Miracle-dz/UniFAR-FTUs huggingface dataset:
Internalizing Behavior Problems and Scholastic Achievement in Children: Cognitive and Behavioral Pathways as Mediators of Outcome

Examined a conceptual model in which dual developmental pathways (behavioral and cognitive) are hypothesized to account for the relation among internalizing behavior problems, intelligence, and later scholastic achievement using a cross-sectional sample of 325 children. Classroom behavior and select aspects of cognitive functioning (vigilance, short-term memory) were hypothesized to mediate the relations among internalizing problems, IQ, and long-term scholastic achievement. Hierarchical tests applied to a nested series of models demonstrated that (a) individual differences in measured intelligence among children are associated with variations in classroom performance and cognitive functioning, (b) classroom performance and cognitive functioning make unique contributions to prediction of later achievement over and above the influence of intelligence, (c) anxious/depressive features are correlated but separable constructs, and (d) anxiety/depression and withdrawal contribute to prediction of classroom performance and cognitive functioning over and above the effects of intelligence. Classroom performance and cognitive functioning thus appear to mediate the effects of internalizing behaviors as well as intelligence. Particular attention to the presence and potential impact of social withdrawal on children's functioning, both alone and concomitant with anxiety/depression, appears warranted during the course of clinical evaluations owing to the strong continuity among these variables.
Effect of Selected Yogic Practices on Pain and Disability in Patients with Lumbar Spondylitis

Aim: The study was designed to find the effect of selected yogic practices on lumbar spondylitis. Materials and Methods: This was a prospective, randomized study without a control trial. A total of 172 participants with lumbar spondylitis (age 21–79 years) from the outpatient department (OPD) of neurosurgery, AIIMS, Bhubaneswar, were randomly assigned to receive yoga therapy. The module of selected yogic practices consisted of pawanamuktasana series 1 (loosening and strengthening), asana, pranayama, and relaxation techniques Yoga Nidra. Statistics Analysis: Within groups, comparison was done by paired t-test, and between groups, ANOVA test was carried out to determine the significant difference among the various groups under study. Correlation regression analysis was done to measure the degree of linear relationship between pre- and post-study for various groups. Results: Significant differences were observed with yoga therapy in instant relieve practice group, in short-term practice group, and in long-term practice group (LTPG) with better results in LTPG. Conclusion: Selected yoga therapy has got the better result in management of pain in lumbar spondylitis.
Management Control as a System or a Package? Conceptual and Empirical Issues

Despite the trend in investigating combinations of MC practices that form packages or systems, there is ambiguity about what is meant by a “control package” or “control system”. In this paper, we address questions related to MC as a package and as a system, both from a conceptual and empirical perspective. The purpose of our study is to clarify a number of issues, so as to guide future research in this area. We do not claim to have all the answers. Rather we make a number of assumptions explicit to show when it is important to address multiple MC practices simultaneously, why this is the case, and what the empirical implications are. Our research directly relates to the systems approach to contingency theory and the literature’s struggle to clearly define its most fundamental concept, i.e., “internal consistency”. Our analysis provides a formal definition of “internal consistency” and shows how it can be used to conceptualize MC systems, thereby giving contingency theorists the necessary ingredient to move forward.
Fast Electrical Demand Optimization Under Real-Time Pricing

The introduction of smart meters has motivated the electricity industry to manage electrical demand, using dynamic pricing schemes such as real-time pricing. The overall aim of demand management is to minimize electricity generation and distribution costs while meeting the demands and preferences of consumers. However, rapidly scheduling consumption of large groups of households is a challenge. In this paper, we present a highly scalable approach to find the optimal consumption levels for households in an iterative and distributed manner. The complexity of this approach is independent of the number of households, which allows it to be applied to problems with large groups of households. Moreover, the intermediate results of this approach can be used by smart meters to schedule tasks with a simple randomized method.
Is distance to chemotherapy an obstacle to adjuvant care among the N.C. Medicaid-enrolled colon cancer patients?

