Miracle-dz/UniFAR-FTUs huggingface dataset:
A fast finite element solution for cloth modelling

We present an efficient model based on finite elements for viscoelastic, highly flexible surfaces. It is particularly designed for numerically stiff materials such as textiles because it yields linear equations in each time step and allows fast time stepping in an implicit integration method. This is achieved by reducing the nonlinear elasticity problem to a planar, linear one in each step. We apply this model to a garment simulation in which we assemble garments from CAD cloth patterns, seam these together, and animate the cloth in dynamic scenes with any chosen material properties. This results in a physically accurate but also fast simulation.
Multimodel and Vegetation Indices for Drought Vulnerability Assessment: A Case Study of Afar Region in Ethiopia

Drought is a water related climatic natural disaster affecting wide range of environmental, biological and social factors. Short, poor and delayed rainfall in 2015 caused critical water shortage, livestock causality and decline in milk production in the pastoral areas of Ethiopia. The relationship between rainfall and vegetation indices was analyzed to identify drought-vulnerable areas in Afar region of Ethiopia using 11 years time series of decadal NDVI, VCI, DSI and SPI using SPOT (2005-2013) and PROVA-V (2014-2015) data. For the validation of drought indices, correlation and regression analyses between NDVI and rainfall (r = 75%), NDVI and crop yield, and VCI and rainfall (r = 90%) were done. The findings showed that there was extreme drought in the Afar region in 2005, 2009, 2011 and 2015. The region was highly prone to drought, even though its severity levels varied in different years. Drought was severe, longer and intense in most of the areas in the region, adversely affecting agricultural productivity and livestock maintenance and management. Assessments of such natural disasters are useful to plan mitigative measures in advance for effective management programmes, including drought hazards.
Design of Post-Wall Feed Waveguide for a Parallel Plate Slot Array by an Analysis Model with Corrected Solid-Walls

A novel analysis model for post-wall waveguide T-junctions is proposed. Equivalent solid-walls for the post-walls to have equal guided wavelength are corrected in the analysis model so that the wall thickness for the coupling windows is set to the difference in the width between the post-wall and the solid-wall waveguides. The accuracy of the proposed model is confirmed by comparing it to an HFSS analysis for the real structure of the post-wall waveguide T-junction including the post surfaces. 61.25GHz model antennas are fabricated for experimental verification. The reflection of the antenna designed by the modified analysis model is suppressed to below −15dB over a 5.6GHz bandwidth, while that in the antenna designed by the conventional model is larger than −15dB around the design frequency.
Everybody Hurts: Addiction, Drama, and the Family in the Reality Television Show Intervention

This article employs the literature on reality television as well as empirical studies on addiction to analyze Intervention's narrative. We look at the narrative structure of the Intervention's first six seasons (2005–2009), its repeated emphases on the causes of addiction, and the show's purported success rate. Highlighting disturbing discrepancies between the show's representations and assertions versus empirical research, Intervention's notions of what constitutes effective remedies are those treatments generally available only to the financially affluent, and the program's depictions of addiction and intervention practices reinforce a popular culture, rather than a science-based understanding, of the family and of addiction itself.
LAANT: A library to automatically optimize EDP for OpenMP applications

Efficiently exploiting thread level parallelism from new multicore systems has been challenging for software developers. While blindly increasing the number of threads may lead to performance gains, it can also result in disproportionate increase in energy consumption. For this reason, rightly choosing the number of threads is essential to reach the best compromise between both. However, such task is extremely difficult: besides the huge number of variables involved, many of them will change according to different aspects of the system at hand and are only possible to be defined at run-time. To address this complex scenario, we propose LAANT, a novel library to automatically find the optimal number of threads for OpenMP applications, by dynamically considering their characteristics, input set, and the processor architecture. By executing nine well-known benchmarks on three real multicore processors, LAANT improves the EDP (Energy-Delay Product) by up to 61%, compared to the standard OpenMP execution; and by 44%, when the dynamic adjustment of the number of threads of OpenMP is activated.
Asset allocation and optimal selling rule with regime switching and partial observation

Regime Switching model was receiving increasing attention as researchers searching good models to capture prices of financial assets. Using a regime switching model we study asset allocation problem with one risk free asset and one risky asset. We characterize the value function in terms of solutions of a partial differential equation. We use Viscosity solution and Markov chain approximation for its numerical solution. The second part is concerned with stock selling rule. We use our regime switching model to find the optimal timing to sell under a logarithmic utility function. A key component in this thesis is that we consider the models with partial information. We resort to Wonham filter to recover necessary information required for optimal control of the problems under consideration. Index words: Asset allocation, regime switching, optimal selling time Asset allocation and optimal selling rule with regime switching and partial observation
The importance of key supplier relationship management in supply chains

