, the density of B cells in human tumor tissues correlates significantly with expression levels of several STAT3-downstream pro-angiogenic genes, as well as the degree of tumor angiogenesis. Together, these findings define a novel role of B cells in promoting tumor progression through angiogenesis and identify STAT3 in B cells as potential therapeutic target for anti-angiogenesis therapy.
Morphological Characteristics of Electrophysiologically Characterized Layer Vb Pyramidal Cells in Rat Barrel Cortex

Layer Vb pyramidal cells are the major output neurons of the neocortex and transmit the outcome of cortical columnar signal processing to distant target areas. At the same time they contribute to local tactile information processing by emitting recurrent axonal collaterals into the columnar microcircuitry. It is, however, not known how exactly the two types of pyramidal cells, called slender-tufted and thick-tufted, contribute to the local circuitry. Here, we investigated in the rat barrel cortex the detailed quantitative morphology of biocytin-filled layer Vb pyramidal cells in vitro, which were characterized for their intrinsic electrophysiology with special emphasis on their action potential firing pattern. Since we stained the same slices for cytochrome oxidase, we could also perform layer- and column-related analyses. Our results suggest that in layer Vb the unambiguous action potential firing patterns "regular spiking (RS)" and "repetitive burst spiking (RB)" (previously called intrinsically burst spiking) correlate well with a distinct morphology. RS pyramidal cells are somatodendritically of the slender-tufted type and possess numerous local intralaminar and intracolumnar axonal collaterals, mostly reaching layer I. By contrast, their transcolumnar projections are less well developed. The RB pyramidal cells are somatodendritically of the thick-tufted type and show only relatively sparse local axonal collaterals, which are preferentially emitted as long horizontal or oblique infragranular collaterals. However, contrary to many previous slice studies, a substantial number of these neurons also showed axonal collaterals reaching layer I. Thus, electrophysiologically defined pyramidal cells of layer Vb show an input and output pattern which suggests RS cells to be more "locally segregating" signal processors whereas RB cells seem to act more on a "global integrative" scale.
Performance of Propensity Score Methods in the Presence of Heterogeneous Treatment Effects

Title of dissertation: PERFORMANCE OF PROPENSITY SCORE METHODS IN THE PRESENCE OF HETEROGENEOUS TREATMENT EFFECTS Kathleen M. Stepien, Doctor of Philosophy, 2016 Dissertation directed by: Laura M. Stapleton, Associate Professor Department of Human Development and Quantitative Methodology; Measurement, Statistics and Evaluation Program Estimating an average treatment effect assumes that individuals and groups are homogeneous in their responses to a treatment or intervention. However, treatment effects are often heterogeneous. Selecting the most effective treatment, generalizing causal effect estimates to a population, and identifying subgroups for which a treatment is effective or harmful are factors that motivate the study of heterogeneous treatment effects. In observational studies, treatment effects are often estimated using propensity score methods. This dissertation adds to the literature on the analysis of heterogeneous treatment effects using propensity score methods. Three propensity score methods were compared using Monte Carlo simulation: single propensity score with exact matching on subgroup, matching using group propensity scores, and multinomial propensity scores using generalized boosted modeling. Methods were evaluated under various group distributions, sample sizes, effect sizes, and selection models. An empirical analysis using data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K) is included to demonstrate the methods studied. Simulation results showed that estimating group propensity scores provided the smallest MSE, MNPS performance was comparable to GBM, and including the group indicator in the propensity score model improved treatment effect estimates regardless of whether group membership influenced selection. In addition, subclassification performed poorly when one group was more prevalent in the extremes of the propensity score distribution. PERFORMANCE OF PROPENSITY SCORE METHODS IN THE PRESENCE OF HETEROGENEOUS TREATMENT EFFECTS by
Language Technology Support for Semantic Annotation of Icono-graphic Descriptions

The paper describes an approach for semantic annotation of multimedia objects implemented for the purposes of SINUS Project 1 . Semantic annotations are supported by semantic annotation models based on ontological presentation of knowledge concerning Bulgarian Icono-graphy. The process of semantic annotation includes automated data-lifting procedure and user-directed approach. The paper pays attention to a specific variant of the semantic annotation process directed by the user - application of Language Technologies for semi-auto-mated creation of semantic text annotations (tags) based on analysis of descriptive texts. The ‘ontology-to-text’ approach has been adapted to the needs of the iconographic domain. Initial experiments are established to support the user during the process of manual semantic annotations in the context of SINUS environment.
THE IMPACT OF DRUGSTORE MAKEUP PRODUCT REVIEWS BY BEAUTY VLOGGER ON YOUTUBE TOWARDS PURCHASE INTENTION BY UNDERGRADUATE STUDENTS IN INDONESIA