BACKGROUND Adjuvant chemotherapy for colon cancer has been linked to patient and provider characteristics but little is known about whether distance to chemotherapy providers constitutes an obstacle to chemotherapy. METHODS A total of 1,184 Medicaid patients diagnosed with colon cancer in North Carolina in 1999-2002 comprised the sample. Data from the N.C. Central Cancer Registry, N.C. Medicaid Claims, American Hospital Directory and US Census were merged. Logistic regression models were used to estimate the association between chemotherapy receipt and the distance to nearest chemotherapy provider. RESULTS Compared to the referent group of SEER-staged II (local) cancer patients living less than 2 miles from the nearest chemotherapy provider, the odds of receiving chemotherapy fell as the distance to the nearest provider increased. The odds ratio (OR) for those living ≥5 to <15 miles away was 0.13 [95% confidence intervals (CI), 0.04-0.39], and OR for those living ≥15 miles away was 0.06 (95% CI, 0.01-0.52). Patients diagnosed with regional, SEER-staged III (regional) cancer were less likely to receive chemotherapy if they lived in rural areas more than 20 miles away from the nearest provider (OR =0.08; 95% CI, 0.01-0.72). However, we found no evidence of association between chemotherapy receipt and distance to the nearest provider for regional cancer patients living in urban areas and those living in rural areas within 20 miles from the nearest chemotherapy provider. CONCLUSIONS Distance to provider may be an obstacle to chemotherapy for some groups of low-income colon cancer patients. Relieving travel burdens of rural patients living far from providers may help Medicaid increase guideline-consistent adjuvant care for regional cancer patients.
Economic theory and the welfare state : a survey and interpretation

'I propose here the view that, when the market fails to achieve an optimal state, society will, to some extent at least, recognize the gap, and nonmarket social institutions will arise attempting to bridge it. ' (Kenneth Arrow 1963, p. 947). 'Economic theorists traditionally banish discussions of information to footnotes. Serious consideration of costs of communication, imperfect knowledge . would, it is believed, complicate without informing. [T]his comforting myth is false. Some of the most important conclusions of economic theory are not robust to considerations of imperfect information' (Michael Rothschild and Joseph Stiglitz 1976, p. 629). 'That any sane nation, having observed that you could provide for the supply of bread by giving bakers a pecuniary interest in baking for you, should go on to give a surgeon a pecuniary interest in cutting off your leg, is enough to make one despair of political humanity' (George Bernard Shaw, The Doctor's Dilemma, 1911).
Mutual Information Theory for Adaptive Mixture Models

Many pattern recognition systems need to estimate an underlying probability density function (pdf). Mixture models are commonly used for this purpose in which an underlying pdf is estimated by a finite mixing of distributions. The basic computational element of a density mixture model is a component with a nonlinear mapping function, which takes part in mixing. Selecting an optimal set of components for mixture models is important to ensure an efficient and accurate estimate of an underlying pdf. Previous work has commonly estimated an underlying pdf based on the information contained in patterns. In this paper, mutual information theory is employed to measure whether two components are statistically dependent. If a component has small mutual information, it is statistically independent of the other components. Hence, that component makes a significant contribution to the system pdf and should not be removed. However, if a particular component has large mutual information, it is unlikely to be statistically independent of the other components and may be removed without significant damage to the estimated pdf. Continuing to remove components with large and positive mutual information will give a density mixture model with an optimal structure, which is very close to the true pdf.
University of Dundee A Critical Discussion Game for Prohibiting Fallacies

The study of fallacies is at the heart of argumentation studies. In response to Hamblin’s devastating critique of the state of the theory of fallacies in 1970, both formal dialectical and informal approaches to fallacies developed. In the current paper, we focus on an influential informal approach to fallacies, part of the pragma-dialectical theory of argumentation. Central to the pragma-dialectical method for analysing and evaluating argumentative discourse is the ideal model of a critical discussion. In this discussion model, a dialectical perspective on argumentation is combined with a pragmatic take on communicative interaction. By formalising and computationally implementing the model of a critical discussion, we take a first step in the development of software to computationally model argumentative dialogue in which fallacies are prohibited along the pragmadialectical norms. We do this by defining the Critical Discussion Game, a formal dialogue game based on the pragma-dialectical discussion model, executable on an online user-interface which is part of a larger infrastructure of argumentation software.
Treatment seeking for obsessive-compulsive disorder: role of obsessive-compulsive disorder symptoms and comorbid psychiatric diagnoses.

Previous research has indicated that individuals afflicted with obsessive-compulsive disorder (OCD) have a very low rate of seeking help from mental health professionals. From standardized psychiatric interviews of 7,214 residents of Edmonton, Canada, we identified 172 subjects with a lifetime diagnosis of OCD; 63 (36.6%) had consulted a doctor about their symptoms. Total number of OCD symptoms (odds ratio [OR] = 2.23) and severe obsessions of violence and other unpleasant thoughts (OR = 2.52) were significantly associated with treatment seeking in multivariate analysis. The absence of association between compulsions and treatment seeking was corroborated by a very low prevalence of treatment seeking (17.3%) in individuals suffering from compulsions only. Our findings suggest that there is a need to teach the public about compulsions, and such a strategy may enhance future public health education programs.
Radiometric calibration of the advanced wind scatterometers carried on-board the METOP satellites

