Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Variation in Wood Density of Gmelina arborea planted on different sites in Wester Venezuela.

ESPINOZA, JESÚS ALBERTO. Genetic Variation in Wood Density of Gmelina arborea planted on different sites in Western Venezuela. (Under the direction of William S. Dvorak.) Variation in wood specific gravity from the base to the top of tree and from pith to bark was investigated for Gmelina arborea Roxb. plantations in western Venezuela. Increment cores were taken from 30 trees at five different sections up the stem: 0.1 m, 1.3 m, 1⁄2 total height, 3⁄4 total height and at the stem top (10 cm of diameter). These trees were chosen from commercial plantations located at three different sites. Specific gravity was obtained using an Xray densitometer. The results show that there is an increase in specific gravity from pith to bark. Changes in SG from pith to bark were greater at the top than the bottom of the trees. Slopes of the tendency lines of SG from pith to bark increased from the bottom to the top of tree and they were significantly different at p = 0.012. It was also evident that SG decreased from the base of the tree to 1⁄2 of the total height, then increased towards the top of the tree. These difference were significantly different at α = 0.05. Phenotypic correlations between SG and total height of the tree were very low and ranged from – 0.007 to 0.1 across the three sites. The correlations were non-significant at level α = 0.05. In a second study, variation of wood specific gravity among sites and provenances was investigated for Gmelina arborea in four provenance-progeny trials in Venezuela. Eighteen provenances and two controls were evaluated across the sites. Twelve or 5 mm increment cores were extracted from 25 trees in each provenance at every site, with the exception of one trial where 20 samples were taken. Specific gravity was obtained using the gravimetric method. The results indicated that there was high correlation (0.93) among samples taken at 2, 3 and 5 years of age in Gmelina arborea. Variation in wood specific gravity was high among provenances and varied from 0.447 at Muak Lek, (Thailand) to 0.360 at Pawlangyi and Kabaw (Myanmar). A negative correlation between diameter and specific gravity at the provenance level was found, and ranged from 0.92 to 0.30 depending on the specific method of calculation.
Learning on demand: dynamic creation of customized, coherent eLearning experiences

This paper presents a conceptual model concerning automatic creation of coherent eLearning experiences through dynamic aggregation of heterogeneous learning objects. The model uses detailed user profiles as the main key to create customized learning content, tailored to each user’s needs, preferences and skills. Aggregation of heterogeneous learning objects may result in a very incoherent learning sequence. Therefore, the model incorporates a method to improve the learning coherence of the generated course. The compromise between customization and coherence is fully adjustable from maximum coherence to maximum customization.
Male Breast Cancer Patients’ Perspectives on Their Health Care Situation: A Mixed-Methods Study

Background: Male breast cancer is rare. No information was available on how male breast cancer patients (MBCPs) experience the health care they receive in Germany in a setting that is tailored to women. The aim of this study was to explore the health care situation of MBCPs from their perspectives. Methods: The study follows a mixed-methods design, combining quantitative data from a standardized written questionnaire with qualitative data from personal interviews. Descriptive statistics (quantitative data) and qualitative content analysis (qualitative data) were used for data analysis. Results: Questionnaires completed by 100 and personal interviews of 27 MBCPs were analyzed. Several men reported mainly positive experiences while others experienced shortcomings. These included delays in diagnosis, health care provider uncertainty about treatment (tamoxifen, radiation therapy), experiences of stigmatization, and issues of continuity of care including unclear responsibilities for aftercare and access challenges to breast-cancer-specific care in gynecology settings. Conclusions: The awareness of male breast cancer needs to be increased among the public, health care providers and researchers in order to avoid delays in diagnosis and reduce stigmatization and uncertainty about treatment. Health care structures ensuring access to gynecology care and clear responsibilities for aftercare need to be established.
Determinants of Rural-to-Urban Labour Movements in Mexico: Household Perspective

The purpose of this paper is to test specific hypotheses about the detenninants of temporary ruralto- urban migration (circulation) by male heads of households for the putpose of engaging in wage employmenL Data from a sample of 145 rural households located in the central Mexican highlands are used to estimate the model. The circulation equation is formulated as a polychotomous, ordered-response model and is estimated using logistic regression. The results of the model suggest that males' level of education and previous circulation experience have a positive and significant impact on the probability of circulation. By comparison, land has a negative effect, and ecooomic status has a U-shaped effect. Age and the nmnber of adults in the household are fotmd to have a statistically weak association with the dependent variable.
Influence of zinc deficiency on one year recurrence in children with nephrotic syndrome

