Miracle-dz/UniFAR-FTUs huggingface dataset:
Daycare Spending in Advanced Capitalist Countries: The Conditional Effects of Female Labor Market Integration

What are the effects of female labor market integration on daycare spending in advanced capitalist countries, and what factors condition the effects? In their seminal book, Huber & Stephens (2001a) argue that the interaction between female labor force participation (FLFP) and strong leftist governments will result in more welfare spending – essentially because female labor market integration increases demand for caregiving services. Applying their model to daycare spending this article finds no evidence for the Huber&Stephens hypothesis. The article instead finds that female labor market integration will increase daycare spending, but only in economies with strong employer organizations and political systems with few constitutional constraints on state power. In political economies with fragmented and weak employer organizations and a political system with many constitutional constraints, the mobilization of women on the labor market does not seem to result in more daycare spending. As such, the organization of the political economy and the structure of the state is argued to be strong mediating factors of the effects of female labor market integration on daycare spending – and hence on early childhood education. The arguments are tested using an error correction specification on 17 advanced capitalist countries with data from 1980-2007.
Infrared ultraspectral signature classification based on a restricted Boltzmann machine with sparse and prior constraints

The state-of-the-art ultraspectral technology brings a new hope for the high precision applications due to its high spectral resolution. However, it comes with new challenges brought by the improvement of spectral resolution such as the Hughes phenomenon and over-fitting issue, and our work is aimed at addressing these problems. As new Markov random field (MRF) models, the restricted Boltzmann machines (RBMs) have been used as generative models for many different pattern recognition and artificial intelligence applications showing promising and outstanding performance. In this article, we propose a new method for infrared ultraspectral signature classification based on the RBMs, which adopt the regularization-based techniques to improve the classification accuracy and robustness to noise compared to traditional RBMs. First, we add an arctan-like term to the objective function as a sparse constraint to improve the classification accuracy. Second, we utilize a Gaussian prior to avoid the over-fitting problem. Third, to further improve the classification performance, a multi-layer RBM model, a deep belief network (DBN), is adopted for infrared ultraspectral signature classification. Experiments using different spectral libraries provided by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Environmental Protection Agency (EPA) were performed to evaluate the performance of the proposed method by comparing it with other traditional methods, including spectral coding-based classifiers (binary coding (BC), spectral feature-based binary coding (SFBC), and spectral derivative feature coding (SDFC) matching methods), a novel feature extraction method termed crosscut feature extraction matching (CF), and three machine learning methods (artificial deoxyribonucleic acid (DNA)-based spectral matching (ADSM), DBN, and sparse deep belief network (SparseDBN)). Experimental results demonstrate that the proposed method is superior to the other methods with which it was compared and can simultaneously improve the accuracy and robustness of classification.
Understanding Information Rating Intention Based on Ant Foraging Behavior

This study focuses on an understudied topic: What are the factors influencing individual intention to share their information (e.g., news) rating with others in an online community? Drawing on social foraging theory, particularly on ant information sharing behavior, we proposed that information rating intention is affected by four factors: altruistic motives, identification with the community, information quality, and knowledge selfefficacy. The model was tested in the context of news communities, using survey data from 150 subjects. Altruistic motives were found to predict intention for both positive rating and negative rating. In addition, higher positive rating intention was predicted by stronger identification with the community, while higher negative rating intention was predicted by lower information quality and higher knowledge self-efficacy. The findings advance our knowledge about information rating, and provide implications for practitioners of rating systems. The adaptation of foraging theories for information systems research is a promising future research area.
Role and potential benefit of teacher collaboration in elementary school

ii Acknowledgements . iii Dedication . iv Chapter One: Introduction to My Research. 1 My Path to Becoming a Researcher . 1 Why Did I Decide to Conduct Research in Teacher Collaboration? 2 Theoretical Framework . 3 Overview of the Research. 7 Significance of the Study . 8 Layout of the Thesis . 9 Chapter Two: Literature Review . 10 Theoretical Aspects of Teachers Professional Development . 10 Formal Professional Development for Teachers . 19 Informal Professional Development for Teachers . 21 Collaboration as a Key Aspect of PD. 23 a. What is collaboration? 23 b. Characteristics of successful collaboration . 27 c. Benefits of teacher collaboration . 29
Solar Radiation Estimation from Rainfall and Temperature Data in Arid and Semi-arid Climates of Iran