The Advanced Wind Scatterometer (ASCAT) instrument [1, 2 & 3] is one of the instruments carried by the ESA / EUMETSAT METOP satellites (METOP A, B & C) [4]. The ASCAT is a six-beam radar instrument designed to measure wind fields over the oceans [5 & 6]. The instrument also provides useful data for ice and land applications. For the ASCAT, calibration is vitally important; the scientific value of the data is directly related to the quality of the radiometric calibration. Therefore achieving, maintaining and demonstrating excellent radiometric calibration is of the utmost importance. ASCAT calibration is performed using three active calibration point targets, the ASCAT Transponders, which have very accurately known point target cross-sections. The calibration strategy is described below and a detailed explanation is given of how the transponder measurements are used to accurately estimate the in-flight antenna gain patterns and their orientations.
IMU Sensor-Based Electronic Goniometric Glove for Clinical Finger Movement Analysis

Arthritis remains a disabling and painful disease, and involvement of finger joints is a major cause of disability and loss of employment. Traditional arthritis measurements require labour intensive examination by clinical staff. These manual measurements are inaccurate and open to observer variation. This paper presents the development and testing of a next generation wireless smart glove to facilitate the accurate measurement of finger movement through the integration of multiple IMU sensors, with bespoke controlling algorithms. Our main objective was to measure finger and thumb joint movement. These dynamic measurements will provide clinicians with a new and accurate way to measure loss of movement in patients with rheumatoid arthritis. Commercially available gaming gloves are not fitted with sufficient sensors for this particular application, and require calibration for each glove wearer. Unlike these state-of-the-art data gloves, the inertial measurement unit glove uses a combination of novel stretchable substrate material and nine degree of freedom inertial sensors in conjunction with complex data analytics to detect joint movement. Our novel iSEG-Glove requires minimal calibration and is therefore particularly suited to the healthcare environment. Inaccuracies may arise for wearers who have varying degrees of movement in their finger joints, variance in hand size or deformities. The developed glove is fitted with sensors to overcome these issues. This glove will help quantify joint stiffness and monitor patient progression during the arthritis rehabilitation process.
The Real-Bills Doctrine versus the Quantity Theory: A Reconsideration

Two competing monetary policy prescriptions are analyzed within the context of overlapping generations models. The real-bills prescription is for unfettered private intermediation or central bank operations designed to produce the effects of such intermediation. The quantity-theory prescription, in contrast, is for restrictions on private intermediation designed to separate "money" from credit. Although our models are consistent with quantity-theory predictions about money supply and price-level behavior under these two policy prescriptions, the models imply that the quantity-theory prescription is not Pareto optimal and the real-bills prescription is.
Objective analysis of whole lung and lobar ventilation/ perfusion relationships in pulmonary embolism

Purpose: Lung scintigraphy using single photon emission computed tomography (SPECT) allows accurate regional measurement of the ventilation/perfusion () relationship. Objective analysis has been shown to be useful in the diagnosis of pulmonary embolism (PE). By using anatomical information provided by co‐registered computed tomography, we describe methodology for determining the extent of heterogeneity at a lobar level. We investigate this methodology using simulated data, and demonstrate its potential application in the clinical setting of PE.
Firm Complexity and Capital Structure: Evidence from Italian Diversified Firms

This paper examines the links between product diversification, international diversification and capital structure for a panel of medium and large Italian firms. The results indicate that the interaction between these two dimensions of diversification strategy has a negative and significant impact on leverage. Furthermore, debt maturity analysis reveals that firms pursuing a simultaneous dual diversification strategy have, in particular, lower long‐term debt ratios. Our findings support the hypothesis that the complexity that comes from diversification reduces debt levels. Copyright © 2014 John Wiley & Sons, Ltd.
Investor Sentiment in India: A Survey

In this paper we examine definitional aspect of Investor Sentiment, the key economic, market and regulatory factors that influence investor sentiment and the relationship between investor sentiment and market performance. There seems to be no clear consensus on the concept of investor sentiment and hence any meaningful definition ought to be inclusive and fluid. The important economic factors highlighted in the work are: Real GDP, Corporate Profits, Rate of Inflation, Level of Interest Rate, and Liquidity in the Economy. The market based factors that can be linked to Investor Sentiment are: Put Call Ratio, Advance Decline Ratio, Earning Surprises, P/E Ratio, and Price to Book Value. The regulatory framework of a financial market does seem to have a strong bearing on investor sentiment especially the legal provisions relating to corporate governance and Grievance Redressal Mechanism. Most respondents believe that investor's sentiment and market returns are bilaterally co-related. Our findings are largely in conformity with recent studies for other capital markets. These findings can be used to develop a comprehensive Investor Sentiment Index for India and hence have significant implications for investors, market intermediaries and financial regulators.
Exploring Closed Loop Supply Chain for Optimisation of Environmental Issues &amp; Total Profit Using System Dynamics

