Miracle-dz/UniFAR-FTUs huggingface dataset:
The Volumetric Analysis of the Human Body as Starting Point for Clothing Pattern Design

The paper presents evaluation of the overall and microclimatic volume changes due to different upper limb positions simulating functional reaching movements for the aircrew personnel. The study was performed in order to evaluate the needed ease allowance added to chest and waist circumference for outerwear garments in order to fully achieve the wearing comfort. The accurate 3D body scanning was used and the impact of the upper limb position on microclimatic volume distribution was tested. The scanning data process was performed using a 3D laser scanner and a computer analysis. The raw scans were processed and reconstructed. After the scan reconstruction, the volume and the area were calculated. The experimental study covered the objective measuring methods: the material testing, the 3D scanning, the scan reverse engineering modelling and the volume/area calculation. The volume calculations included both the overall volume calculation for the unclothed torso and for the torso dressed in the chosen outerwear jacket. It also included the volume calculation of an air layer formed between second and third layered garments. The clothing ensemble CE 0 is the control variable, the unclothed body. The CE 1 is the clothing ensemble combined from the underlying basic garments (undershirt, underpants, classical male business shirt, and jeans) and combined with the bomber jacket. The three human subjects with the analogous body proportions (the height of 185 cm and chest girth of 100 cm) were scanned using the 3D laser body scanner Vitus Smart (Human Solutions GmbH) in an upright standing position according to ISO 20685:2010 changing only upper limb positions simulating functional reaching movements for the aircrew personnel.
Modelling time series with conditional heteroscedasticity

Over the last fifteen years, the interest in nonlin ear time series models has been steadily increasing. Univariate time-series models may not w rk successfully if they restrict only to linear functions of past observations. The same past may well contain useful information for the present and future if the depen dence is nonlinear. Among nonlinear functions we shall consider the simplest of the fam ily of heteroscedastic models the autoregressive conditional heteroscedastic or ARCH model that is based on the conditional variance structure. This model was firs t applied by Engle (1982) to estimate the variance of U.K. Inflation. The aim of this art icle is to find out whether ARCH models should also be applied to quarterly time series of the Portuguese Imports (escudos) for the period 1976 – 2004.
Assessments of Recent GRACE and GOCE Release 5 Global Geopotential Models in Canada

The objective of this study is to assess the recent GRACE and GOCE release 5 (R5) global geopotential models (GGM) in Canada. For the evaluation of the GGM against GPS-Levelling data and deflections of the vertical, the satellite models need to be combined with terrestrial gravity data to determine highresolution geoid models. This process allows a significant reduction of the omission error in the satellite gravity models. The geoid computation is founded on the remove-compute-restore Stokes-Helmert scheme, in which the Stokes kernel function modification is used to constrain the regional geoid models to the spectral bands of the satellite model to be assessed. The resulting geoid models are directly comparable to the GPS-Levelling data, and these same geoid models can be used to derive deflections of the vertical which are compared to astronomic deflections. The data analysis indicates that the GOCE R5 models provide better precision than the GOCE release 4 (R4) models beyond degree and order 180. The accuracy of the GOCE R5 models is estimated to be better than 4-5 cm up to spherical harmonic degree ~200. The astronomic deflections appear not accurate enough to measure improvements in the GOCE R5 models with respect to the GOCE R4 models. For the validation of GGM against terrestrial gravity data over land, EIGEN-6C4, which includes a GOCE R5 model, is assessed in contrast to EGM2008. Our analysis infers that the GOCE contribution in EIGEN-6C4 is more accurate than the corresponding wavelength components in EGM2008, which includes the Canadian terrestrial gravity data.
Dynamic Model of Capital Structure for the Noncorporate Firm

A dynamic model of capital structure for the noncoiporate farm is developed and analyzed. In this model. the probability of bankruptcy increases as the farmer's debt/asset ratio increases. Funds invested outside agriculture earn a risldess rate of return. The farmer/proprietor is also able to obtain a riskless wage from off-fann employment; this wage may differ from the implicit wage received as a farmer. The expected return to equity on the farm depends on the leverage. The model examines the effects on optimal capital snucture of (I) bankruptcy risk. (2) the difference between the riskless rate and the expected renun in agriculture, and (3) the difference between the off.farm wage and the implicit on-farm wage. The third element introduces an incentive for the prq>rietor to change leverage over the proprietor's lifetime; this ocrurs if the difference between the wages is nonzero but C<Xlstant. If the difference between the wages is z.ero, a constant leverage is optimal under reasonable circumstances. The model predicts that older farmers require more leverage to induce them to remain in fanning and that they tend to reduce their leverage as retirement approaches. The model is tested with cross-sectional data.
Subjective Well-Being and Universal Cultural Patterns: A Cross-Cultural Study