Purpose: This paper investigates the impact of key supplier relationship management (KSRM) – understood as an aggregated supply chain management (SCM) process in the upstream direction – on the overall level of the execution of SCM within organizations. Methodology: A conceptual model is developed from a theoretical framework and proposes the capability to do KSRM as a mediator between internal and external SCM resources and SCM execution. A survey of 174 managers representing different supply chain stages is used to test the model through variance-based structural equation modelling. Findings: The findings reveal that external SCM resources directly affect the capability to do KSRM. Nevertheless, internal resources show a considerable indirect impact through external resources and can thus be considered an indirect determinant. The capability to do KSRM in turn impacts upon the level of SCM execution, measured in terms of the integration of business processes, directly and substantially, as well as mediating the effect between SCM resources and the level of SCM execution. Value: The main contribution of this paper is to empirically demonstrate the potential of KSRM for enhancing the level of SCM execution within organizations and consequently the level of integration in supply chains, leading to higher customer and shareholder value.
Research as Curriculum: Engaging Undergraduates and Community Residents in Immigrant Health Research Partnerships

<p class="summaryheading"><span class="summaryheading">Background:</span></p><p> Engaging undergraduate students in applied community research partnerships can promote greater health equity by providing students with the skills and capacity to work collaboratively with diverse populations. </p><p><b>Objectives:</b> The aim of this project was to develop a sustainable model to engage community members and students in public health research. </p><p><b>Methods:</b> Using an integrated research-as-curriculum model, students, community members, and faculty collaborated on the study design and implementation. </p><p><b>Conclusions:</b> Community residents in the classroom provided insights that strengthened the research process and helped to develop our understanding of contextual factors that influence health and well-being. This model provides a mechanism by which to fully incorporate undergraduate students in interdisciplinary partnership research for health. </p>
Pricing Guarantee Option Contracts in a Monte Carlo Simulation Framework

This thesis focuses on the valuation of guarantee option contracts of two life insurance products (LOGA and Levensloop Rendement) by using Monte Carlo simulation procedures. The option contracts are in-the-money for a specific client if this client is alive and the underlying asset portfolio has not reached the guarantee value at the specified end date. In this research project option values are derived in a Black-Scholes model, where asset prices are simulated, and in a Hull-White Black-Scholes model, where the short term interest rate is simulated as well. Since simulation time becomes a constraint for large client portfolios, I check whether the overal simulation time can be reduced by aggregating client portfolios, by using antithetic variables, and by simulating under another measure. Furthermore I check to what input parameters the option values of both individuals dummy clients and the entire portfolio are most sensitive. Finally, I propose an alternative life-cycle investment mix for the Levensloop Rendement product. Within the Black-Scholes setting it is derived that in case of a low volatility level and a large interest rate parameter the option value is lowest for the LOGA product. The analysis in this setting for the Levensloop Rendement product is only based on the interest rate parameter. It shows low option values for high interest rate levels. Aggregation of client portfolios is investigated in the same setting. It turns out to be effective for the LOGA portfolio, but highly inaccurate for the Levensloop Rendement product. Antithetic variates, however, work well for both products in this setting. In the Hull-White Black-Scholes model, results for the option values are derived as well. For the entire client portfolios these values are especially sensitive to interest rate related parameters. In the context of variance reduction, antithetic variables still work in this setting, but less effectively. The T-forward measure (instead of the risk-neutral measure), however, turns out to be extremely effective for dummies having a contract with a long time to maturity. These dummies also indicate that the option value as well as its sensitivities are very client related. By implementing a more defensive life-cycle investment strategy in the Levensloop Rendement product very different results are derived in comparison with the values of the original mix. The option value is lowered a lot, while it is in general relatively more sensitive to changes in the underlying parameter values.
Fair value impairment testing under IFRS : examining Australia's disclosure quality

This paper examines the use of the fair value approach to impairment testing pursuant to IFRS by a sample of large listed Australian corporations. A mounting body of literature has criticised the theoretical and technical foundations of the IFRS mandated impairment testing process. This paper adds to that literature by examining the quality of impairment testing disclosures of firms that tested for impairment on a fair value basis rather than the more common value in use approach. We find that these firms tended to have greater levels of goodwill, yet exhibited lower rates of impairment recognition. We also document systematic deviations between mandated disclosures relating to impairment testing and those actually produced by firms in our sample.
Power Allocation for a Downlink Non-Orthogonal Multiple Access System

This letter investigates power allocation for a downlink non-orthogonal multiple access system with a base station and two users. We first formulate an optimization problem for the single-input single-output (SISO) case in terms of power allocation between two users for maximizing the sum capacity under a total power constraint and a quality-of-service condition that the minimum rate requirement of each user is satisfied. Two closed-form solutions are subsequently derived. Then we extend the SISO solutions to a multiple-input multiple-output scenario. As compared to the optimal and the suboptimal approach presented in a recent work, the proposed schemes achieve close sum capacity performance with much lower computational complexity.
The Challenge of Teaching Marketing to Small Businesses