Nowadays, as companies are adopting strategies that are in a better balance with environmental friendly practices, so "Going Green" is becoming an effective strategy in terms of costs benefits and customer satisfaction. The focus of this paper is on the study of recollection in Closed Loop Supply Chain (CLSC), using system dynamics approach, by identifying and establishing relationships between variables in a CLSC system. A system dynamic model has been developed to simulate the influence of recollection on various factors like demand, sales, uncontrollable disposal, recycling rate, serviceable inventory, and the total profit. The results have indicated that, on a long term basis, closed loop supply chain can be successfully adopted to improve the cost benefits and to reduce the uncontrollable product disposals.
Measuring the Efficiency of Managerial and Technical Performances in Forestry Activities by Means of Data Envelopment Analysis (DEA)

Abstract The relation between the most productive scale size for particular input and output mixes and returns to scale for multiple-input multiple-output situations is explicitly developed. Data Envelopment Analysis (DEA) has been extensively applied in a range of empirical settings to identify relative inefficiencies, and provide targets for improvements. It accomplishes this by developing peer groups for each unit being operated (Decision Making Unit: DMU) This paper introduces the technique and focuses on some of the key issues that arise in applying DEA in practice. Some illustrations of the practical applications of these results to the estimation of most productive scale sizes and returns to scale for Forest Owner’s Associations (FOAs) at the local level in Japan are also provided to emphasize the advantage of this method in examining specific segments of the efficient production surface.
Demand Analysis of Meat in Malaysia

One distinct change in Malaysians' food consumption behavior has been the preference toward meat products. Thus it is meaningful to gain insight of meat consumption patterns. As the market becomes increasingly market-led, information on current meat consumption patterns is required to assess how they are likely to change as prices and incomes change. This study attempts to provide a better understanding of demand for meat products in Malaysia. By utilizing data from Household Expenditure Survey 2004/2005, Engel curve analysis was conducted to derive income elasticities of meat products from QUAIDS model. The estimated income elasticities show that current food consumption patterns are showing signs of convergence toward a Western diet, exhibiting tendency for preference toward red meats (mutton and beef) over white meats (poultry and pork). The estimated elastic own-price elasticities indicate that Malaysian consumers are sensitive to the change in prices of the meat products, with other things remain constant.
Estimating Quarterly Poverty Rates Using Labor Force Surveys: A Primer

The paper shows how Labor Force Surveys can be used effectively to estimate poverty rates using Household Expenditure Surveys and cross-survey imputation methods. With only two rounds of Household Expenditure Survey data for Morocco (2001 and 2007), the paper estimates quarterly poverty rates for the period 2001-2010 by imputing household expenditures into the Labor Force Surveys. The results are encouraging. The methodology is able to accurately reproduce official poverty statistics by combining current Labor Force Surveys with previous period Household Expenditure Surveys, and vice versa. Although the focus is on head-count poverty, the method can be applied to any welfare indicator that is a function of household income or expenditure, such as the poverty gap or the Gini index of inequality. The newly produced time-series of poverty rates can help researchers and policy makers to: (a) study the determinants of poverty reduction or use poverty as an explanatory factor in cross-section and panel models; (b) forecast poverty rates based on a time-series model fitted to the data; and (c) explore the linkages between labor market conditions and poverty and simulate the effects of policy reforms or economic shocks. This is a promising research agenda that can expand significantly the tool-kit of the welfare economist.
Learning from neighbours

When payoffs from different actions are unknown, agents use their own past experience as well as the experience of their neighbours to guide their decision making. In this paper, we develop a general framework to study the relationship between the structure of these neighbourhoods and the process of social learning. We show that, in a connected society, local learning ensures that all agents obtain the same payoffs in the long run. Thus, if actions have different payoffs, then all agents choose the same action, and social conformism obtains. We develop conditions on the distribution of prior beliefs, the structure of neighbourhoods and the informativeness of actions under which this action is optimal. In particular, we identify a property of neighbourhood structures—local independence—which greatly facilitates social learning. Simulations of the model generate spatial and temporal patterns of adoption that are consistent with empirical work.