Until now it has not been analysed in previous research if and how cultures affect the well-being of people. It was the aim of this investigation to find conform and different patterns of subjective cultural well-being in the examined cultures of Bulgaria, France, Germany and China. Overall, 280 test persons from these countries were surveyed, namely 70 persons from each country. These samples are connected with different cultural traditions. A cohort design was used with subject to age and sex to assure comparability and to be able to meet the demands for a variance analysis. Overall, the results show that the relationships between the cultural patterns and the subjective specific well-being are not as strong as assumed, but significant. The sociodemographic variables do not influence subjective well-being.
Tradeoffs in Accuracy and Efficiency in Supervised Learning Methods

ABSTRACT Words are an increasingly important source of data for social science research. Automated classification methodologies hold the promise of substantially lowering the costs of analyzing large amounts of text. In this article, we consider a number of questions of interest to prospective users of supervised learning methods, which are used to automatically classify events based on a pre-existing classification system. Although information scientists devote considerable attention to assessing the performance of different supervised learning algorithms and feature representations, the questions asked are often less directly relevant to the more practical concerns of social scientists. The first question prospective social science users are likely to ask is, How well do such methods work? The second is, How much human labeling effort is required? The third is, How do we assess whether virgin cases have been automatically classified with sufficient accuracy? We address these questions in the context of a particular dataset—the Congressional Bills Project—which includes more than 400,000 bill titles that humans have classified into 20 policy topics. This corpus offers an unusual opportunity to assess the performance of different algorithms, the impact of sample size, and the benefits of ensemble learning as a means for estimating classification accuracy.
Purchasing in Construction Companies Bildsten

A significant part of the cost of a construction project, up to 90%, consists of purchased goods and services. Suppliers thereby have a large impact on the quality, price and time of projects. Purchasing management is therefore important for the outcome of a project. The aim of research covered by this thesis is to describe and analyse purchasing management and its interrelation with the supplier relationships and the production process. The research design was twofold: theory building and case studies. In the latter, the initial phase was inductive through studies of industrialized building, changing to abductive and, thereafter, deductive when tentative theories were tested within construction companies. The findings were that maintaining supplier relationships and, at the same time, retaining competition with several suppliers are desirable. The construction industry has been portrayed by some researchers as price-driven with respect to the choice of suppliers. The research reveals that the choice of suppliers is based to a large extent on long-term relationships, where the trustworthiness of suppliers plays an important part. Through long-term relationships, the project team can rely on the experiences acquired from previous purchases to overcome problems of coordination, communication and integration. It is important for construction companies to recognize that the project team possesses significant knowledge about the nature of services and products delivered by different subcontractors and suppliers. Decisions that are not made in collaboration with those involved in production can lead to lower quality, higher cost and later project delivery than might otherwise be the case. A combination of skills purchasing and construction seems appropriate for project managers. The theoretical contributions of the research consist of: (1) a framework on waste and coordination; (2) a framework comparing value-driven and market-driven purchasing; (3) a portfolio matrix considering the aspects of intensity and time perspective in purchaser-supplier relationships; (4) a framework to serve as a guide to describe and analyse the purchasing process in the companies that were examined; and (5) a portfolio matrix to portray purchasing in construction companies based on the findings.
Common Factor Analysis or Components Analysis: An Update on an Old Debate.

Both common factor analysis and components analysis are useful techniques for reducing the number of variables in a data set or for identifying underlying covariance structures that exist among a set of variables. Although researchers have for some years debated the appropriateness of selecting one of these methods over the other, components analysis has traditionally been the dominant strategy among educational researchers. Following a brief overview of the logic of factor analysis, a review of several studies comparing the common factor and principal components methods is presented. Actual educational research data are used to demonstrate cases in which the two methods will produce different results. Data used in these analyses were collected from 70 preservice and inservice teachers using a 3-subscale "logic of confidence" measure developed by K. R. Okeafor and others (1987). Guidelines are presented to assist the researcher in determining which method to use in specific research situations. Six tables illustrate the analyses. A 49-item list of references is included. (Author/SLD) Reproductions supplied by EDRS are the best that can be made from the original document.
Intellectual capital disclosure determinants and its effects on the market capitalization: evidence from Indonesian listed companies

Currently, intellectual capital (IC) is the main source of company’s competitive advantage. The role of IC has become one of the main factors of company’s value creation process. Since companies rely more on their intangibles (including IC), management must provide an appropriate annual report in which discloses information regarding IC in order to give better information to the related parties. The aim of this study is to examine variables that expected to have a significant influence to the level of intellectual capital disclosure (ICD) practices in Indonesian listed companies’ annual reports. A content analysis method is used to examine the ICD level, based on the framework developed by [1]. The IC information was collected from 135 Indonesian LQ45 listed companies, which derived from their annual reports from the year 2012 to 2014. Sample companies are classified into two groups of industries: high- and low profile industries in order to analyze differences in IC reporting practices between the two groups. The empirical results proved that company size, industry type and market capitalization are significantly associated with the ICD, while the influence of company profitability on the level of ICD is not significant. Furthermore, it is revealed that there is no significant difference in the intellectual capital disclosure practices between companies in high- and low-profile industries.
Robust Constraints on Past CO2 Climate Forcing From the Boron Isotope Proxy

