Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison between the Therapeutic Effect of Metformin, Glimepiride and Their Combination as an Add-On Treatment to Insulin Glargine in Uncontrolled Patients with Type 2 Diabetes

Aims To compare the commonly prescribed oral anti-diabetic drug (OAD) combinations to use as an add-on therapy with insulin glargine in patients with uncontrolled type 2 diabetes despite submaximal doses of OADs. Methods People with inadequately controlled type 2 diabetes (n = 99) were randomly assigned on a 1∶1∶1 basis to receive insulin glargin, with fixed doses of glimepiride, metformin, and glimepiride plus metformin. Outcomes assessed included HbA1c, the changes in fasting glucose levels, body weight, serum lipids values, insulin dose and symptomatic hypoglycemia. Results After 24 weeks, HbA1C levels improved from (mean ± SD) 8.5±0.9% to 7.7±0.8% (69.0±10.0 mmol/mol to 60.8±8.6 mmol/mol) with insulin glargine plus metformin, from 8.4±1.0% to 7.7±1.3% (68.8±10.6 mmol/mol to 61.1±14.4 mmol/mol) with insulin glargine plus glimepiride and from 8.7±0.9% to 7.3±0.6% (71.7±9.8 mmol/mol to 56.2±6.7 mmol/mol) with insulin glargine plus glimepirde plus metformin. The decrease in HbA1c was more pronounced with insulin glargine plus glimepiride plus metformin than with insulin glargine plus metformin (0.49% [CI, 0.16% to 0.82%]; P = 0.005) (5.10 mmol/mol [CI, 1.64 to 8.61]; P = 0.005) and insulin glargine plus glimepiride (0.59% [CI, 0.13% to 1.05%]; P = 0.012) (5.87 mmol/mol [CI, 1.10 to 10.64]; P = 0.012) (overall P = 0.02). Weight gain and the risk of hypoglycemia of any type did not significantly differ among the treatment groups. Conclusion The combination therapy of metformin and glimepiride plus glargine insulin resulted in a significant improvement in overall glycemic control as compared with the other combinations. Trial registration information ClinicalTrials.gov, NCT00708578. The approval number of Kangbuk Samsung hospital's institutional review board (IRB): C0825.
An econometric analysis of charitable donations in the Republic of Ireland

This paper explores the variables that affect the probability of donating to charity and those that affect the size of donations by Irish households. The dataset employed is the Irish Household Budget Survey (HBS) 1999/2000, which is analysed using a tobit model and doublehurdle model with an inverse hyperbolic sine transformation of the dependent variable. To date, there has been no prior econometric analysis of charitable donations in the Republic of Ireland.
AN EMPIRICAL STUDY OF COMMUNITY AND FAMILY INTERVENTIONS TO PROMOTE PHYSICAL ACTIVITY AMONG LATINO YOUTH

Physical inactivity contributes to risks for chronic disease and premature death (World Health Organization, 2010). Community coalitions play an important role in addressing and preventing chronic diseases (Butterfoss, Goodman, & Wandersman, 1993). This dissertation examines two intervention efforts related to the Latino Health for All Coalition's action plan, using an ecological perspective (McLeroy, Bibeau, Steckler, & Glanz, 1988). The first study involved a universal intervention to promote physical activity among Latino boys and girls (age 5-15) in Kansas City by offering structured soccer sessions consisting of soccer drills and informal games. These structured soccer sessions were promoted though an informal, flyer-based campaign. An empirical case study design and related measures were used to answer four questions: 1) How effective was the campaign in attracting overweight and obese Latino youth? (involved analysis of a paper-and-pencil survey by parents of participating youth), 2) How frequently did participants attend? (involved analysis of weekly attendance records), 3) How much moderate-to-vigorous physical activity did participants accumulate during these informal soccer sessions? (involved the use of Actigraph accelerometers), and 4) How satisfied were parents and youth with these physical activity opportunities? (involved analysis of a paper-and-pencil survey at the concluding session). Results show that 74 youth attended at least one of the weekly soccer sessions (90.5% Hispanic/Latino, 43.2% overweight or obese). On average, youth attended 4.2 sessions; there was no difference in attendance rate by gender (t(40)=2.08, p=0.48) or body mass index category [F(2, 49) = 0.16, p = 0.85]. A convenience sample of 12 participants accumulated 18.8 to 22.2 minutes of moderate-to-vigorous physical activity during a single soccer session. Both children and parents expressed high levels of satisfaction with the structured soccer sessions. In conclusion, these structured soccer sessions enabled a diverse group of Latino children and youth to accumulate about a third of their daily requirement of physical activity, in an enjoyable way. The second study examined a targeted family-based intervention to promote physical activity in home settings. It involved Latino children (3 boys, 2 girls), ages 5 to 7. The intervention occurred during the summer (June - August). Parents were taught to set weekly physical activity goals for their children, develop weekly behavioral contracts, and reinforce short bouts of physical activity. Children wore Actigraph accelerometers during waking hours to monitor changes in physical activity levels. The U.S. Department of Health and Human Services guidelines for physical activity were reviewed with parents, followed by weekly accelerometer feedback on their child's physical activity level. A multiple baseline design was used to examine the effects of the intervention on daily levels of moderate-to-vigorous physical activity. The intervention resulted in large changes in physical activity…
Market concentration and productivity in the United States corn sector: 2002-2009

There is a large literature which investigates the relationship between market concentration and innovation. It is difficult to find a suitable measure for innovative output. We use a rich dataset based on university trials of corn hybrids to estimate, using fixed effects, a production function. We predict the fixed effects, by year and Crop Reporting District (CRD), for each hybrid to identify the amount of yield that is directly related to the genetics of the hybrids. We combine this dataset with one which provides information for market concentration, and find, using two stage least squares, that there is a positive relationship between market concentration and innovation.
Mice homozygous for c.451C>T mutation in Cln1 gene recapitulate INCL phenotype

Nonsense mutations account for 5–70% of all genetic disorders. In the United States, nonsense mutations in the CLN1/PPT1 gene underlie >40% of the patients with infantile neuronal ceroid lipofuscinosis (INCL), a devastating neurodegenerative lysosomal storage disease. We sought to generate a reliable mouse model of INCL carrying the most common Ppt1 nonsense mutation (c.451C>T) found in the United States patient population to provide a platform for evaluating nonsense suppressors in vivo.
Ungulate preference for burned patches reveals strength of fire–grazing interaction

The interactions between fire and grazing are widespread throughout fire-dependent landscapes. The utilization of burned areas by grazing animals establishes the fire–grazing interaction, but the preference for recently burned areas relative to other influences (water, topography, etc.) is unknown. In this study, we determine the strength of the fire–grazing interaction by quantifying the influence of fire on ungulate site selection. We compare the preference for recently burned patches relative to the influence of other environmental factors that contribute to site selection; compare that preference between native and introduced ungulates; test relationships between area burned and herbivore preference; and determine forage quality and quantity as mechanisms of site selection. We used two large ungulate species at two grassland locations within the southern Great Plains, USA. At each location, spatially distinct patches were burned within larger areas through time, allowing animals to select among burned and unburned areas. Using fine scale ungulate location data, we estimated resource selection functions to examine environmental factors in site selection. Ungulates preferred recently burned areas and avoided areas with greater time since fire, regardless of the size of landscape, herbivore species, or proportion of area burned. Forage quality was inversely related to time since fire, while forage quantity was positively related. We show that fire is an important component of large ungulate behavior with a strong influence on site selection that drives the fire–grazing interaction. This interaction is an ecosystem process that supersedes fire and grazing as separate factors, shaping grassland landscapes. Inclusion of the fire–grazing interaction into ecological studies and conservation practices of fire-prone systems will aid in better understanding and managing these systems.
Distance Variation Function for Simulation of Near-Field Virtual Auditory Space

We present a method for simulating a near-field sound source in virtual auditory space (VAS). The method scales individualised HRTFs, measured at a distance of Im to arbitrary distances in the near-field. It uses a model of the acoustic scattering for a point-source on a rigid sphere to calculate a distance variation function (DVF) to apply to the HRTFs. A sound localisation experiment was conducted in VAS with three subjects to evaluate the acoustic spatial fidelity of this method. Results show that with the modified HRTFs directional localisation is generally maintained at different distances and there is reasonable correlation between the perceived distance and target distance for distances up to 50 cm from the centre of the subject's head
CONJOINT ANALYSIS MODELLING OF STATE OF PREFERENCES. A REVIEW OF THEORY, METHODS, RECENT DEVELOPMENTS AND EXTERNAL VALIDITY

This paper reviews the state-of-the-art in the conjoint analysis paradigm for stated preference research. Communalities and differences among different conjoint analysis techniques are discussed, including the assumptions required to use the techniques and to simulate individuals' choices. The discussion is organised around rating, ranking and discrete response methods of collecting conjoint data. Recent advances in conjoint analysis are discussed, and particular attention is given to the design and analysis of discrete choice experiments. Limitations and problems in the use of conjoint techniques are outlined, and suggestions are made about directions for future research. (Author/TRRL)
Dysregulated but not decreased salience network activity in schizophrenia

Effective estimation of the salience of environmental stimuli underlies adaptive behavior, while related aberrance is believed to undermine rational thought processes in schizophrenia. A network including bilateral frontoinsular cortex (FIC) and dorsal anterior cingulate cortex (dACC) has been observed to respond to salient stimuli using functional magnetic resonance imaging (fMRI). To test the hypothesis that activity in this salience network (SN) is less discriminately modulated by contextually-relevant stimuli in schizophrenia than in healthy individuals, fMRI data were collected in 20 individuals with schizophrenia and 13 matched controls during performance of a modified monetary incentive delay (MID) task. After quantitatively identifying spatial components representative of the FIC and dACC features of the SN, two principal analyses were conducted. In the first, modulation of SN activity by salience was assessed by measuring response to trial outcome. First-level general linear models were applied to individual-specific time-courses of SN activity identified using spatial independent component analysis (ICA). This analysis revealed a significant salience-by-performance-by-group interaction on the best-fit FIC component's activity at trial outcome, whereby healthy individuals but not individuals with schizophrenia exhibited greater distinction between the response to hits and misses in high salience trials than in low salience trials. The second analysis aimed to ascertain whether SN component amplitude differed between the study groups over the duration of the experiment. Independent-samples T-tests on back-projected, percent-signal-change scaled SN component images importantly showed that the groups did not differ in the overall amplitude of SN expression over the entire dataset. These findings of dysregulated but not decreased SN activity in schizophrenia provide physiological support for mechanistic conceptual frameworks of delusional thought formation.
Face expression recognition using integrated approach of Local Directional Number and Local Tetra Pattern

Recognizing the human facial expression and emotion by computer is an interesting and challenging problem. This project proposes a method for facial expression recognition (FER) using Local Directional Number Pattern (LDN) and Local Tetra Pattern (LTrP). The proposed FER method removes the noise using Modified Decision Based Unsymmetrical Median Filter (MDBUTMF) method. The Local Directional Number (LDN) pattern descriptor is found based on the eight Gaussian edge descriptors. The proposed method encodes the relationship between the referenced pixel and its neighbors, based on the directions that are calculated using the first-order derivatives in vertical and horizontal directions. The training poses such as disgust, sad, smile and surprise are undergone the Gaussian mask generation, Gaussian edge detection, LDN process, LTrP process, MLDN histogram and LTrP histogram process. These training histograms are used to train up the facial expressions using Support Vector Machine (SVM). The SVM classifier classifies the facial expressions into disgust, sad, smile and surprise. The proposed method increases the FER accuracy at a significant level. The proposed method is a suitable one for any facial expression recognition needs.
Efficient background modeling using nonparametric histogramming

With rapid increase in the deployment of high-definition surveillance cameras, the need of efficient video analytics for extracting video objects from high-resolution surveillance videos in real time has become more and more demanding. Conventional background modeling methods, e.g., the Gaussian mixture modeling (GMM), although having long been proven to be effective for foreground object extraction, are actually not efficient enough for the real-time analysis of high-resolution videos. We thus propose a novel background modeling approach using nonparametric histogramming that can derive a holistic, histogram-based background model for each pixel with low computational complexity. Due to the simple algorithm design, the proposed approach can be easily implemented by fixed-point computation. Without using any accelerator (like CUDA, Intel SIMD, or Intel IPP library), multi-threading or sub-sampling technique, our implementation of the proposed algorithm achieves high efficiency for the processing of 1920×1080 color videos at ~18.81 fps on a general computer (Intel Core i7 3.4GHz CPU). In the experimental comparisons, the proposed approach is ~3.9 times faster than the GMM, while giving comparable foreground segmentation results.
Organization Development and Transformation: Managing Effective Change

Part 1 Mapping the territory: what is organizational development? a history of organization development general strategies for effecting change in human systems toward third-wave managing and consulting organization development and transformation estimating the success of OD applications. Part 2 Foundations of organization development and transformation: the field approach - culture and group life as quasi two-person disputes, intervention theory and method inter-group problems in organizations organizational culture sociotechnical system principles and guidelines - past and present. Part 3 Fundamental interventions: methods for finding out what's going on operation KPE - developing a new organization planning procedures/managing interfaces/charting responsibility when power conflicts trigger team spirit strategies for improving headquarters-field relations the confrontation meeting collateral organization - a new change strategy survey-guided development - using human resources managment in organizational change. Part 4 Cutting edge change strategies: successful self-directed teams and planned change - a lot in common survey guided appreciative inquiry - a case study inventing the future - search strategies for whole systems improvement meeting the global competitive challenge -building systems that learn on a large scale centres of excellence - empowering people to manage change building a learning organization teaching smart people how to learn. Part 5 Implementation guidelines and issues: the experience and evolution of trust - implications for cooperation and teamwork creating readiness for organizational change defining a political model of organizations functional roles of group members choosing the depth of organizational intervention rules of thumb for change agents facilitating transformational change. Part 6 Examples and special situations: creating successful organization change the employee-customer-profit chain at Sears creating excellence out of crisis - organizational transformation at the Chicago Tribune organization development in the entrepreneurial firm are organizational development interventions appropriate in turnaround situations? Part 7 Challenges and opportunities for the future: empowerment - the emperor's new clothes ethics and organizational change re-engineering the mature organization managing discontinuities - the emerging challenges seven practices of successful organizations from team building to community building the new agenda for organization development.
Pre-service teacher learning and practice for mathematical literacy.

This study explores the nature of pre-service Mathematical Literacy teachers' problem solving with a focus on intra-mathematics and extra-mathematics connections, across two years (2011-2012). The pre-service teachers were enrolled into a new three-year Bachelor of Education course, Concepts and literacy in mathematics (CLM), at a large urban University in South Africa. The CLM course aimed specifically at developing the teachers' fundamental mathematical knowledge as well as contextual knowledge, which were believed to be key components in ML teaching. The fact that the course offered a new approach to professional teacher development in ML (pre-service), contrasting the old model (in-service) reported in ML-related literature in South Africa, where qualified teachers from other subjects were reskilled, coupled with the need to grow the pool of qualified ML teachers, provided a rationale for conducting this study. Data relating to the pre-service teachers' responses to assessment tasks within the course, and their school practicum periods focusing on classroom mathematical working, combined with pedagogical orientations, was collected. PISA's (OECD, 2010, 2013) dimensions of the mathematisation process provided the theoretical framework while Graven and Venkat's (2007a) pedagogic agendas were used to make sense of the pedagogic orientations in practice. The results relating to both learning and practice suggest that the teachers' knowledge relating to model formulation, an aspect of extramathematics connections, was weak across the two years. Nevertheless, improvements in ways in which the dimensions ofthe mathematisation process occurred were noted across the two years, with localised errors. In terms of pedagogic agendas foregrounded by the teachers in ML classrooms, results indicate that agenda 2 (content and context driven) and agenda 3 (mainly content driven) featured more than agenda 1 (context driven) which supports the rhetoric in the ML curriculum. Two implications to teacher training have been noted; first the need for a focus on correctly translating quantities from problem situations into mathematical models, and secondly, the need for promotion of provision of solution procedures with pedagogic links. This study offers two key contributions namely; extending knowledge relating to pre-service ML teacher training, and extending theory for understanding steps in problem solving to incorporate aspects of pedagogy.
Coordination Control of Heterogeneous Compounded-Order Multi-Agent Systems with Communication Delays

Since the complexity of the practical environment, many distributed networked systems can not be illustrated with the integer-order dynamics and only be described as the fractional-order dynamics. Suppose multi-agent systems will show the individual diversity with difference agents, where the heterogeneous (integer-order and fractional-order) dynamics are used to illustrate the agent systems and compose integer-fractional compounded-order systems. Applying Laplace transform and frequency domain theory of the fractional-order operator, consensus of delayed multi-agent systems with directed weighted topologies is studied. Since integer-order model is the special case of fractional-order model, the results in this paper can be extend to the systems with integer-order models. Finally, numerical examples are used to verify our results.
Benchmarking domestic gas and electricity consumption to aid local authority carbon reduction policy

As part of an effort to be a world leader in international efforts in reducing atmospheric carbon dioxide levels, the UK Government has set itself ambitious targets to reduce carbon dioxide emissions by 80% relative to 1990 levels by 2050. To meet this target, there is a strong emphasis in reducing carbon emissions from the domestic sector through the reduction of energy consumption in UK households by improving the energy efficiency of the housing stock, and the behaviours of the occupants. The Department of Energy and Climate Change have indicated that Local Authorities in England are potentially to work in partnership with businesses and community organizations to facilitate delivery; and as a promoter of domestic energy efficiency policies. Consultation with 11 Local Authorities across England confirmed that they are lacking a reliable mechanism that can detect areas within their administrative boundaries that are most in need of intervention to improve the energy efficiency of the housing stock. For the year 2008 the regression models demonstrate that geographical variations in the size of the house, median household income, and air temperature account for 64% of the variation in English domestic gas consumption, and that variations in the size of the house, median household income, and proportion of households connected to the national gas grid account for 73% of the variation in domestic electricity consumption. The predicted values from these regression models serve as benchmarks of domestic gas and electricity consumption in England having accounted for household income, house size, house type, tenure, and climatic differences and could be used to identify areas within Local Authorities with higher than expected energy consumption for energy efficiency interventions. These results contribute to the wider academic debate over how best to achieve the overall aims of household CO2 reductions by moving beyond a purely technical or behavioural-based approach to reducing domestic energy consumption.