Introduction: Relapses in children with steroid sensitive nephrotic syndrome (SSNS) are common and sometimes triggered by various infections. Low zinc levels have been described in children with nephrotic states. It is supposed to that zinc deficiency might lead to dysregulation of immune system and an increased risk of infection. Objectives: This study sought to examine whether the plasma level of zinc in nephrotic patients is related to the number of relapses in these patients. Patients and Methods: Forty-three children aged 1-10 years were entered in this study. Baseline data including age, serum zinc level, number of relapses during one year was recorded. The t test and chi-square tests were used to compare the mean values and proportions respectively with significant P value (P < 0.05). Results: Forty-three children with storied sensitive nephrotic syndrome enrolled in this study. Twenty-three (53.5%) of them were male and 20 (46.5%) were female. Around 74.4 % of patients experienced relapses of nephrotic syndrome in one-year period. There was a significant relation between zinc deficiency and recurrence rate. Conclusion: Zinc deficiency is common in children suffering from nephrotic syndrome and is related to recurrence of relapses in these patients.
Detection of sodium in the atmosphere of WASP-69b

Transit spectroscopy is one of the most commonly used methods to characterize exoplanets atmospheres. From the ground, these observations are very challenging due to the terrestrial atmosphere and its intrinsic variations, but high-spectral resolution observations overcome this difficulty by resolving the spectral lines and taking advantage of the different Doppler velocities of the Earth, the host star and the exoplanet. We analyze the transmission spectrum around the Na I doublet at 589 nm of the exoplanet WASP-69b, a hot Jupiter orbiting a K-type star with a period of 3.868 days, and compare the analysis to that of the well-know hot Jupiter HD 189733b. We also present the analysis of the Rossiter-McLaughlin effect for WASP-69b. Two transits of WASP-69b were observed with the HARPS-North spectrograph (R = 115 000) at the TNG telescope. We perform a telluric contamination subtraction based on the comparison between the observed spectra and a telluric water model. Then, the common steps of the differential spectroscopy are followed to extract the transmission spectrum. The method is tested with archival transit data of the extensively studied exoplanet HD 189733b, obtained with the HARPS-South spectrograph at ESO 3.6m telescope, and then applied to WASP-69b data. For HD 189733b, we spectrally resolve the Na I doublet and measure line contrasts of $0.72\pm0.05\%$ (D2) and $0.51\pm0.05\%$ (D1), and FWHMs of $0.64\pm0.04${\AA} (D2) and $0.60\pm0.06${\AA} (D1), in agreement with previously published results. A net blueshift of ${\sim}0.04${\AA} is measured. For WASP-69b only the contrast of the D2 line is measured ($5.8\pm0.3\%$). Even if this corresponds to a detection at the $5\sigma$-level of excess absorption of $0.5\pm0.1\%$ in a passband of $1.5${\AA}, more transits are needed to fully characterize the lines profiles and retrieve accurate atmospheric properties.
Bearing Fault Detection Based on Daubechies Wavelet

Journal bearings are widely used to support the shafts in industrial machinery involving heavy loads, such as compressors, turbines and centrifugal pumps. The major problem that could arise in journal bearings is catastrophic failure due to corrosion or erosion and fatigue, which results in economic loss and creates major safety risks. Thus, it is necessary to provide suitable condition monitoring technique to detect and diagnose failures, and achieve cost savings to the industry. Therefore, this paper focuses on fault diagnosis on journal bearing using Debauchies Wavelet-02 (DB-02). Nowadays, wavelet transformation is one of the most popular technique of the time-frequency-transformations. An experimental setup was used to diagnose the faults in the journal bearing. The accelerometer is used to collect vibration data, from the journal bearing in the form of time domain. This was then used as input for a MATLAB code that could plot the time domain signal. This signal was then decomposed based on the wavelet transform. The fast Fourier transform is then used to obtain the frequency domain, which gives us the frequency having the highest amplitude. To diagnose the faults various operating conditions are used in the journal bearing such as Full oil, half loose, half oil, fault 1, fault 2, fault 3 and full loose. Then the Artificial Neural Networks (ANN) is used to classify faults. The network is trained based on data already collected and then it is tested based on random data points. ANN was able to classify the faults with the classification rate of 85.7%. Thus, the test process for unseen vibration data of the trained ANN combined with ideal output target values indicates high success rate for automated bearing fault detection.
The calibration of carbon nanotube based bionanosensors

We derive the calibration constants necessary for using single-walled carbon nanotubes CNTs as nanoscale mass sensors. The CNT resonators are assumed to be either in cantilevered or in bridged configurations. Two cases, namely, when the added mass can be considered as a point mass and when the added mass is distributed over a larger area is considered. Closed-form transcendental equations have been derived for the frequency shift due to the added mass. Using the energy principles, generalized nondimensional calibration constants have been derived for an explicit relationship between the added mass and the frequency shift. A molecular mechanics model based on the universal force field potential is used to validate the new results presented. The results indicate that the distributed nature of the mass to be detected has considerable effect on the performance of the sensor. © 2010 American Institute of Physics. doi:10.1063/1.3435316
Machine Learning for HTTP Botnet Detection Using Classifier Algorithms