The atmospheric concentration of the greenhouse gas carbon dioxide, CO2, is intimately coupled to the carbon chemistry of seawater, such that the radiative climate forcing from CO2 can be changed by an array of physical, geochemical, and biological ocean processes. For instance, biological carbon sequestration, seawater cooling, and net CaCO3 dissolution are commonly invoked as the primary drivers of CO2 change that amplify the orbitally paced ice age cycles of the late Pleistocene. Based on first‐principle arguments with regard to ocean chemistry, we demonstrate that seawater pH change (ΔpH) is the dominant control that effectively sets CO2 radiative forcing (ΔF) on orbital timescales, as is evident from independent late Pleistocene reconstructions of pH and CO2. In short, all processes relevant for CO2on orbital timescales, including temperature change, cause pH to change to bring about fractional CO2 change so as to yield a linear relationship of ΔpH to CO2 climate forcing. Further, we show that ΔpH and CO2 climate forcing can be reconstructed using the boron isotope pH proxy more accurately than absolute pH or CO2, even if seawater boron isotope composition is poorly constrained and without information on a second carbonate system parameter. Thus, our formalism relaxes otherwise necessary assumptions to allow the accurate determination of orbital timescale CO2 radiative forcing from boron isotope pH reconstructions alone, thereby eliminating a major limitation of current methods to estimate our planet's climate sensitivity from the geologic record.
Cortaderia sp. in New Zealand: patterns of genetic variation in two widespread invasive species

Cortaderia selloana (pampas grass) and C. jubata (purple pampas grass) are both invasive in New Zealand. Cortaderia selloana is found throughout most of the country, whereas C. jubata is restricted to the North Island and the northern South Island. We examine the genetic variation present in each of the species, and compare this to the findings of an earlier study that analysed the variation in invasive C. jubata plants from New Zealand. Cortaderia selloana is comprised of two main genetic groupings in New Zealand, one of which is more common than the other. The distribution of these two genetic groupings is discussed with respect to introduction history. Cortaderia jubata has considerably more genetic variation than expected, higher than estimated by a previous work. We discuss these results in the context of Cortaderia invasion in New Zealand and how this may impact on the design of a biocontrol programme.
The Impact of Human Capital on Economic Growth in Ethiopia

In contemporary economics literatures human capital accumulation is considered as one of the major determinants of economic growth. To this effect, this study used empirical econometric model to analyse the impact of education and health (human capital) on economic growth from 1980-2013 in Ethiopia. Human capital stock is proxied by primary, secondary and tertiary school enrolment. Human capital investment is proxied by expenditure on education and health. Augmented Dickey Fuller test and Johansen’s Co-integration technique were used to test unit root and to validate co-integration among variables, respectively. The findings of the study have shown public expenditure on health and education, primary and secondary school enrolment have positive statistically significant effect on economic growth both in long run and short run. In addition, physical capital has positive whilst inflation has negative effect on economic growth. However, tertiary school enrolment has insignificant effect on economic growth both in long run and short run. Based on these findings exceling an effort to increase primary and secondary school enrolment is recommended. In addition, substantial amount of government expenditure should be allocated towards health and education sectors to further increase contribution of the sectors to economic growth. Keywords : Economic Growth, Health, Education, Time Series Model, Human Capital
Hub-Induced Synchronization in Scale-Free Networks with Cluster Structure

A recent research indicated that the corticocortical connectivity network of the cat possesses cluster structure and that each cluster in the network is scale-free and has a most connected hub. Motivated by that research, we slightly modify the network model and derive sufficient conditions for cluster synchronization of the modified network based on Lyapunov function method. The obtained results indicate that cluster synchronization can be induced by the hubs of the scale-free networks. In our opinion, the concept of hub-induced synchronization provides a better understanding of cluster synchronization in scale-free networks. Numerical examples are provided to demonstrate the effectiveness of the theoretical results.
The Marginal Willingness-to-Pay for Health Related Food Characteristics

With food, consumers often face a trade-off between taste and nutrition. A priori, it is not obvious which would be more important to the average consumer, so it is an empirical question how consumers value food characteristics that simultaneously affect taste and nutritional value. In this paper, Swedish consumer preferences regarding food characteristics in breakfast cereals, hard bread and potato products are analyzed. In particular, the value consumers attach to fat, fibre, salt and sugar is studied, as well as the value of easily accessible nutritional information provided by a nutrition symbol. The equations estimated are derived from a hedonic price model. The price data originates from a household panel and scanner data, whereas the corresponding data on food characteristics was collected manually in supermarkets or from producers. The value consumers attach to food characteristics are found to vary by product and the results also imply that these values could be sensitive to changes in the combination of characteristics in a product.
Reducing Embodied Carbon in the Built Environment: A Research Agenda

In spite of significant global efforts, the International Energy Agency suggests that buildings-related emissions are on track to double by 2050. Whilst operational energy efficiency continues to receive significant attention by researchers, a less well-researched area is the assessment of embodied carbon in the built environment in order to understand where the greatest opportunities for its mitigation and reduction lie. This paper reports on available mitigation strategies to tackle embodied carbon identified through a systematic review of the available academic evidence. It also investigates the scope and scale of current academic investigations to highlight where significant gaps are for impactful further research on the topic. In total, 17 mitigation strategies have been identified from within the existing literature which have been discussed individually. Results reveal that a one-size-fits-all approach is unlikely to yield beneficial results and future research should be diverse in breadth and scope, locally accurate, and significantly interdisciplinary.
Output and Economic Growth in G 7 Countries : New Evidence from Asymmetric Panel Causality Testing

Recent studies have shown increasing interest on the relationship between research output and economic growth. The study of such a relationship is not only of theoretical interest, but it can also influence specific policies to improve the quality, and probably the quantity of research output. This paper has studied this relationship in G7 countries using the asymmetric panel causality test of Hatemi-J (2011). Our results show that only the United Kingdom shows a causal relationship from the output of research to real GDP. However, when the signs of variations are taken into account, there is an asymmetric causality running from negative research output shocks to negative real GDP shocks. JEL Classification: C33, O3, O4
Measuring dark energy with the $E_{\rm iso}-E_{\rm p}$ correlation of gamma-ray bursts using model-independent methods

In this paper, we use two model-independent methods to standardize long gamma-ray bursts (GRBs) using the $E_{\rm iso}-E_{\rm p}$ correlation, where $E_{\rm iso}$ is the isotropic-equivalent gamma-ray energy and $E_{\rm p}$ is the spectral peak energy. We update 42 long GRBs and try to make constraint on cosmological parameters. The full sample contains 151 long GRBs with redshifts from 0.0331 to 8.2. The first method is the simultaneous fitting method. The extrinsic scatter $\sigma_{\rm ext}$ is taken into account and assigned to the parameter $E_{\rm iso}$. The best-fitting values are $a=49.15\pm0.26$, $b=1.42\pm0.11$, $\sigma_{\rm ext}=0.34\pm0.03$ and $\Omega_m=0.79$ in the flat $\Lambda$CDM model. The constraint on $\Omega_m$ is $0.55<\Omega_m<1$ at the 1$\sigma$ confidence level. If reduced $\chi^2$ method is used, the best-fit results are $a=48.96\pm0.18$, $b=1.52\pm0.08$ and $\Omega_m=0.50\pm0.12$. The second method is using type Ia supernovae (SNe Ia) to calibrate the $E_{\rm iso}-E_{\rm p}$ correlation. We calibrate 90 high-redshift GRBs in the redshift range from 1.44 to 8.1. The cosmological constraints from these 90 GRBs are $\Omega_m=0.23^{+0.06}_{-0.04}$ for flat $\Lambda$CDM, and $\Omega_m=0.18\pm0.11$ and $\Omega_{\Lambda}=0.46\pm0.51$ for non-flat $\Lambda$CDM. For the combination of GRB and SNe Ia sample, we obtain $\Omega_m=0.271\pm0.019$ and $h=0.701\pm0.002$ for the flat $\Lambda$CDM, and for the non-flat $\Lambda$CDM, the results are $\Omega_m=0.225\pm0.044$, $\Omega_{\Lambda}=0.640\pm0.082$ and $h=0.698\pm0.004$. These results from calibrated GRBs are consistent with that of SNe Ia. Meanwhile, the combined data can improve cosmological constraints significantly, comparing to SNe Ia alone. Our results show that the $E_{\rm iso}-E_{\rm p}$ correlation is promising to probe the high-redshift universe.
Differences in community composition of bacteria in four deep ice sheets in western China

Differences in community composition of bacteria in four deep ice sheets in western China L. An, Y. Chen, S. -R. Xiang, T. -C. Shang, and L. -De Tian Key Laboratory of Arid and Grassland Agroecology (Ministry of Education) School of Life Sciences, Lanzhou University, Lanzhou, Gansu 730000, China Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Science, Beijing 100085, China State Key Laboratory of Cryospheric Science, Cold and Arid Regions Environmental Engineering Research Institute, Chinese Academy of Science, Lanzhou, Gansu 730000, China Department of Plant Pathology, Gansu Agricultural University, Lanzhou, Gansu 730070, China