Precipitation and air temperature data, only, are often recorded at meteorological stations, with radiation being measured at very few weather stations, especially in developing countries. Therefore there arises a need for suitable models to estimate solar radiation for a completion of data sets. This paper is about an evaluation of eight models for an estimation of daily solar radiation (Q) from commonly measured variables in six synoptic stations of Iran, namely: Mashhad, Kerman, Tabriz, Esfehan, Hamedan and Zanjan using daily rainfall and temperature data for a duration of three years of 2000, 2001 and 2002. These stations represent several arid and semiarid sub-climates of Iran as based on extended-De Martonne climatic classification (semiarid-cold: Mashhad and Tabriz, arid-cold: Esfehan, Kerman, semiarid-extracold: Hamedan and Zanjan). The STATISTICA (ver. 6.0) software was employed for non-linear multivariate regression. The results indicated that most of the models overestimated in lower values of solar radiation while underestimating in the higher ranges, indicating a systematic error. Performance of the models was evaluated based on the Root Mean Square Errors (RMSE) as well as R. RMSE ranged from 1.14 to 7.76 Cal cmmin for the whole data range and in all the six stations. Among the eight models, the Richardson model rendered the best agreement with the measured data in Kerman and Zanjan stations. In case of Hamedan station, Bristow and Campbell model was the most suitable. As for Tabriz station, De Jong and Stewart model using rainfall and range of daily temperature data led to the best performance. In Mashhad station, McCaskill equation can be recommended. Analysis of the data in Esfehan station showed no significant difference among the models. Due to variation in equations' performances, to come to valid conclusions and to choose the most suitable radiation models, further study would be required from other climatic regions the country.
The Impact of Sales Promotions on the Performance of Auto-Mobile Industries in Ghana: A Case Study of PHC Motors (Accra-Ghana)

The purpose of the study was to assess the impact of sales promotion on organisational performance in the auto mobile industry in Ghana. The study was conducted at PHC Motors Ghana’s Retail Outlet in Accra, Ghana. The objective of the study was to examine the relationship between sales promotion and organisational performance, to examine the effect of sales promotion in the automobile market, and to identify the challenges hindering sales promotions effectiveness.The study used descriptive research approach and the data was purely quantitative. In order to achieve this objective, thirty (30) respondents were selected using purposive and random sampling techniques. The Data was analysing using SPSS obtained from the field. The research revealed that the impact of sales promotion on organizational performance in PHC is intense. Also, from the management perspective most of the respondents agree that sale promotion provides extra incentives to purchase as well as stimulating resellers demand and effectiveness. The study devoted to conclude the relationship between sale promotion and the organizational performance, most sales promotion provide extra incentives to purchase as well as stimulating resellers demand and effectiveness. It revealed that effective sales promotion increase sales. The researcher therefore recommended that, management of PHC Motors should embark on more strategic sale promotion in order to increase their market share and profitability. Keywords : Sales promotion, Auto mobile industry, Performance, Relationship, Ghana.
A nonsmooth algorithm for solving the frictional quasistatic contact problems

The aim of this paper is to give an algorithm for solving nondifferentiable equations using the generalized Jacobians with applications in contact problems. In contact problems, the functional which describes the contact conditions and the influence of the frictions is nondifferentiable. A nonsmooth model for solving by damped Newton method the nonsmooth equations, is presented, in which the variables are related to the candidate contact nodes, and which modeling the influence of the friction and the contact conditions. Some definitions, results and algorithms from nonsmooth analysis are presented which leads to some sufficient conditions such that the nonlinear and nondifferentiable system obtained in modeling the contact problems with friction, have one solution obtained by Newton's method using generalized gradient.
uorescent indicator for determination of b-glucosidase activity †

Enzymes represent a group of organic macromolecules acting as catalysts for the vital processes occurring in cells. In healthy organisms, concentration and activity of enzymes are maintained within strictly dened ranges. Inappropriate activity and changes in structure of some enzymes most oen indicate serious dysfunction of a cell or whole organism including genetic disorders in humans like glucose-6-phosphate dehydrogenase (G6PD) deciency, Tay–Sachs and Gaucher diseases. In the view of indisputable importance of enzymes for living organisms, investigations aimed at developing the new methods of measuring enzymes activity are of high cognitive importance and applicative value. b-Glucosidases are a group of glycosyl hydrolases which catalyze cleavage of b-glucosidic bonds in disaccharides and other glucose-containing molecules. These enzymes are abundant in microorganisms, plants, mammals and humans, where they play important roles in a wide sort of biological processes. Since action of b-glucosidases leads to release of biologically active molecules from respective glycosides, b-glucosidases have been investigated and employed in different elds of science, medicine and technology. For example, monitoring of the b-glucosidase activity in humans is used in diagnosis of Gaucher disease, which is a genetic disorder characterized by the deciency of acid b-
The effect of context change on simple acquisition disappears with increased training

The goal of this experiment was to assess the impact that experience with a task has on the context specificity of the learning that occurs. Participants performed an instrumental task within a computer game where different responses were performed in the presence of discriminative stimuli to obtain reinforcers. The number of training trials (3, 5, or 8) with each discriminative stimulus varied between participants. A single test trial was conducted in the context where training occurred or in a different but equally familiar context. The change in context attenuated performance in participants that received 3 training trials, but not in the others, suggesting that the influence of context on performance decreases when training increases.
Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods

In recent years state space models, particularly the linear Gaussian version, have become the standard framework for analyzing macro-economic and financial data. However, many theoretically motivated models imply non-linear or non-Gaussian specifications or both. Existing methods for estimating such models are computationally intensive, and often cannot be applied to models with more than a few states. Building upon recent developments in precision-based algorithms, we propose a general approach to estimating high-dimensional non-linear non-Gaussian state space models. The baseline algorithm approximates the conditional distribution of the states by a multivariate Gaussian or t density, which is then used for posterior simulation. We further develop this baseline algorithm to construct more sophisticated samplers with attractive properties: one based on the accept-reject Metropolis-Hastings (ARMH) algorithm, and another adaptive collapsed sampler inspired by the cross-entropy method. To illustrate the proposed approach, we investigate the effect of the zero lower bound of interest rate on monetary transmission mechanism.
Experimental Verification of the Quality of Clusterings Produced by Hard Clustering Algorithms after the Removal of Unstable Data Elements

Many different clustering algorithms have been developed to detect structure in data sets in an unsupervised way. As user intervention for these methods should be kept to a minimum, robustness with respect to userdefined initial conditions is of crucial importance. In a previous study, we have shown how the robustness of a hard clustering algorithm can be increased by the removal of what we called unstable data elements. Although robustness is a main characteristic of any clustering tool, the most important feature is still the quality of the produced clusterings. This paper experimentally investigates how the removal of unstable data elements from a data set affects the quality of produced clusterings, as measured by the mutual information index, using three biological gene expression data sets. Keywords-hard clustering; cluster quality; unstable elements; mutual information context; microarray data.
MIDDLE AND HIGH SCHOOL TEACHERS' TRANSFORMATIVE LEARNING OF CENTER

We describe a project to design and implement professional development and investigate how dilemma, critical reflection, and rational discourse affect middle and high school teachers’ reasoning about center. Framed by transformative learning theory, the study highlights how teachers’ engagement with activities focused on these elements can enhance understandings of traditionally problematic content. Results reveal that critically reflecting on activities, engaging in rational discourse while working on activities, and examining multiple perspectives through multiple representations and conceptualizations broadened teachers’ perspectives on the mean. This study contributes to teacher education by identifying circumstances conducive to deepening statistical understandings and supporting reasoning in increasingly sophisticated ways using a theoretical frame for adult learning to investigate teacher learning. BACKGROUND The proliferation of data in our technological world brings about an urgent need for schools to graduate statistically literate students. Considerable research work offers insights into how students learn statistics content in conceptually meaningful ways. Translating these insights into generalized classroom practices, however, necessitates teachers who are knowledgeable about the content and ways to teach the content. Anecdotal evidence suggests that many teachers lack sufficient experiences with statistics content to realize current educational visions in statistics. Although considerable research focuses on center, evidence suggests that teachers’ knowledge related to this foundational topic remains largely procedural (e.g., Leavy & O’Loughlin, 2006) and similar to that of their students (Groth & Bergner, 2006; Jacobbe, 2012). Continued research is needed to design instruction and activities that are effective in facilitating teachers’ development of conceptual understandings as one step towards achieving larger educational goals. In this paper, we describe an investigation of professional development (PD) designed to support middle and high school mathematics teachers’ reasoning and learning in statistics. We focus on measures of central tendency to address the research question: How do dilemma, critical reflection, and rational discourse affect teachers’ reasoning about measures of central tendency? FRAMEWORK
ANTIOXIDANT ACTIVITY (PHENOL AND FLAVONOID CONTENT ) OF THREE DIFFERENT CULTIVARS OF PIPER BETLE L. (PIPERACEAE)

In the present study, an attempt has been made for the estimation of total phenol and flavonoid content and their radical scavenging properties using Piper betle (L.) leaves. In that, Cultivars i.e., Nov Bangla (NB), Sirugamani-1 (SGM-1) and Halisar Sanchi (HS) were selected for this study. The total phenolic content was ranged from 95.04 to 127.33 mg/100g equivalent to gallic acid and flavonoids were ranged from 51.72 to 61.08 mg/ 100g equivalent to standards of Catechin. In vitro antioxidant activity was estimated using 1,1-diphenyl-2-picryl hydrazyl (DPPH), free radical scavenging activity, improved ABTS radical cation decolorization assay and ferric reducing antioxidant power (FRAP) assay. Among all the cultivars, The highest Phenol content (93.79%) was observed for Sirugamani-1 by DPPH method and highest Phenol content (96.12% & 6791.86 (µg/g) was obtained for Halisar Sanchi by ABTS assay and FRAP activity respectively. The study revealed that the leaves of Piper betle (L.) has higher amount of antioxidant activity and it could be used for any novel drug preparation.
FAILURE OF SUBMARINE SLOPES UNDER WAVE ACTION