Recently, HTTP based Botnet threat has become a serious problem for computer security experts as bots can infect victim’s computer quick and stealthily. By using HTTP protocol, Bots are able to hide their communication flow within normal HTTP communications. In addition, since HTTP protocol is widely used by internet application, it is not easy to block this service as a precautionary approach. Thus, it is needed for expert finding ways to detect the HTTP Botnet in network traffic effectively. In this paper, we propose to implement machine learning classifiers, to detect HTTP Botnets. Network traffic dataset used in this research is extracted based on TCP packet feature. We also able to find the best machine learning classifier in our experiment. The proposed method is able to classify HTTP Botnet in network traffic using the best classifier in the experiment with an average accuracy of 92.93%.
Occurrence of tetracyclines in feedingstuffs – results of a two-year study within the official control of feed

Abstract The paper describes a microbiological method for the detection of antibacterial substances in feedingstuffs. The method allowed detection of the main antibiotic groups, including tetracyclines. In 2013-2014, a total of 171 feed samples were analysed to determine antibacterial substances. Among the analysed samples 84 (49.1%) were suspected to contain tetracyclines. Out of the 84 feeds analysed using chromatography, 28 (33.3%) contained undeclared tetracyclines, which were identified at concentrations ranging from 0.32 mg kg-1 to 48.98 mg kg-1.
Holocene North Atlantic Overturning in an atmosphere-ocean-sea-ice model compared to proxy-based reconstructions

Climate and ocean circulation in the North Atlantic region changed over the course of the Holocene, partly because of disintegrating ice sheets and partly because of an orbital-induced insolation trend. In the Nordic Seas, this impact was accompanied by a rather small, but significant, amount of Greenland ice sheet melting. We have employed the EMIC LOVECLIM and compared our model simulations with proxy-based reconstructions of δ13C, sortable silt, and magnetic susceptibility (κ) used to infer changes in past ocean circulation over the last 9000 years. The various reconstructions exhibit different long-term evolutions suggesting changes in either the overturning of the Atlantic in total or of subcomponents of the ocean circulation, such as the overflow waters across the Greenland-Scotland ridge. Thus, the question arises whether these reconstructions are consistent with each other or not. A comparison with model results indicates that δ13C, employed as an indicator of overturning, agrees well with the long-term evolution of the modeled Atlantic meridional overturning circulation (AMOC). The model results suggest that different long-term trends in subcomponents of the AMOC, such as Iceland-Scotland overflow water, are consistent with proxy-based reconstructions and allow some of the reconstructions to be reconciled with the modeled and reconstructed (from δ13C) AMOC evolution. We find a weak early Holocene AMOC, which recovers by 7 kyr B.P. and shows a weak increasing trend of 88 ± 1 mSv/kyr toward present, with relatively low variability on centennial to millennial timescales.
Substance Use and Abuse

While the issues of substance use and abuse have been addressed from a variety of perspectives and approaches, the fundamental social issues have not been covered in any systematic way. This book represents the first academic effort to apply major sociological theories to the field of substance use and abuse in order to provide readers with a solid knowledge base from which they may develop more informed ideas about prevention, intervention, treatment, law enforcement, and social reactions to this ubiquitous social problem. Using a systematic framework, Shaw reviews the existing literature, explains key concepts, addresses fundamental issues, and discusses the policy implications for public health, social control, community, and work. This comprehensive sociological treatment of substance use and abuse is essential reading for educators in public policy, sociology, criminology, and deviance. Applying the major sociological theories of anomie, career, conflict, functionalist, rational choice, social control, social disorganization, social learning, social reaction, and subculture perspectives, Shaw provides an important overview of the issues involved with substance use and abuse. By utilizing such an approach, he demonstrates that public views, governmental policies, intervention strategies, and prevention programming can be informed by the different sociological theories. This unique consideration and analysis illustrates that no single view on substance use and abuse is absolute or sacred. Therefore, considering the issues from a variety of sociological perspectives will bring greater understanding to a pervasive social problem that continues to plague American society.
Latent Class Model on Socio-Religious Data

We believe that in last two decades perception regarding socio-religious values had been changed in our society. Survey has been carried out on â€œchanges in social values and their acceptanceâ€ in year 2011. Respondents have asked 74 questions (marked on Likert-scale) regarding educational system, political and religious affiliations and their impact on social values. Among these we have selected only those questions related to socio-religious issues (based on of individual and collective perceptions about the prevailing standard of the society in comparison with Islamic standards). Similar surveys using the same questionnaire had had conducted in year 1994 and 2001. Respondents, at each time of survey, were young students (youth acquiring education) from different colleges (Karachi region) and Karachi University. Perception can be explained more appropriately through latent class model (LCM). Through LCM we can explore structures in the data in term of different opinion groups. The modeling is done on the selected set of similar questions from each year. Conditional probabilities for year 2011, 2001 and 1994 are then compared in search of presence of any difference of opinion between the respondents. It is observed that by the passage of time, due to the influence of the electronic media there is a change in the opinion about the values of the society among the youth. Although, there is a reduction in the proportion of â€œDissatisfied groupâ€ within the society but negative perception is penetrating among our young generation specifically about Ulmah and Imamâ€™s role and womenâ€™s due rights toward society.
Robots LearnWriting

