Miracle-dz/UniFAR-FTUs huggingface dataset:
Relating Language Teaching and Content Teaching.

material. A rough sketch of discourse classes from more specific to more general (i.e. in the direction of greater generalization) is given in Table 1. Table 1: Discourse categories CL and assumption 2(c) In this case a language class is taught with the intention of aiding the L2 students' achievement in content classes, i.e., LT -CL. This discussion should go beyond the case where a general basic ESL course teaches a student some English with the result that the student can make some sense of any content course he takes later. This is likely to happen to some degree with any language course and requires no particular curriculum planning. It is desirable, too, that it go beyond the case where the language course has the limited objective of helping the student through the content in a particular lesson or unit, since this is similar to the objective of L, teaching combined with content teaching. The aim should be more general and long-term: to see what LT curriculum can help students manage content learning tasks independently. This is particularly important in the higher grades in the school system where the content is more abstract, the language demands are more intense (more lecturing, more reading and writing), and the student has a decreasing number of years to catch up in language and content achievement. Two ESL models for L. teaching for content learning are English for special purposes and ESL study skills courses, (e.g., Yorkey 1970). Both assume that LT -> CL, and would be redundant if they did not, but there do not appear to be any studies which test this assumption. A third model, developed for L1 students, is reading and study skills in the content areas, and here there is some evidence for LT CL. Thus Schiller (1963) found that the systematic use of study skills in social studies promoted a significant increase in geography achievement. 179 This content downloaded from 157.55. 39.207 on Thu, 20 Oct 2016 04:13:58 UTC All use subject to http://about.jstor. org/terms
Metabolomics as a Tool in Agriculture

Metabolomics is a study through can be obtain a better understanding of the complex - ity of the biological systems, through the chemical composition and relations with the physiology of the plant. The literature describes a lot of information on this support in areas of medicinal plants, chemosystematics, adulteration of plants, etc., but it is scarce in agriculture. At present, agriculture plays a crucial role in human beings. The demand of foods has increased due to the continuous increase in the population, and this requires an increase in the production of crops, besides the crops being affected by the climatic change, attack of pest and diseases and resistance to a conventional agrochemicals. At present, scientists are doing some practices or studies of genetic improvement of crops to increase their production and avoid the problems pointed out. It is an important part of the genomic studies; the results could be the basis for a genetic improvement based on the chemical composition of the crops, and in the metabolomics studies represent a crucial role in their quality for human consumption. The aim of the chapter is to review the literature from 10 years behind emphasizing the importance of metabolomics in crops of economic and feed value. heredity. Generate metabolic profiles to determine the impact of geographic location and season, study the phenotype of natural variations of certain plant species, evaluate transgenic variet ies, study metabolic variations of different cultivars and carry out functional characterizations (functional genomics). Analyse metabolic changes during growth, development and differentia tion, elucidate biosynthetic pathways, analyse population differentiation, carry out chemotaxo nomic analyses, carry out nontargeted studies and characterize cultivars [21].
Domestic peak-load management including vehicle-to-grid and battery storage unit using an artificial neural network

Controlled charging and discharge of electric vehicles (EVs) in distributed power systems can reduce the peak demand on the grid. This paper presents an energy management strategy (EMS) using an artificial neural network to shave the domestic peak grid load by the coordinated response of distributed energy resource (DER) units including photovoltaic (PV) systems, V2G (vehicle to grid)-capable EVs, and battery energy storage systems (BESS). The developed EMS is implemented on a test system including 15 houses and the realistic load pattern of California, U.S. From the simulation results for this network it is found that an artificial-neural-network controller can effectively coordinate the system to reshape the load curve and shave the domestic peak loading by up to 77%.
Formalizing the MetaTheory of Q 0 in Rogue-Sigma-Pi

Introduced by Peter Andrews in the 1960’s, Q0 is a classical higher-order logic based on simply-typed lambda calculus. This paper presents our work in progress on the formalizing of Q0 in a programming language, Rogue-Sigma-Pi (RSP), with the aim of validating its meta-theory. The main challenge of this project arises from the fact that while all logical derivations are carried out in much detail in Andrews’ formalism, many of the syntactic derivations have been kept implicit. Therefore, most of our work has been devoted to setting up a framework that allows us to formalize low-level syntactic notions of Q0, such as variable occurrences, bindings and replacement. This formalization also includes proving meta-theoretic properties of these various syntactic notions. Building on the the ability to prove syntactic derivations assumed in Andrews’ formalism, recent progress has led to the proving of basic meta-theorems of Q0, such as the equality rules, alpha-equivalence, betaand eta-conversions, as well as capture-avoiding substitution. This paper will discuss the theoretical and engineering challenges faced in our formalizing of Q0 in RSP that is guided by a faithful adherence to Andrews’ presentation on paper.
A 2-Year Quantitative Assessment of Chlamydia Trachomatis in a Sexually Transmitted Diseases Clinic Population by the Microtrak Direct Smear Immunofluorescence Test

