Miracle-dz/UniFAR-FTUs huggingface dataset:
CHINESE STUDENTS’ DECISION-MAKING IN HIGHER EDUCATION:

This paper presents the findings of an exploratory mixed-methods study into the consumer purchase decisions about higher education in Thailand by Chinese students. The research is based on a theoretical model by Cubillo, Sanchez and Cervino (2006). Four factors in the consumer decisions –personal reasons, country image effect, institution image, and programme evaluation – were examined. The study used a student questionnaire (n = 80) and a focus group (n = 10). Participants were Chinese students at different universities in Bangkok and Chiang Mai. The questionnaire was analysed using a structural equation model. This analysis showed that institution image and programme evaluation were significant factors in the choice of a Thai university, but the country image effect and personal reasons were not. In contrast, the focus group interviews showed that personal reasons like language development, was essential to students as well as institution image and programme evaluation, but country image was less important for their choice.
Self-Enforcing Climate Coalitions And Preferential Free Trade Arrangements

In this paper, we discuss the endogenous formation of self-enforcing climate coalitions linked to the issue of a free trade agreement. As a framework, a strategic trade model is used in which countries may discourage greenhouse gas emissions by means of an import tariff on dirty goods. In addition, countries can set an emissions cap being effective on a permit market. Our main focus, however, is on the utilization of terms of trade privileges provided to members of a preferential free trade area. We propose evidence for that the welfare gains of trade liberalization are strongly promoting the formation of climate coalitions. In the parametrical simulation of the model, global emissions as well as climate change damages are found significantly reduced compared to the BAU scenario while global welfare is found significantly higher. JEL classification: Q54, Q56, Q58, F18, F13
SETTLING OF SAND THROUGH A CLAY SLURRY

The potential for segregation behaviour of a slurry as a function of the surface properties of the fines in the slurry was studied from a rheological perspective. The fines-water slurry used for this study was a kaolinite clay-water mix. NonNewtonian flow behaviour with a Herschel-Bulkley rheological model fit was generally observed for the test slurry. A modified segmented standpipe was designed, fabricated and used in a series of experiments to determine concentration profiles during the sedimentation processes. Analyses of the solid content profiles and sand content profiles in the standpipes indicated a capture of sand particles which could be correlated to the yield stress of the finesmatrix. Theoretical calculations, however, showed over-prediction of the captured sand size. An average correction factor of about 0.2 to the theoretical size was applicable for this test case. A bi-viscous model analysis of the sedimentation process was also used to study the segregation mechanism. RÉSUMÉ Le potentiel pour le comportement de ségrégation d'une boue en fonction des propriétés extérieures des fines dans la boue a été étudié avec une perspective rhéologique. La boue de l'amende-eau utilisée pour cette étude était un mélange de l'argile-eau de kaolinite. On a généralement observé le comportement Non-Newtonien d'écoulement avec un ajustement rhéologique de modèle de Herschel-Bulkley pour la boue d'essai. Une colonne segmentée modifiée a été conçue, fabriquée et utilisée dans une série d'expériences pour déterminer des profils de concentration pendant les processus de sédimentation. Les analyses des profils de contenu plein et des profils contents de sable dans les colonnes ont indiqué une capture des particules de sable qui pourraient être corrélées avec l'effort d'fléchissement de l'amende-matrice. Les calculs théoriques, cependant, ont montré l'au-dessus-prévision de la taille capturée de sable. Un facteur moyen de correction environ de 0.2 à la taille théorique était applicable pour ce cas d'essai. Une analyse modèle Bi-visqueuse du processus de sédimentation a été également employée pour étudier le mécanisme de ségrégation.
Community and Individual Level Factors Influencing Modern Contraceptive Use among Married Women in Nigeria