This paper proposes a general method for robots to learn motions and corresponding semantic knowledge simultaneously. A modified ISOMAP algorithm is used to convert the sampled 6D vectors of joint angles into 2D trajectories, and the required movements for writing numbers are learned from this modified ISOMAP-based model. Using this algorithm, the knowledge models are established. Learned motion and knowledge models are stored in a 2D latent space. Gaussian Process (GP) method is used to model and represent these models. Practical experiments are carried out on a humanoid robot, named ISAC, to learn the semantic representations of numbers and the movements of writing numbers through imitation and to verify the effectiveness of this framework. This framework is applied into training a humanoid robot, named ISAC. At the learning stage, ISAC not only learns the dynamics of the movement required to write the numbers, but also learns the semantic meaning of the numbers which are related to the writing movements from the same data set. Given speech commands, ISAC recognizes the words and generated corresponding motion trajectories to write the numbers. This imitation learning method is implemented on a cognitive architecture to provide robust cognitive information processing.
Master Erasmus Mundus in Color in Informatics and Media Technology (CIMET) Automatic Semantic Annotation for Media Learning Objects

Recent advances in technology have provided alternative solutions and approaches to everyday tasks. One of which is in education, where the learning process is no longer confined to conventional classrooms. E-learning or distance learning are now a popular alternative which involves the use of learning objects for teachers to convey instructional content. These learning objects are accessible to students on a digital repository and can come in many different forms. Recently multimedia files such as videos are also used. In order to enable efficient indexing and retrieval of these videos, they must be encapsulated into effective media learning objects. Although many querying methods exist, users are most accustomed to query by keyword methods, giving text based queries to retrieve corresponding videos. Generally these keywords are selected manually, but this method is not favorable because manual annotation is restrictive to a set of words, subjective to the annotator, and overall a labor intensive process. This research explores semantic keyword selection methods for automatic video annotation. Cross document annotation is used to extract potential keywords by taking into consideration surrogate documents, e.g. transcript, slides, lecture notes, etc. These potential keywords are then refined based on a set of preselected seed words in order to obtain highly related keywords, based on WordNet and visualness similarity scores. Three novel objective scoring methods are proposed to select top-ranking keywords based on visualness similarity and word sense disambiguation. These developed methods are then evaluated based on questionnaire responses of selected keywords for a set of videos. The three developed objective scoring methods correlate well with the scores of the subjectives responses and generally outperform the traditional term frequency inverse document frequency (TF-IDF) method. The proposed LVD-F method obtains the highest precision and recall of all.
The roles of knowledge assets in promoting firm productivity and innovation in China

THE ROLES OF KNOWLEDGE ASSETS IN PROMOTING FIRM PRODUCTIVITY AND INNOVATION IN CHINA by YANG Jingsi Master of Philosophy This paper investigates how intangible knowledge assets impact upon the firm’s products and the output of new products through a large panel data set covering all manufacturing firms from the period of 1998-2007. We hypothesize that more knowledge assets have a positive impact on total factor productivity and the ratio of new products to total products, but only up to a point, due to the importance of complementary assets. The inverse quadratic relationship found in the relationship between the ratio of knowledge assets to total assets and TFP suggests that it is necessary to balance knowledge assets with complementary assets in order to achieve a higher degree of productivity. However, the positive effects of intangible asset ratio on the proportion of the output of new products in that of total products suggest that new products always increase with knowledge assets, because products are the prerequisite for one firm to benefit from its knowledge assets. The results are robust in all firms with different ownership types, including foreign, state-owned and private groups or all those with different motivations (international-market oriented vs. domestic-market oriented). These results are still robust after considering the effects of R&D expenditure whose effects on firms are discussed more in the literature, however, as an important channel for knowledge assets accumulation, R&D cannot be completely equal to the generated knowledge assets one firm has. DECLARATION I declare that this is an original work based primarily on my own research, and I warrant that all citations of previous research, published or unpublished, have been duly acknowledged. ( YANG Jingsi ) Date: CERTIFICATE OF APPROVAL OF THESIS THE ROLES OF KNOWLEDGE ASSETS IN PROMOTING FIRM PRODUCTIVITY AND INNOVATION IN CHINA by YANGJingsi Master of Philosophy Pan ofExaminers: