Miracle-dz/UniFAR-FTUs huggingface dataset:
Personal goals and academic achievement among theology students

Studying in higher education requires long‐term commitment. Previous studies have shown that commitment, perceived competence, intrinsic motivation and work‐life orientation are positively related to academic achievement. This study examines the kinds of goals theology students have at the beginning of studies, and whether these goals are related to academic achievement during their first three years at university. Personal project analysis was used to acquire information about first‐year students’ study‐related personal goals and related evaluations. The evaluations were factor analysed, and three clusters of students were derived on the basis of the factors: the committed, self‐fulfillers and the non‐committed. The results show that students who perceived progress, were capable and had intrinsic reasons for their goals advanced more rapidly in their studies. The implication is that variation in academic achievement is at least partly a consequence of variation in orientation towards studying at the beginning of the study period.
Metaphor in (Arabic-into-English)translation with specific reference to metaphorical concepts and expressions in political discourse

Cognitive linguistics scholars argue that metaphor is fundamentally a conceptual process of mapping one domain of experience onto another domain. The study of metaphor in the context of Translation Studies has not, unfortunately, kept pace with the discoveries about the nature and role of metaphor in the cognitive sciences. This study aims primarily to fill part of this gap of knowledge. Specifically, the thesis is an attempt to explore some implications of the conceptual theory of metaphor for translation. Because the study of metaphor in translation is also based on views about the nature of translation, the thesis first presents a general overview of the discipline of Translation Studies, describing the major models of translation. The study (in Chapter Two) then discusses the major traditional theories of metaphor (comparison, substitution and interaction theories) and shows how the ideas of those theories were adopted in specific translation studies of metaphor. After that, the study presents a detailed account of the conceptual theory of metaphor and some hypothetical implications for the study of metaphor in translation from the perspective of cognitive linguistics. The data and methodology are presented in Chapter Four. A novel classification of conceptual metaphor is presented which distinguishes between different source domains of conceptual metaphors: physical, human-life and intertextual. It is suggested that each source domain places different demands on translators. The major sources of the data for this study are (1) the translations done by the Foreign Broadcasting Information Service (FBIS), which is a translation service of the Central Intelligence Agency (CIA) in the United Sates of America, of a number of speeches by the Iraqi president Saddam Hussein during the Gulf Crisis (1990-1991) and (2) official (governmental) Omani translations of National Day speeches of Sultan Qaboos bin Said of Oman.
Position and Imposition: Power Relations in a Multicultural Foundations Class.

My students, who are prospective high school teachers, reflect many of the common attitudes held by the larger general population; that is, they tend to be fairly apolitical, individualistic, and nonconfrontational, and most often they view situations and people from a personal point of view. My primary challenge as a White teacher educator is thus to intervene in such a way that my students do not reproduce in their teaching what they have experienced in their schooling. Two of my goals are that students develop the ability to be open and reflective about their learning histories, values, beliefs, and actions on those beliefs; and that they become conscious of the "hidden curriculum" of schooling (Chan & Rueda, 1979). Because I want my students to problematize (critically examine) the puzzling and contradictory aspects of their views of reality as well as their experiences, I strive to help them discover, experience, and construct powerful alternatives to their past experiences. I want them to become aware of the role that they may be asked to play in perpetuating oppressive structures and practices in the educational system and find ways to take an oppositional stance to an oppressive role. In effect, I try to teach my students to challenge the status quo in the hopes that they, as the teachers of the future, will choose to take a stand in the interests of social justice. Translating theory into practice, however, has proven difficult. While I do not assume that all prospective teachers enter teacher education programs with racist and sexist values, I believe that a great majority of them do and that they tend either to be unconscious of this reality or want to deny it. As a teacher I have observed that a critical
Learning Inference Models for Computer Vision

Computer vision can be understood as the ability to perform inference on image data. Breakthroughs in computer vision technology are often marked by advances in inference techniques. This thesis proposes novel inference schemes and demonstrates applications in computer vision. We propose inference techniques for both generative and discriminative vision models. The use of generative models in vision is often hampered by the difficulty of posterior inference. We propose techniques for improving inference in MCMC sampling and message-passing inference. Our inference strategy is to learn separate discriminative models that assist Bayesian inference in a generative model. Experiments on a range of generative models show that the proposed techniques accelerate the inference process and/or converge to better solutions. A main complication in the design of discriminative models is the inclusion of prior knowledge. We concentrate on CNN models and propose a generalization of standard spatial convolutions to bilateral convolutions. We generalize the existing use of bilateral filters and then propose new neural network architectures with learnable bilateral filters, which we call `Bilateral Neural Networks'. Experiments demonstrate the use of the bilateral networks on a wide range of image and video tasks and datasets. In summary, we propose techniques for better inference in several vision models ranging from inverse graphics to freely parameterized neural networks. In generative models, our inference techniques alleviate some of the crucial hurdles in Bayesian posterior inference, paving new ways for the use of model based machine learning in vision. In discriminative CNN models, the proposed filter generalizations aid in the design of new neural network architectures that can handle sparse high-dimensional data as well as provide a way to incorporate prior knowledge into CNNs.
COORDINATE REPRESSION OF THE SYNTHESIS OF FOUR HISTIDINE BIOSYNTHETIC ENZYMES BY HISTIDINE.

Introduction. -In several instances, the rate of synthesis of the enzymes of a biosynthetic pathway appears to be regulated by the size of the pool of the end product of that pathway.1-4 This phenomenon has been called enzyme repression.2 We have observed repression by histidine during the investigation of the histidine biosynthetic enzymes in histidine-requiring mutants of Salmonella typhimurium.6 The cellular concentration of the four histidine biosynthetic enzymes which were examined were increased about 15-fold by limiting the amount of histidine available to a mutant during growth. A simple method for limiting the availability of histidine in the cell during the entire growth period, and thus increasing the enzyme concentrations, was realized by growing histidine-requiring mutants on a derivative of histidine, formylhistidine, as a source of this amino acid. It appeared, therefore, that the normal low level of the biosynthetic enzymes in wild-type cells grown on minimal medium was probably due to the repression by the normal pool of histidine. of most of the cellular capacity for synthesizing these proteins. This investigation is concerned with utilizing the histidine biosynthetic system from Salmonella to answer the following question: Does the histidine repression of enzyme synthesis affect each of the enzymes of the pathway to the same extent, i.e., is there a parallel increase in specific activity of all four enzymes on lowering the internal histidine pool and a constant ratio of the activity of one histidine enzyme to another independent of the concentration of the enzymes in the cell? A secondary point of interest is whether there is any influence of the concentration of the enzyme substrates on the enzyme synthesis control mechanism. The strains used in this study were some of the several hundred histidine-requiring' mutants of Salmonella that have been mapped by Hartman, et al.6' 7 They were able to demonstrate that each of the mutants could be classified into one of the seven genetic loci, E, F, A, B, C, D, and G, which were closely linked on the chromosome in the above sequence. These same mutants were analyzed by us for presence or absence of various enzymes of the histidine biosynthetic pathway. , The genetic data taken in conjunction with the biochemical analysis gave more direct support for Hartman's original suggestion8 that the sequence of the genes in the linkage map corresponds to the sequence of the enzymes they control in the biosynthetic pathway.
Cocaine-induced ‘active immobility’ and its modulation by the serotonin1A receptor

‘Active immobility’ (AI) is an independent behaviour that can be characterized by behavioural immobility, an increased muscular rigidity and the sustaining of an unusual posture. In previous studies with cocaine we observed, concomitant with hyperlocomotion and increased rearing activity, an increase in AI in well-habituated animals, which may constitute another ‘positive’ acute effect of cocaine on behaviour. The contribution of the serotonergic (5-HT) system to AI is well established. However, little information exists about the contribution of particular 5-HT-receptor subtypes. In order to examine a possible role of the 5-HT1A receptor on this effect of cocaine, we systematically re-analysed four previous experiments in well-habituated animals and one in little-habituated animals, focusing on the acute behavioural effects of cocaine on AI. We found that, in well-habituated animals, cocaine at a medium dose (10 mg/kg, i.p.) induces AI behaviour, which, however, does not correlate with cocaine effects on locomotion, rearing or grooming behaviour. However, there was no effect of cocaine (1, 5 or 15 mg/kg, i.p.) on AI in little-habituated animals. The 5-HT1A-receptor antagonist, WAY 100635 [N-{2-(4-2-methoxyphenyl)-1-piperazinyl}ethyl}-N-(2-pyridinyl) cyclohexane carboxamide trihydrochloride] (0.4 mg/kg, i.p.), potentiated cocaine-induced AI in well-habituated animals, while the 5-HT1A-receptor agonist, 8-OH-DPAT (0.2 mg/kg, i.p.), attenuated it. The local application of 8-OH-DPAT [8-hydroxy-2-(di-n-propylamino)tetralin] into the nucleus accumbens (0, 1, 10 μmol/l) or hippocampus (0, 0.1, 1, 10 μmol/l) modulated cocaine-induced AI in a complex way. These results showed that cocaine induces AI at a medium dose in well-habituated but not in little-habituated animals. The cocaine-induced AI in well-habituated animals can be potentiated by systemic 5-HT1A-receptor antagonism and attenuated by 5-HT1A-receptor agonism. Two experiments with local activation of postsynaptic 5-HT1A receptors revealed that both nucleus accumbens and hippocampal 5-HT1A-receptor populations are involved in the expression of cocaine-induced AI.
OCEANS-6 : Character Trait, Age Demographic Analysis and Sexist Speech Detection of Dialogues

Character trait analysis has always been an open-ended problem with many potential applications. In a technologically advanced age where every industry seeks to benefit from artificial intelligence, combining its capacity with NLP offers us a fresh way to gather data on people. The majority of features in the digital world are typically observed based on the user’s interests and other incredibly hard-to-gather information. The authors examine a novel unsupervised graph-based method that can identify useful information about a person’s speech or writing style. The study encompasses three major components: Character Trait Prediction, Age Demographic Analysis, and Sexist Speech Detection. Every person is categorised into one of five character traits (OCEAN - Big Five character traits, which include openness, conscientiousness, extroversion, agreeableness, and neuroticism), with the addition of a sixth dimension: a non-binary sexist speech, making it the OCEANS-6. The proposed algorithm removes the need for expertly labelled data and offers new angles on the character analysis issue. This work offers a multifaceted approach to dialogue analysis, with applications ranging from character trait prediction in literature to age demographic analysis and the detection of sexist speech in social media. The findings contribute to a deeper understanding of character dynamics, linguistic cues, and social discourse in various contexts.
Segmentation in Local Hospital Markets

This study examines evidence of market segmentation on the basis of patients' insurance status, demographic characteristics, and medical condition in selected local markets in California in the years 1983 and 1989. Substantial differences exist in the probability patients may be admitted to particular hospitals based on insurance coverage, particularly Medicaid, and race. Segmentation based on insurance and race is related to hospital characteristics, but not the characteristics of the hospital's community. Medicaid patients are more likely to go to hospitals with lower costs and fewer service offerings. Privately insured patients go to hospitals offering more services, although cost concerns are increasing. Hispanic patients also go to low-cost hospitals, ceteris paribus. Results indicate little evidence of segmentation based on medical condition in either 1983 or 1989, suggesting that “centers of excellence” have yet to play an important role in patient choice of hospital. The authors found that distance matters, and that patients prefer nearby hospitals, moreso for some medical conditions than others, in ways consistent with economic theories of consumer choice.
Adaptive Pointwise Estimation in Time-Inhomogeneous Conditional Heteroscedasticity Models

This paper offers a new method for estimation and forecasting of the volatility of financial time series when the stationarity assumption is violated. Our general, local parametric approach particularly applies to general varying-coefficient parametric models, such as GARCH, whose coefficients may arbitrarily vary with time. Global parametric, smooth transition and change-point models are special cases. The method is based on an adaptive pointwise selection of the largest interval of homogeneity with a given right-end point by a local change-point analysis. We construct locally adaptive estimates that can perform this task and investigate them both from the theoretical point of view and by Monte Carlo simulations. In the particular case of GARCH estimation, the proposed method is applied to stock-index series and is shown to outperform the standard parametric GARCH model.
Automatic Smoothing Spline Projection Pursuit

Abstract A highly flexible nonparametric regression model for predicting a response y given covariates {xk}d k=1 is the projection pursuit regression (PPR) model ŷ = h(x) = β0 + Σjβjfj(αT jx) where the fj , are general smooth functions with mean 0 and norm 1, and Σd k=1α2 kj=1. The standard PPR algorithm of Friedman and Stuetzle (1981) estimates the smooth functions fj using the supersmoother nonparametric scatterplot smoother. Friedman's algorithm constructs a model with M max linear combinations, then prunes back to a simpler model of size M ≤ M max, where M and M max are specified by the user. This article discusses an alternative algorithm in which the smooth functions are estimated using smoothing splines. The direction coefficients αj, the amount of smoothing in each direction, and the number of terms M and M max are determined to optimize a single generalized cross-validation measure.
Vertical dissipation profiles and the photosphere location in thin and slim accretion disks

As several authors in the past, we calculate optically thick but geometrically thin (and slim) accretion disk models and perform a ray-tracing of photons in the Kerr geometry to calculate the observed disk continuum spectra. Previously, it was common practice to ray-trace photons assuming that they are emitted from the Kerr geometry equatorial plane, z = 0. We show that the continuum spectra calculated with this assumption differ from these calculated under the assumption that photons are emitted from the actual surface of the disc, z = H(r). This implies that a knowledge of the location of the thin disk effective photosphere is relevant for calculating the continuum emission. In this paper we investigate, in terms of a simple model, a possible influence of the (unknown, and therefore assumed ad hoc) vertical dissipation profiles on the vertical structure of the disk and thus on the location of the effective photosphere, and on the observed continuum spectra. For disks with moderate and high mass accretion rates ( u m > 0.01 u mC), we find that the photosphere location in the inner, radiation pressure dominated, disk region (where most of the radiation comes from) does not depend on the dissipation profile and therefore emerging disk spectra are insensitive to the choice of the dissipation function. For lower accretion rates, the photosphere location depends on the assumed vertical dissipation profile down to the disk inner edge, but the dependence is very weak and thus of minor importance. We conclude that the continuum spectra of optically thick accretion disks around black holes should be calculated with ray-tracing from the effective photosphere and that, fortunately, the choice of a particular vertical dissipation profile does not substantially influence the calculated emission.
Analysis and Design of Hindi Fake News Detection Model Using Machine Learning

The current society we live in is marked by fast change, which brings with it a variety of obstacles that, when taken together; make it difficult for people to live their lives. The discussion that we are having right now focuses on the single most essential problem, which is fake news. The term “fake news” refers to a kind of propaganda or a problem that may include incorrect information and is often distributed through the media. The word itself comes from the English phrase “fake news. ” This encompasses not just the internet but also more conventional kinds of media, such as television, newspapers, and even smart phones, to name a few examples. In the society we live in today, where there is an abundance of social media networks, a large number of people are seeking to develop and share information, yet the vast majority of it is pointless and has little bearing on real-world issues. This misleading news is the major driving force behind the dissemination of various different political and commercial purposes. Those aims include: It is now becoming more difficult to differentiate between genuine news and actual news as a direct result of the proliferation of the internet world. In an effort to find a solution to the problem of fake news, we have been putting a lot of effort into developing the idea of a “False news detecting system. ” This system integrates a large number of news articles written in Hindi that have been obtained from a wide range of sources.
Hepatitis B Seroprevalence and Risk Factors in Adult Population of Chaharmahal and Bakhtiari Province in 2013