The prevalence of contraceptive use is low in Nigeria with wide variations across the different geopolitical zones. Though researchers have devoted considerable attention to the impact of individual-level factors on contraceptive use, less is known about how community characteristics affect contraceptive use in married women. The objective of this study is to assess the effects of community level variables on family planning use among Nigerian married women of reproductive age group (15-49 years). The study is based on data collected from the 2008 Nigeria Demographic and Health Survey (NDHS). Random effects multilevel logistic regression analyses of 23479 married women of reproductive age nested within 888 clusters was carried out to assess the role of selected individual (socio demographic and other family planning related factors) and community level factors (childbearing, wealth index, education, high parity, exposure to family planning messages) in the use of modern contraceptives. The regression model was fitted using the GLLAMM command in STATA-10. Level of significance was at 5%. Contraceptive use was lowest in communities which were poor, have low level of education and those who felt having more than four children was ideal. Overall, the results of this study suggest that contextual factors play an important role in contraceptive use. More attention needs to be paid particularly to contextual factors while formulating family planning policies in Nigeria so as to improve modern contraceptive use.
Sim 2 real of soft-bodied , shape-changing robots

Soft robots provide a unique capability over rigid machines: the ability to continuously change their shape on demand. As demonstrated by organisms capable of shape change, this behavior has several desirable properties, including the ability to enter and operate in a wider range of environments, or manipulate objects with greater delicacy than a fixed-shape organism can. Introducing shape as a control variable leads to a rich yet complicated range of configurations, opening up a wide range of possibilities for multi-functional, shape-changing robots. Here, we present a target pipeline for the automatic design of soft-bodied, shape-changing robots to accomplish an input task, such as locomotion or grasping. We demonstrate working aspects of such a pipeline as we attempt sim2real transfer of morphing robots. In this context, we explore the current role of simulation, shortcomings of current soft robot simulators, and discuss methods for overcoming such shortcomings.
OF EXISTING ALGORITHMS FOR FACE DETECTION AND RECOGNITION

-In this paper, we present a review on the most successful existing algorithms or methods for face recognition technology to encourage researchers to embark on this topic. A brief on general information of this topic is also included to compose an overall review. This review is written by investigating past and ongoing studies done by other researchers related to the same subject. Five different algorithms have been preferred based on the most widely used criteria. The algorithms are Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), skin colour, wavelet and Artificial Neural Network (ANN). Certain parameters have been taken into account for the algorithms’ review. The parameters are size and types of database, illumination tolerance, facial expressions variations and pose variations. However, no specific justification can be claimed as it is only a review paper based on other researches. Key-Words: Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Skin Colour, Wavelet, Artificial Neural Networks (ANN)
A UTOMATABLE SPLICING METHOD FOR STEEL CORD CONVEYOR BELTS – F INDING A SUITABLE PREPARATION PROCESS

The increasing demand of raw materials leads to longer conveyor belt systems with higher mass flows all over the world. Due to logistic reasons, conveyor belts are produced in segments to guarantee manageability. The different segments are spliced at the conveyor system to form an endless belt, which can amount up to multiple kilometres. This process shows a high level of optimization potential since currently the different work steps are performed manually. An automation of this process can minimize the downtime of the conveyor system and improve the splice quality. In this study, a suitable preparation process is evaluated to automate the stripping process, where the rubber has to be removed from the steel cords. Therefore, the application of water jetting and laser processing is investigated.
Rigidity theorems for Spin C-manifolds

We prove a rigidity and vanishing theorem for Spin-manifolds. Special cases include the rigidity of the elliptic genus and the elliptic genera of higher level. We state some applications to Spin-manifolds with nice Pin(2)-action. ( 1999 Elsevier Science Ltd. All rights reserved.
Econometric Forecasts Package : Short-Run Forecasting Models for the Current Analysis of the Canadian Economy ¤

To improve the monitoring of the Canadian economy, a new forecasts package is introduced: the Econometric Forecasts Package (EFP). The EFP makes use of di¤erent indicator models or reduced-form speci.cations that were originally developed by the sta¤ at the Bank of Canada. This document provides a comprehensive view of the models currently available for near-term forecasting of various economic indicators such as GDP and in‡ation. It also provides the Bank’s sta¤ with a new forecasting strategy where econometric models are being used in a systematic framework. Forecasts are reported in tables every week, incorporating up-to-date information, with weekly updates. A wide variety of models are used, including sophisticated non-linear models such as Markov-Switching. The EFP will be a useful and stimulating tool for the Bank’s Sta¤, making the BoC a leading institution in terms of developing and using econometric models for the purpose of timely short-run forecasting. Bank classi.cation: Current Analysis, Econometric and Statistical Methods. ¤This work is the result of long standing research in model building by past and current economists at the Bank of Canada. Without these past works, our actual project would have been impossible to realize. We also wish to thank Richard Dion, Jamie Armour, Michel Laurence, Sylvain Martel, John Murray, Don Coletti, Paul Fenton, and Bob Amano for their comments and suggestions, and other participants at seminars held at the Bank of Canada and the University of Ottawa. We are also grateful to colleagues in other central banks for fruitful conversations and for sharing on their experience in short-run forecasting when participating to the Bank of Canada Workshop on Monitoring and Forecasting, held in Ottawa on October 22nd and 23rd, 2004. The views expressed herein and any remaining errors are those of the authors. No responsibility for them should be attributed to the Bank of Canada. Internal reference: RM-04-011 (December 2004). yCorresponding author: Research Department, Bank of Canada, 234 Wellington St., Ottawa, Ontario, K1A OG9, Canada (fdemers@bank-banque-canada.ca). zFormally at the Bank of Canada. An Important question in econometric model-building is how useful econometric models are likely to be for short-run forecasting purposes. Ray C. Fair, 1974
Effect of an energy-deficient diet on populations of ciliate protozoans in bovine rumen

Ten young rumen-cannulated crossbred steers were randomly divided into two groups: a control group (C; n=4), which was fed a balanced diet for daily weight gain of 900g; and a pronounced energy-deprived group (PED; n=6), receiving 30% less of the required energy for maintenance. After 140 days of these alimentary regimes, rumen fluid and urine samples were collected for biochemical and functional tests, before feeding and at 1, 3, 6, and 9 hours after feeding. The energy-deprivation diet caused a significant reduction in the number of Entodinium, Eodinium, Isotricha, Dasytricha, Eremoplastron, Eudiplodinium, Metadinium, Charonina, Ostracodinium, and Epidinium protozoa. There was no effect of the time of sampling in both groups on the total number of ciliates in rumen fluid. A higher number of protozoan forms in binary division were recorded in the control group, at the 6 and 9 hours after feeding (P<0.019). There was a high positive correlation between the total count of protozoans in rumen fluid and glucose fermentation, ammonia, and urinary allantoin excretion index; and a negative correlation between the total count of protozoa and metilene blue reduction, and a medium correlation between the total count of protozoa and total volatile fatty acids concentration. The determination of the protozoa populations does not imply in the use of complex and hard-to-execute techniques, although it is time consuming and needs practice. This exam particularly helps in clinical expected diagnosis.
BORRALHO, N. M. G., P. P. COTTERILL and P. J. KANOWSKI (1992): Genetic control of growth of Eucalyptus globulus

Interspecific hybrids of Eucalyptus urophylla E. tereticornis in a factorial-mating design were used to analyze general hybridizing ability (GHA), specific hybridizing ability (SHA) and heterosis for height (H; 0.5, 1.5, 2.5, 4 and 7.5 years in age), diameter at breast height (D; ages 1.5, 2.5, 4 and 7.5) and wood density (WD; age 7.5) across two environments. The GHA variances were significant for all traits, and those of the SHA were also significant for most of the traits but with less magnitude, indicating the greater importance of additive gene effects in explaining the phenotypic variation among hybrids. The narrow-sense heritability (h2) and dominance (d2) estimates with hybrid growth and wood density ranged between 0.02±0.05 (d2 in D7.5) and 0.23±0.10 (d2 in H1.5) over the different ages, suggesting weak additive and dominant effects on these traits. Additive genetic correlations of growth with wood density were weak at age 7.5. Female general combining ability (GCA) based on maternal open-pollinated families was not necessarily a good indicator of GHA as their corHybridizing ability and heterosis between Eucalyptus urophylla and E. tereticornis for growth and wood density over two environments By Q. WENG1),2), X. HE2),3), F. LI2), M. LI2), X. YU2), J. SHI3) and S. GAN1),2),*) Q. WENG and X. HE equally contributed to this work (Received 3rd April 2013) 1) State Key Laboratory of Tree Genetics and Breeding, Chinese Academy of Forestry, Xiangshan Road, Beijing 100091, China. 2) Research Institute of Tropical Forestry, Chinese Academy of Forestry, Longdong, Guangzhou 510520, China. 3) The Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Nanjing Forestry University, 159 Longpan Road, Nanjing 210037, China. *) Corresponding author: SIMING GAN. Tel. +86-20-87032402, Fax +86-20-87031622. E-Mail: Siming.Gan@ritf.ac. cn Weng et. al.·Silvae Genetica (2014) 63-1/2, 15-24 DOI:10.1515/sg-2014-0003 edited by Thünen Institute of Forest Genetics 16 relations were 0.48 (P=0.17), 0.65 (P=0.04) and –0.56 (P=0.10) for H7.5, D7.5 and WD7.5, respectively. A great proportion of hybrids showed positive female-parent heterosis (FPH) at age 7.5, with the highest relative FPH of 47.2% in D7.5. This study demonstrates the heterosis between inter-sectional species and could have implications for E. urophylla E. tereticornis hybrid breeding.
TheImpactof Non-verbalCommunicationon LexiconFormation

This paperpresentsa seriesof experimentsin which two mobile robotsdevelop a sharedlexicon of which the meaningis groundedin the real world. The experiments investigatethe impact of non-verbal communicationon lexicon formation. Non-verbal communicationis usedto establishjoint attentionor to evaluatefeedback. Theexperimentsimplementadapti ve languagegamesin which two agentstry to communicatesomereal world object. Whenthe agentsfail, they canadapttheir memoryin orderto improve performanceon futureoccasions.As theexperimental resultsshow, thequalityof theevolvedlexicon is betterwhenfeedbackis usedrather thanjoint attention.
ARNOLD JOURNALS

A mixture model in multivariate survival analysis is presented, whereby heterogeneity among subjects creates divergent paths for the individual’s risk of experiencing an event (i.e., disease), as well as for the associated length of survival. Dependence among competing risks is included and rendered testable. This method is an extension of the bivariate correlated gamma-frailty model. It is applied to a data set on Danish twins, for whom cause-specific mortality is known. The use of multivariate data solves the identifiability problem which is inherent in the competing risk model of univariate lifetimes. We analyse the influence of genetic and environmental factors on frailty. Using a sample of 1470 monozygotic (MZ) and 2730 dizygotic (DZ) female twin pairs, we apply five genetic models to the associated mortality data, focusing particularly on death from coronary heart disease (CHD). Using the best fitting model, the inheritance risk of death from CHD was 0.39 (standard error 0.13). The results from this model are compared with the results from earlier analysis that used the restricted model, where the independence of competing risks was assumed. Comparing both cases, it turns out, that heritability of frailty on mortality due to CHD change substantially. Despite the inclusion of dependence, analysis confirms the significant genetic component to an individual’s risk of immortality from CHD. Whether dependence or independence is assumed, the best model for analysis with regard to CHD mortality risks is an AE model, implying that additive factors are responsible for heritability in susceptibility to CHD. The paper ends with a discussion of limitations and possible further extensions to the model presented.
Brain Image Segmentation Based on Fuzzy Clustering

The segmentation performance is topic to suitable initialization and best configuration of supervisory parameters. In medical image segmentation, the segmentation is very important when the diagnosing becomes very hard in medical images which are not properly illuminated. This paper proposes segmentation of brain tumour image of MRI images based on spatial fuzzy clustering and level set algorithm. After performance evaluation of the proposed algorithm was carried on brain tumour images, the results showed confirm its effectiveness for medical image segmentation, where the brain tumour is detected properly.
No Support for Honest Signaling in Birdsong and the 1 Motor Constraints Hypothesis 2

9 Birdsong biologists interested in sexual selection and honest signaling have repeatedly 10 confirmed, over more than a decade, the significance of a scatter plot between trill rate and 11 frequency bandwidth. This “motor constraints hypothesis” of Podos (1997) proposes that the 12 closer a song plots to an upper bound on this graph, the more difficult the song is to sing, and the 13 more difficult the song the higher quality the singer, so that song quality honestly reveals male 14 quality. In reviewing the confirming literature, however, I can find no support for this 15 hypothesis. 16 The scatter in the graph for songbirds is explained not by male quality but largely, if not 17 entirely, by social factors and song learning. When songbirds learn their songs from each other, 18 multiple males in a neighborhood will sing the same song type. The need to conform to the local 19 dialect of song types guides males to learn a typical example of each song type for that 20 population, not to take a memorized song and diminish or exaggerate it in trill rate or frequency 21 Kroodsma, Honest Signaling and Motor Constraints, p. 2 bandwidth to honestly demonstrate his relative prowess. When data in this scatter plot are coded 22 both by song type and by male, it is the song type and the need to conform that explains the 23 variability, not the quality of different males. There is no reliable information in the song 24 performance measures that can be used to evaluate a singing male. 25 Understanding how and why birds sing will require an open and honest attempt to falsify 26 multiple working hypotheses, rather than attempts to confirm a favored one. 27
Deep Convolution Neural Networks Cascaded Improved Boosted Forest for Pedestrian Detection

Due to the resolution of small size pedestrian is relatively low, and the hard negative background is very similar to people, therefore, detecting small size pedestrian or detecting pedestrian from hard negative background still a challenging problem in computer vision. In order to effectively address these problem, we propose a novel deep convolution neural networks, and cascade an improved boosted forest classifier method to detect pedestrian. Firstly, by using selective search method to propose pedestrian candidate boxes with confidence scores for utmost retaining image resolution; then, based on these proposed confidence values, adopting convolution neural network model to extract candidate regions feature maps; finally, we improve the boosted forest classifier and cascade it to classify candidate boxes for achieving efficiently pedestrian detection. Extensive experiments on Caltech and KITTI benchmarks demonstrate the proposed method outperforms the state-of-the-art, achieves promising precision on KITTI and the lowest miss rate of 11.53% on Caltech, outperforming the second best method (CompACT-Deep) by 0.17%.
End-to-end equalization with convolutional neural networks

This work aims to implement a novel deep learning architecture to perform audio processing in the context of matched equalization. Most existing methods for automatic and matched equalization show effective performance and their goal is to find a respective transfer function given a frequency response. Nevertheless, these procedures require a prior knowledge of the type of filters to be modeled. In addition, fixed filter bank architectures are required in automatic mixing contexts. Based on end-to-end convolutional neural networks, we introduce a general purpose architecture for equalization matching. Thus, by using an end-toend learning approach, the model approximates the equalization target as a content-based transformation without directly finding the transfer function. The network learns how to process the audio directly in order to match the equalized target audio. We train the network through unsupervised and supervised learning procedures. We analyze what the model is actually learning and how the given task is accomplished. We show the model performing matched equalization for shelving, peaking, lowpass and highpass IIR and FIR equalizers.