In this era, digital platforms play a very significant role in influencing consumer preference and attitude. Content creators on digital platforms such as YouTube are becoming aspirational figures that have strong influence in the minds of the consumers. This paper is aimed to determine the impact of drugstore makeup product reviews by beauty vloggers on YouTube towards purchase intention by undergraduate students in Indonesia. In order to determine the factors that influence purchase intention, the variables of Source Credibility Model (Ohanian, 1990) were used. The Source Credibility Model was also projected as a mean to evaluate the factors of quality that was delivered by the beauty vloggers on their videos. Moreover, the dimensions of Trustworthiness, Expertise and Attractiveness from Source Credibility Model are projected into overall consumer attitude in order to determine the impact towards purchase intention. The author had gathered primary data in the form of online questionnaires as well as secondary data resources including journals, books, and articles. Furthermore, quantitative research methods were used in order to examine the respondent’s knowledge and preference. The result indicates that the dimensions of Source Credibility Model in most extent had significantly influenced purchase intention through the videos that was presented by the beauty vloggers on YouTube. In the end, this research would contribute to academic and practical sector in exploring the impact of digital platforms towards consumer preference and attitude. Other than that, this research would also encourage cosmetics brands to realize the importance of content creators and digital platforms and imply them as a new way of marketing. Keywords: Cosmetics, Beauty Vlogger, Purchase Intention, Consumer Attitude
Impact of speciation on removal of manganese and organic matter by nanofiltration

The removal of manganese and humic acid (HA) by two nanofiltration membranes, TFC-SR2 and TFC-SR3, was investigated in order to highlight the influence of speciation on manganese and HA retention. Manganese speciation and complexation with HA were modelled to understand how speciation could affect NF removal mechanisms. The behaviour of the two membranes was dramatically different in terms of manganese retention. Manganese retention for TFC-SR3 was higher and dominated by size exclusion. Manganese retention for TFC-SR2 varied with pH. At pH 7 (i.e. the pH of most natural waters) manganese retention for TFC-SR2 was about 45% versus 90% for TFC-SR3, with fluxes of about 75 and 25 l m−2 h−1, respectively. Both membranes showed very high retention of HA (about 80%); therefore they are suitable for surface waters where no salt removal is required. Manganese deposit on both membranes was generally low (<10%), but increased at pH 10 and 12 as manganese deposited as precipitated MnCO3, and the membranes showed a yellow-brownish layer.
Associations Between Reading Skills, Interest in Reading, and Teaching Practices in First Grade

ABSTRACT This study examined associations between classroom-level reading fluency, comprehension, interest in reading, and teaching practices. Participants were 466 children from 21 classrooms. Reading fluency and interest were assessed at the beginning and end of Grade 1, reading comprehension at the end of Grade 1. Teaching practices were observed with the Early Childhood Classroom Observation Measure (ECCOM). Teachers were more likely to use teacher-directed methods in classrooms where children had poorer initial reading fluency. In classrooms with mostly child-centered methods, children showed better reading fluency, comprehension, and higher interest, whereas in classrooms with predominately teacher-directed practices, children had lower reading comprehension at the end of Grade 1. Findings highlight the need for teacher education programs to incorporate discussions about the benefits and disadvantages of different teaching methods.
The Impact of Initial Systemic Inflammatory Response After Aneurysmal Subarachnoid Hemorrhage.

AIM To assess the association between inflammatory response and early brain injury (EBI), and the association between inflammatory response and the following pneumonia after aneurysmal subarachnoid hemorrhage (SAH). MATERIAL AND METHODS Eighty-nine patients with spontaneous SAH and 12 patients with unruptured aneurysm were included in this prospective study. The systemic inflammatory biomarkers such as C-reactive protein (CRP), IL-1? , IL-2,IL-6,IL-8, IL10 and T leukocyte subsets were measured within 24 hours after admission. Their clinical features and laboratory findings were clearly reviewed and univariate analysis was used to find the main predictors. RESULTS The levels of serum inflammatory cytokines especially IL-6 (p=0.004) and CRP (p=0.014) would significantly increase after aneurysm SAH. Higher Fisher grades on admission result in higher levels of IL-6 and IL-10 (pIL-6=0.003. pIL-10=0.002), and higher levels of IL-6, IL-10 and CRP were significantly associated with severe EBI, and increased the susceptibility to pneumonia (p < 0.05). The counts of CD3+ T Cells would decrease after aneurysm rupture (p=0.001), especially in patients with a poor initial clinical grade. A reversed correlation between IL-6 level and CD3 T cells count was revealed in this study (p=0.014,r=-0.249); a lower CD4 T-Cells counts might lead to subsequent pneumonia after SAH (p=0.041). The levels of serum inflammatory cytokines were not different between aneurysmal and non-aneurysmal SAH. CONCLUSION Systemic inflammatory response would be activated after aneurysm rupture; a similar systemic inflammatory response would be noticed in non-aneurysmal SAH. The degree of inflammatory response could reflect the severity of EBI, and excessive inflammatory response could also aggravate EBI, induce immunodepression and increase the susceptibility to infections. Inflammatory cytokines such as IL-6, IL-10 and CRP are important predictors.
Integration of Two Skeptical Emotion Theories: Dimensional Appraisal Theory and Russell's Psychological Construction Theory