Background: Hepatitis B virus is one of the important viral causes of liver inflammation with high worldwide prevalence and important hepatic and extra hepatic complications. Objectives: The aim of this study was to investigate the prevalence and risk factors of hepatitis B in Chaharmahal and Bakhtiari province, Iran. Patients and Methods: For this descriptive, analytical, population-based study, 3000 participants older than 15 years were enrolled according to the clustering method. After obtaining written informed consent and taking required blood samples, we gathered data on demographic status and probable transmission routes of disease using questionnaire between 2012 and 2013. The data was analyzed using SPSS software (descriptive parameters and chi-square). P value below 0.05 was considered as statistically significant. Results: The mean age of participants was 38.4 ± 16.3. The seroprevalence rate of hepatitis B was found to be 1.3% (95% CI, 0.95%-1.81%). Prevalence of HBeAg among HBsAg positive participants was 2.5% (only 1 of 40). Seroprevalence was higher in male group (2.5 times higher than women), age group of over 55 years, farmers, and non-public occupations. Positive seroprevalence was associated with a history of renal disease, familial transmission, transfusion, surgery in hospital, circumcision, contact with hepatitis B infected individuals, imprisonment, intravenous (IV) drug abuse, and smoking (P < 0.05). Nevertheless, the highest odds ratio (OR) was obtained for history of renal disease (OR = 7.64: 3.01-18.4), followed by imprisonment (OR = 5.4: 1.86 -15.7) and IV drug abuse (OR = 5.68: 1.3-24.7). Conclusions: Chaharmahal and Bakhtiari province could be categorized as a low endemic region for hepatitis B infection, with a seroprevalence similar to that in other provinces of western Iran. Vaccination seems to influence its decrease, especially in adolescents and youth. More surveillance and attention to risk factors are suggested to identify high-risk groups and to implement vaccination.
Heart rate deflection point as a strategy to defend stroke volume during incremental exercise.

The purpose of this study was to examine whether the heart rate (HR) deflection point (HRDP) in the HR-power relationship is concomitant with the maximal stroke volume (SV(max)) value achievement in endurance-trained subjects. Twenty-two international male cyclists (30.3 +/- 7.3 yr, 179.7 +/- 7.2 cm, 71.3 +/- 5.5 kg) undertook a graded cycling exercise (50 W every 3 min) in the upright position. Thoracic impedance was used to measure continuously the HR and stroke volume (SV) values. The HRDP was estimated by the third-order curvilinear regression method. As a result, 72.7% of the subjects (HRDP group, n = 16) presented a break point in their HR-work rate curve at 89.9 +/- 2.8% of their maximal HR value. The SV value increased until 78.0 +/- 9.3% of the power associated with maximal O(2) uptake (Vo(2 max)) in the HRDP group, whereas it increased until 94.4 +/- 8.6% of the power associated with Vo(2 max) in six other subjects (no-HRDP group, P = 0.004). Neither SV(max) (ml/beat or ml.beat(-1). m(-2)) nor Vo(2 max) (ml/min or ml.kg(-1). min(-1)) were different between both groups. However, SV significantly decreased before exhaustion in the HRDP group (153 +/- 44 vs. 144 +/- 40 ml/beat, P = 0.005). In the HRDP group, 62% of the variance in the power associated with the SV(max) could also be predicted by the power output at which HRDP appeared. In conclusion, in well-trained subjects, the power associated with the SV(max)-HRDP relationship supposed that the HR deflection coincided with the optimal cardiac work for which SV(max) was attained.
Complete 1H and 13C NMR assignments of two phytosterols from roots of Piper nigrum

Using modern NMR techniques, including DQF‐COSY, NOESY, HETCOR and HMBC, the full assignments of all 1H and 13C chemical shifts were made for stigmastane‐3,6‐dione and stigmast‐4‐ene‐3,6‐dione, isolated from the roots of Piper nigrum (Piperaceae). Their stereochemistry was resolved by a combination of 2D NOESY data and analysis of coupling constants. The two compounds were isolated from the genus Piper for the first time. Copyright © 2004 John Wiley & Sons, Ltd.