Looks at the recent development of the teaching of marketing to the owners and managers of small business. Considers the requirements of education of small businesses and the differences that arise. Investigates the attempts of the marketing group of the University of Ulster, Northern Ireland, to meet these requirements. Concludes that success for marketing educators can only be achieved by practising marketing in the design and conduct of their programmes.
A barycentric coordinate based approach to formation control of multi-agent systems under directed and switching topologies

This paper studies the formation control problem for a leader-follower network in 3D. The objective is to control the agents to form a globally rigid formation, for which the sensing graph is directed and switching while the communication graph is undirected and switching. Under such a setup, a barycentric coordinate based approach is proposed for the design of formation control laws ensuring global convergence. A necessary and sufficient graphical condition is obtained to guarantee that the followers converge to form a globally rigid formation together with the leaders. By this approach, the formation of the whole group, namely, the orientation, translation and formation scale, can be reconfigured by the leaders.
DO EARLY PERCEPTIONS OF STRATEGIC DECISIONS INFLUENCE STRATEGIC PROCESSES?: AN EMPIRICAL INVESTIGATION.

This paper investigates the impact of perceived decision-specific characteristics on the processes followed in making Strategic Decisions (SDs). It empirically derives generic decision-specific characteristics (e.g. magnitude of impact, crisis, pressure, familiarity, emergence) and decision-process dimensions (e.g. comprehensiveness, politicization. decentralization). Results support that SDs with different characteristics are handled through different processes.
The Impact of Expectations Manipulation on the Usefulness of Analyst Forecasts in Firm Valuation*

This paper examines the impact of expectations manipulation on the usefulness of analyst forecasts in the residual income valuation model. Recognizing that firms may guide down analyst forecast to either truthfully communicate information (legitimate guidance) or mislead analysts to produce beatable forecasts (expectations manipulation), this study first develops a measure to isolate expectations manipulation from the overall forecast guidance. It then assesses forecast usefulness by the performance of forecast-based intrinsic value metrics (V) to predict firm value. The results show that V estimated using manipulated forecasts have less ability to explain stock price and predict future returns. These results remain after controlling for firm size, earnings performance, forecast accuracy, etc. Based on these findings, I conclude that expectations manipulation reduces the usefulness of analyst forecasts in firm valuation, as it impairs the performance of forecast-based valuation models to predict firm value.
Future strategies in the management of dyslipidemia.

R Birjmohun, MD, E Stroes, MD, PhD, J Kastelein†, MD, PhD †Author for correspondence Academic Medical Center of Amsterdam, Department of Vascular Medicine, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands Fax: +31 020 566 9343; e.vandongen@amc.uva. nl ‘Low HDL-C is the most frequent lipid abnormality in patients with premature CHD. Based on epidemiological data, it has been estimated that coronary risk increases by 1–3% for every 1% reduction of HDL-C levels. ’
Community- and ecosystem-level changes in a species-rich tallgrass prairie restoration

Changes in the plant community and ecosystem properties that follow the conversion of agriculture to restored tallgrass prairies are poorly understood. Beginning in 1995, we established a species-rich, restored prairie chronosequence where ∼3 ha of agricultural land have been converted to tallgrass prairie each year. Our goals were to examine differences in ecosystem properties between these restored prairies and adjacent agricultural fields and to determine changes in, and potential interactions between, the plant community and ecosystem properties that occur over time in the restored prairies. During the summers of 2000–2002, we examined species cover, soil C and N, potential net C and N mineralization, litter mass, soil texture, and bulk density across the 6- to 8-year-old prairie chronosequence and adjacent agricultural fields in southern Minnesota. We also established experimentally fertilized, watered, and control plots in the prairie chronosequence to examine the degree of nitrogen limitation on aboveground and belowground net primary production (ANPP and BNPP). Large shifts in functional diversity occurred within three growing seasons. First-year prairies were dominated by annuals and biennials. By the second growing season, perennial native composites had become dominant, followed by a significant shift to warm-season C4 grasses in prairies ≥3 yr old. Ecosystem properties that changed with the rise of C4 grasses included increased BNPP, litter mass, and C mineralization rates and decreased N mineralization rates. ANPP increased significantly with N fertilization but did not vary between young and old prairies with dramatically different plant community composition. Total soil C and N were not significantly different between prairie and agricultural soils in the depths examined (0–10, 10–20, 20–35, 35–50, 50–65 cm). We compared the results from our species-rich prairie restoration to published data on ecosystem function in other restored grasslands, such as Conservation Reserve Program (CRP) and old-field successional sites. Results suggest that rapid changes in functional diversity can have large impacts on ecosystem-level properties, causing community- and system-level dynamics in species-rich prairie restorations to converge with those from low-diversity managed grasslands.
Analysing the Impacts of Various Environmental Parameters on the Biodiversity Status of Major Habitats

Background: Anthropogenic impacts on the environment often result in loss of biodiversity. However, the effects of different parameters (such as soil pH) on biodiversity, which can be influenced by human activities, are poorly investigated on a global scale. The paper at hand proposes an approach to examine the relationship between biodiversity and several parameters, which can be anthropogenically influenced, on a major habitat scale. The goal is to describe the relationship of a single parameter and biodiversity by means of a mathematical model within one major habitat. Methods: Geographic information system (GIS) data for the parameters “mean soil pH”, “mean share of cultivated land” and “mean temperature in June” for the whole world were overlaid with GIS data for the ecoregions proposed by the World Wide Fund for Nature (WWF). By means of the software ArcGIS 10.4 (Esri Deutschland GmbH, Kranzberg, Germany), an average parameter value per ecoregion for all considered parameters was determined. Moreover, the index “biodiversity status” was introduced and determined for every ecoregion by means of the indicators “number of species”, “number of endemic species”, and “mean share of grassland and forest” for each ecoregion. As all ecoregions can be assigned to one of the 14 major habitats (as defined by the WWF), a Kruskal–Wallis test was conducted to analyse whether the parameters and the biodiversity status’ differentiate between the 14 major habitats. A mathematical model, which depicts the impact of the parameters on biodiversity, was established by means of curve fitting. Results: The Kruskal–Wallis test reveals that a significant difference (p-value of 0.000) regarding the considered parameter and the biodiversity status exists between the different major habitats. By means of a regression analysis and curve fitting, mathematical models were developed which describe the relation of the biodiversity status and the parameters for 14 major habitats.
A Heckman Sample Selection Approach to the Demand for Organic Food Products: An Exploratory Study Using Penang Data

Heckman's sample selection analysis is used on survey data in Penang, Malaysia, to examine sociodemographical and attitudinal factors affecting purchase decisions and expenditures on organic food products (OFP). Results of the marginal effects indicate that Chinese, affluent, and those who do not consider price to be a major factor have higher probabilities to spend and expend more on OFP. While Malays, females, and those with concerns about chemical additives and who consume monthly health supplements are likelier purchasers, those who perceive a lack of availability in the market are less prone to procure OFP. Last, individuals between 31–56 years and with more children spend in larger amounts compared to others.
A Recurrent Neural Network Approach to Rear Vehicle Detection Which Considered

Experimental vision-based detection often fails in cases when the acquired image quality is reduced by changing optical environments. In addition, the shape of vehicles in images that are taken from vision sensors change due to approaches by vehicle. Vehicle detection methods are required to perform successfully under these conditions. However, the conventional methods do not consider especially in rapidly varying by brightness conditions. We suggest a new detection method that compensates for those conditions in monocular vision-based vehicle detection. The suggested method employs a Recurrent Neural Network (RNN), which has been applied for spatiotemporal processing. The RNN is able to respond to consecutive scenes involving the target vehicle and can track the movements of the target by the effect of the past network states. The suggested method has a particularly beneficial effect in environments with sudden, extreme variations such as bright sunlight and shield. Finally, we demonstrate effectiveness by state-dependent of the RNN-based method by comparing its detection results with those of a Multi Layered Perceptron (MLP).
Brand Introduction Strategies and Competitive Environments

Drawing on research in marketing strategy and industrial organization economics, the authors develop a model to describe the impact of strategies for introducing a new brand, aspects of the competitive environment, and firm characteristics on the performance of new brands. They test the model for 68 new brands in the pharmaceutical industry using a nested error component model. The results indicate which factors affect brand introduction strategies in marketing.
Effects of luteolin on the inhibition of proliferation and induction of apoptosis in human myeloid leukaemia cells

Luteolin, a flavonoid isolated from the fruit of Vitex rotundifolia, has been examined with regard to the inhibition of proliferation and induction of apoptosis in human myeloid leukaemia HL‐60 cells. The concentration required for 50% inhibition of the growth after 96 h was 15 ± 1.1 μM. The mode of cell death induced by luteolin was found to be apoptosis, as judged by the morphologic alteration of the cells and by the detection of DNA fragmentation using agarose gel electrophoresis. The degree of apoptosis was quantified by a sandwich enzyme immunoassay and flow cytometric analysis. These results suggest that luteolin may be used as potential chemopreventive and chemotherapeutic agents. Copyright © 2002 John Wiley & Sons, Ltd.