The results of model tests, carried out to evaluate the stability of submarine slopes under wave action are presented. A Bentonite clay was sedimented in a glass walled tank 6 feet long by 0.5 feet wide by 2.5 feet deep. The sedimentation and consolidation processes were studied and sediment densities were measured at various depths in the profile. Vane shear strength profiles were also measured afvarious average degrees of consolidation. Plastic markers were placed in the sediment adjacent to a glass wall so that the soil movements under both gravity and wave induced slides could be documented by photography. Dimensional similitude is discussed and the model test data are presented in a dimensionless form. All instabilities were observed to be of the infinite slope type. Analysis of the data shows that wave action is instrumental in initiating downslope mass movements in gently to steeply sloping off-shore sediments. General lack of agreement between the model test results and published theoretical analyses was found but there was close similarity in the depths and form of failure under wave action and under gravity stresses alone. The loss of stability under wave action is analyzed on the concept that failure is gravity controlled and the soil strength is reduced to a value commensurate with gravity sliding by the cyclic shearing stresses imposed by progressive waves. A method of evaluating the stability of prototype slopes using a model test correlation and field vane strength measurements is proposed.
Arrhythmia Susceptibility and Management in Adult Patients with Repaired Tetralogy of Fallot

Tetralogy of Fallot is the most common cyanotic congenital valvular heart lesion. Successful neonatal repair has lead to improved survival into and through adulthood. Severe pulmonary regurgitation occurs as a consequence of surgical repair, resulting in right ventricular volume overload, tricuspid regurgitation, and atrial and ventricular scarring and fibrosis. Repair also involves atriotomy and ventriculotomy, as well as the placement of patch material. These interventions contribute to an increased arrhythmia burden in these patients. Management strategies are variably successful and include pharmacotherapy, catheter ablation, device implantation, and pulmonary valve replacement.
Influence of Plastic Deformation on the Properties of 6066 Heat Treatable Aluminum Alloys

The aims of this work are to (1) study the influence of plastic deformation on the properties of 6066 aluminum alloy; (2) study the effect of deformation on the age hardening of these alloys; (3) study the recovery of these defects from the samples. These effects were investigated in terms of microstructure using positron annihilation spectroscopy (PAS) analysis and mechanical properties by hardness measurements. Dislocations facilitate nucleation of precipitates. At first sight, deformed specimens had lower hardness as compared to non-deformed ones, and as the deformation increase, the hardness decreases. Another output of the mechanical test was the increase in hardness in the specimens after artificial aging with an increase in percent deformation.
The Climate Impact of Aerosols on Lightning: Is it Detectable from Long-term Aerosol and Meteorological Data?

Abstract. Aerosol effect on lightning is still under debate. In this study, the relative roles of meteorology and aerosols on lightning activities in Africa are investigated from a climatological perspective, based on the 11-year worth of lightning flashes from Lightning Imaging Sensor onboard Tropical Rainfall Measuring Mission, aerosol optical depth (AOD) from Moderate Resolution Imaging Spectroradiometer onboard Aqua, meteorological variables from the Medium-Range Weather Forecasting ERA-Interim reanalysis and aerosol composition data from the Modern-Era Retrospective analysis for Research and Application. Six meteorological variables are selected: sea level pressure (SLP), potential temperature ( θ ) at 2 m above ground level, mid-level relative humidity (RH), convective availabe potential energy (CAPE), vertical wind shear (SHEAR), and 200 hPa divergence (Div). To differentiate two dominant aerosol types in Africa and to account for their distinct climate regimes that all affect lightning, we separate two regions of interest (ROIs): the northern Africa (ROI_1) and the southern Africa (ROI_2) dominated by dust and smoke aerosols, respectively. As compared with dust in ROI_1, smoke aerosols in ROI_2 exhibit huge contrast between dry and wet season. Irrespective of regions, the lightning exhibits large diurnal variation with an afternoon peak and strong seasonality with a summertime peak, while the pronounced differences in lightning under relatively clean and polluted conditions signify the potential influences of aerosols. Lightning is dictated mostly by RH and CAPE in the dust dominant region (ROI_1). In the smoke dominant region (ROI_2), the effect of SLP is also significant. Systematic changes of boomerang shape was found in lightning frequency with AOD, with a turning point at around AOD = 0.3, below which lightning flashes increase monotonously with increasing AOD in both ROIs. As AOD approaches the optimal value, lightning activity seems to be saturated under smoky condition, likely due to the tradeoff between the aerosol invigoration effect and the radiative effect that tends to enhance and suppress lightning, respectively. In contrast, lightning activity in ROI_1 is suppressed by dust aerosol presumably due to the more dominant radiative heating effect of dust aerosol under dry environment.