The MicroTrak direct smear immunofluorescence test was used to determine the prevalence of Chlamydia trachomatis elementary bodies (EBs) in groups of patients in various clinical categories, most of whom were seen in a clinic for sexually transmitted diseases (STD). Overall, 8138 adequate specimens were tested, of which 14.3% were found to contain chlamydial EBs. Of the samples from patients seen in the STD clinic, over 70% were from women and 14.9% of these were positive, as were 15.7% of those from men. EBs were detected in 27% of samples from infants and in 7.0% of those from adults with conjunctivitis. EBs were detected most often in men with nongonococcal urethritis (40.2%), infants with conjunctivitis (30%) and contacts of chlamydiae-positive patients (24.5%) and least often in ‘prostatitis’ (2.9%) and patients tested to determine the success of treatment (2.7%). Over 40% of samples from both the male urethra and the cervix contained 10 or fewer EBs, highlighting the importance of recognizing small numbers and the sensitivity required of other detection procedures.
Incremental Regularized Least Squares for Dimensionality Reduction of Large-Scale Data

Over the past few decades, much attention has been drawn to large-scale incremental data analysis, where researchers are faced with huge amounts of high-dimensional data acquired incrementally. In such a case, conventional algorithms that compute the result from scratch whenever a new sample comes are highly inefficient. To conquer this problem, we propose a new incremental algorithm incremental regularized least squares (IRLS) that incrementally computes the solution to the regularized least squares (RLS) problem with multiple columns on the right-hand side. More specifically, for an RLS problem with $c$ ($c>1$) columns on the right-hand side, we update its unique solution by solving an RLS problem with a single column on the right-hand side whenever a new sample arrives, instead of solving an RLS problem with $c$ columns on the right-hand side from scratch. As a direct application of IRLS, we consider the supervised dimensionality reduction of large-scale data and focus on linear discriminant analysis (.
Dietary Intake of Minerals and the Risk of Ischemic Stroke in Guangdong Province, China, 2007-2008

Introduction Previous studies have investigated the association between mineral intake and the risk of ischemic stroke, but results are inconsistent. We conducted a case-control study to ascertain the associations between intake of dietary potassium, calcium, magnesium, sodium, and iron and the ischemic stroke risk in the southern Chinese population. Methods Information on lifestyle and typical food consumption was obtained from 374 hospital inpatients with ischemic stroke and 464 hospital-based control patients. Added sodium from salt or soy sauce could not be reliably quantified, but participants were asked to characterize their diet as low in salt, normal, or high in salt. Logistic regression analyses were performed to assess possible associations between the effects of mineral intake and ischemic stroke risk. Results The mean weekly intakes of potassium, calcium, magnesium, and iron were lower among case patients than among control patients. Sodium was an exception. Lower stroke risk was associated with higher weekly dietary calcium or magnesium levels (adjusted odds ratio, 0.32) for the highest versus lowest category of intake, and significant dose-response relationships were seen. No significant associations were found for potassium, iron, or sodium. However, patients who consumed a salty diet were more than twice as likely as those whose diet was light in salt to experience an ischemic stroke. Conclusion The findings suggest that lowering sodium intake while maintaining high levels of dietary calcium and magnesium may help prevent ischemic stroke in southern Chinese adults.
Le modèle républicain d’intégration : implications pour la psychologie des relations entre groupes

Des analyses historiques et sociologiques ontmis en evidence les caracteristiques du modele republicain en tant que tradition specifiquement francaise d'integration et d'organisation de la vie collective. Cependant, tres peu de recherches en psychologie ont examine les perceptions, les attitudes ou les croyances des individus a l'egard de ce modele. Nous presentons les resultats d'une serie d'etudes qui mettent en evidence deux dimensions distinctes et orthogonales structurant l'ideologie republicaine, l'une reliee a la citoyennete et l'autre reliee a la laicite. De plus, nous montrons que l'adhesion a ces principes republicains est non seulement tres elevee mais qu'elle a des implications importantes pour comprendre les perceptions et les attitudes intergroupes des Francais(es), ainsi que les orientations d'acculturation de Francais(es) issus de l'immigration maghrebine.
Direct Model Reference Adaptive Fuzzy Control of Networked SISO Nonlinear Systems