ABSTRACT This inquiry attempts to integrate two skeptical emotion theories: dimensional appraisal theory and Russell's (2003) psychological construction theory. To bring out the skeptical elements of these theories, I compare them first with two classic theories: affect program theory and discrete appraisal theory. The skeptical theories are similar to each other in that they replace the concept of emotion with the concept of emotional episode, and that they organize the variety within the set of emotional episodes according to dimensions instead of vernacular emotion subsets. Their differences concern the strength of the relations among the components in emotional episodes and the scientific status of the set of emotional episodes. To make an informed decision about the elements to keep and to revise from both theories, I engage in a separate analysis of the behavior-related components and the experience component, guided by insights from general behavior theories and general theories of consciousness. The analysis of the behavior-related components suggests the relatively uncharted idea that the so-called emotional aspect of behavior can be caused by a goal-directed mechanism. The analysis of the experience component reveals that different theories have emphasized different aspects of experience and hence different paths toward experience. The inquiry ends with an integrated theory that rejects the scientific status of emotions or emotional episodes, but accepts the scientific status of the components and sees strong causal relations among them.
Forecasting and Trading Currency Volatility: An Application of Recurrent Neural Regression and Model Combination

In this paper, we examine the use of non-parametric Neural Network Regression (NNR) and Recurrent Neural Network (RNN) regression models for forecasting and trading currency volatility, with an application to the GBP/USD and USD/JPY exchange rates. Both the results of the NNR and RNN models are benchmarked against the simpler GARCH alternative and implied volatility. Two simple model combinations are also analysed. The intuitively appealing idea of developing a nonlinear nonparametric approach to forecast FX volatility, identify mispriced options and subsequently develop a trading strategy based upon this process is implemented for the first time on a comprehensive basis. Using daily data from December 1993 through April 1999, we develop alternative FX volatility forecasting models. These models are then tested out-of-sample over the period April 1999–May 2000, not only in terms of forecasting accuracy, but also in terms of trading efficiency: in order to do so, we apply a realistic volatility trading strategy using FX option straddles once mispriced options have been identified. Allowing for transaction costs, most trading strategies retained produce positive returns. RNN models appear as the best single modelling approach yet, somewhat surprisingly, model combination which has the best overall performance in terms of forecasting accuracy, fails to improve the RNN-based volatility trading results. Another conclusion from our results is that, for the period and currencies considered, the currency option market was inefficient and/or the pricing formulae applied by market participants were inadequate. Copyright © 2002 John Wiley & Sons, Ltd.
Analytical Validation of a Highly Quantitative, Sensitive, Accurate, and Reproducible Assay (HERmark®) for the Measurement of HER2 Total Protein and HER2 Homodimers in FFPE Breast Cancer Tumor Specimens

We report here the results of the analytical validation of assays that measure HER2 total protein (H2T) and HER2 homodimer (H2D) expression in Formalin Fixed Paraffin Embedded (FFPE) breast cancer tumors as well as cell line controls. The assays are based on the VeraTag technology platform and are commercially available through a central CAP-accredited clinical reference laboratory. The accuracy of H2T measurements spans a broad dynamic range (2-3 logs) as evaluated by comparison with cross-validating technologies. The measurement of H2T expression demonstrates a sensitivity that is approximately 7–10 times greater than conventional immunohistochemistry (IHC) (HercepTest). The HERmark assay is a quantitative assay that sensitively and reproducibly measures continuous H2T and H2D protein expression levels and therefore may have the potential to stratify patients more accurately with respect to response to HER2-targeted therapies than current methods which rely on semiquantitative protein measurements (IHC) or on indirect assessments of gene amplification (FISH).
How Do Need, Capacity, Geography, and Politics Influence Giving?

In this chapter we seek to shed light on the question: “What are the types of factors that influence individual giving? ” In recent years there has been a sustained effort, in and out of academia, to address this question. While we have learned a number of things, large areas have yet to be explored. For example, almost all work has been done on the impact on giving of individual factors, such as education, gender, race, income, and so on. While these are clearly relevant, it is important to remember that people are also embedded in larger contexts. So, while their personal income will definitely influence their level of giving, the wealth or poverty (measured by average income) of their city might also have a significant effect on how much they give overall and to certain causes. Based on the aforementioned, it is our belief that in order to understand the totality of influences on individual giving, we need to include the impact of economic, political, and sociocultural environments, or macrofactors, as well as personal factors. It is also important for nonprofit managers, policymakers, and community leaders to be aware of the influence of these macrofactors. It may help to explain why people who have similar personal characteristics but who live in different contextual circumstances may have different levels of giving. What’s more, these larger factors change over time, either through planned efforts or for other reasons. Knowing what impacts on giving these factors have will make possible predictions of what these changes are likely to mean for giving levels. Including macrofactors in social research, however, introduces a number of complications. In the first place, there are measurement errors at both the