This study presents a novel direct model reference fuzzy controller as applied to the control of a nonlinear system over a network subject to variable network induced time delay. The proposed method uses Pade approximation to cope with this condition. Unlike most approaches seen in the literature, which are mostly model based and necessitate the solution of a set of linear matrix inequalities, the proposed approach is online and can be applied to nonlinear systems with a little knowledge about the structure of the system and the values of its parameters. The stability of the proposed method is proved using an appropriate Lyapunov function. The approach is implemented and tested on a dc motor with nonlinear characteristics and nonlinear state-dependent disturbance. It is shown that it is capable of controlling the system over a network subject to variable network-induced time delay with bounded tracking error. In addition, the effect of packet losses is considered in the implementation part and it is seen that the system can be controlled under these conditions too.
Sparse nonnegative matrix underapproximation and its application to hyperspectral image analysis

Dimensionality reduction techniques such as principal component analysis (PCA) are powerful tools for the analysis of high-dimensional data. In hyperspectral image analysis, nonnegativity of the data can be taken into account, leading to an additive linear model called nonnegative matrix factorization (NMF), which improves interpretability of the decomposition. Recently, another technique based on under-approximations (NMU) has been introduced, which allows the extraction of features in a recursive way, such as PCA, but preserving nonnegativity, such as NMF. However, for difficult hyperspectral datasets, even NMU can mix some materials together, and is therefore not able to separate of all materials properly for accurate target identification. In this paper we introduce sparse NMU by adding a sparsity constraint on the abundance matrix and use it to extract materials individually in a more efficient way than NMU. This is experimentally demonstrated on a HYDICE image of the San Diego airport.
Convergent Evolution and Divergent Selection: Lizards at the White Sands Ecotone

Ecological transition zones, where organismal phenotypes result from a delicate balance between selection and migration, highlight the interplay of local adaptation and gene flow. Here, I study the response of an entire species assemblage to natural selection across a common ecotone. Three lizard species, distributed along a dramatic environmental gradient in substrate color, display convergent adaptation of blanched coloration on the gypsum dunes of White Sands National Monument. I investigate the role of gene flow in modulating phenotypic response to selection by quantifying color variation and genetic variation across the ecotone. I find species differences in degree of background matching and in genetic connectivity of populations across the ecotone. Differences among species in phenotypic response to selection scale precisely to levels of genetic isolation. Species with higher levels of gene flow across the ecotone exhibit less dramatic responses to selection. Results also reveal a strong signal of ecologically mediated divergence for White Sands lizards. For all species, phenotypic variation is better explained by habitat similarity than genetic similarity. Convergent evolution of blanched coloration at White Sands clearly reflects the action of strong divergent selection; however, adaptive response appears to be modulated by gene flow and demographic history and can be predicted by divergence‐with‐gene‐flow models.
Characteristics of mutant mice (ICGN) with spontaneous renal lesions: a new model for human nephrotic syndrome

Spontaneous nephrotic mice (ICGN mice), a new mutant strain of mouse from outbred ICR, were clinically, macroscopically, histologically and immunohistochemically studied to establish their value as a model for human nephrotic syndrome. Most of the affected mice developed proteinuria, hypoproteinaemia and hypercholesterolaemia, and some of them developed systemic oedema. A high concentration of blood urea nitrogen (BUN) and a low haematocrit value were also observed. The kidneys of severe cases showed a decrease in size and had a yellowish granular surface. These findings indicated that the mice were terminally affected by chronic renal in-sufficiency. Histopathology demonstrated glomerular lesions consisting of thickened basement membranes of the capillary loops with irregular spike-like protrusions and enlargement of the mesangium unaccompanied by cellular proliferation. The immunofluorescence technique revealed positive granular staining for IgA, IgG and IgM and to a lesser extent for C3 along the capillary loops in affected mice. The similarity between this spontaneous disease and human nephrotic syndrome caused by idiopathic glomerular lesions is discussed. ICGN mice may be a useful animal model for this human disease.
Anxiety in Depressed School Children

The purpose of this study was to investigate the relationship between anxiety and depression in school children. From a pool of 292 nineto eleven-year-old children, 23 depressed children (12 boys and 11 girls) were identified and compared to 23 ageand schoolmatched controls. Measures were based on parallel items from the self-rated Children's Depression Inventory (CDI), parent-rated Child Behaviour Checklist (CBCL) and Children's Behaviour Questionnaire for parents and teachers as compared to DSM-III symptomatology for Overanxious Disorder (OAD). Results suggest that depressed children are generally anxious but not identical to children suffering from OAD. Depressed girls were most likely to suffer from tension and somatic symptoms than depressed boys, who tend to be more generally anxious at this age.
Risk factors for deep surgical site infection following operative treatment of ankle fractures.

BACKGROUND Surgical site infection is one of the most common complications following ankle fracture surgery. These infections are associated with substantial morbidity and lead to increased resource utilization. Identification of risk factors is crucial for developing strategies to prevent these complications. METHODS We performed an age and sex-matched case-control study to identify patient and surgery-related risk factors for deep surgical site infection following operative ankle fracture treatment. We identified 1923 ankle fracture operations performed in 1915 patients from 2006 through 2009. A total of 131 patients with deep infection were identified and compared with an equal number of uninfected control patients. Risk factors for infection were determined with use of conditional logistic regression analysis. RESULTS The incidence of deep infection was 6.8%. Univariate analysis showed diabetes (odds ratio [OR] = 2.2, 95% confidence interval [CI] = 1.0, 4.9), alcohol abuse (OR = 3.8, 95% CI = 1.6, 9.4), fracture-dislocation (OR = 2.0, 95% CI = 1.2, 3.5), and soft-tissue injury (a Tscherne grade of ≥1) (OR = 2.6, 95% CI = 1.3, 5.3) to be significant patient-related risk factors for infection. Surgery-related risk factors were suboptimal timing of prophylactic antibiotics (OR = 1.9, 95% CI = 1.0, 3.4), difficulties encountered during surgery, (OR = 2.1, 95% CI = 1.1, 4.0), wound complications (OR = 4.8, 95% CI = 1.6, 14.0), and fracture malreduction (OR = 3.4, 95% CI = 1.3, 9.2). Independent risk factors for infection identified by multivariable analyses were tobacco use (OR = 3.7, 95% CI = 1.6, 8.5) and a duration of surgery of more than ninety minutes (OR = 2.5, 95% CI = 1.1, 5.7). Cast application in the operating room was independently associated with a decreased infection rate (OR = 0.4, 95% CI = 0.2, 0.8). CONCLUSIONS We identified several modifiable risk factors for deep surgical site infection following operative treatment of ankle fractures.
Capital Mobility in a Second-Best World: Moral Hazard with Costly Financial Intermediation

This paper studies the welfare effects of financial integration in the presence of moral hazard. Entrepreneurs face a trade off between risk and return. Banks may mitigate the resultant excessive risk by costly monitoring, where greater risk reduction requires more resources devoted to risk supervision. Hence, the excessive risk associated with moral hazard is endogenously determined. We show that a drop in banks' cost of funds increases the risk tolerated by banks in a competitive equilibrium. Similarly, less efficient intermediation technology (i.e. more costly risk monitoring), higher macroeconomic volatility, and a more generous deposit insurance all raise the riskiness of projects in a competitive equilibrium. Overborrowing would arise e insurance in circumstances where the cost of financial intermediation is relatively high, the banks' cost of funds is relatively low, and macroeconomic volatility is high. With relative scarcity of funds, financial integration is welfare reducing (enhancing) if the financial intermediation is relatively inefficient (efficient). The association between financial integration and welfare may be non-monotonic. For a large enough cost of financial intermediation, the dependence of welfare on the banks' cost of funds has an inverted U shape. For such an economy, financial integration and reforming the banking sector are complimentary policies, as the gain of each reform is magnified by the second. If one starts with a highly inefficient banking system, reforming it and improving its operation is a precondition for s
MR connectomics: a conceptual framework for studying the developing brain

The combination of advanced neuroimaging techniques and major developments in complex network science, have given birth to a new framework for studying the brain: “connectomics. ” This framework provides the ability to describe and study the brain as a dynamic network and to explore how the coordination and integration of information processing may occur. In recent years this framework has been used to investigate the developing brain and has shed light on many dynamic changes occurring from infancy through adulthood. The aim of this article is to review this work and to discuss what we have learned from it. We will also use this body of work to highlight key technical aspects that are necessary in general for successful connectome analysis using today's advanced neuroimaging techniques. We look to identify current limitations of such approaches, what can be improved, and how these points generalize to other topics in connectome research.
Complexity of Propositional Abduction for Restricted Sets of Boolean Functions

Abduction is a fundamental and important form of non-monotonic reasoning. Given a knowledge base explaining how the world behaves it aims at finding an explanation for some observed manifestation. In this paper we focus on propositional abduction, where the knowledge base and the manifestation are represented by propositional formulae. The problem of deciding whether there exists an explanation has been shown to be SigmaP2-complete in general. We consider variants obtained by restricting the allowed connectives in the formulae to certain sets of Boolean functions. We give a complete classification of the complexity for all considerable sets of Boolean functions. In this way, we identify easier cases, namely NP-complete and polynomial cases; and we highlight sources of intractability. Further, we address the problem of counting the explanations and draw a complete picture for the counting complexity.