Miracle-dz/UniFAR-FTUs huggingface dataset:
Association among Obesity-Related Anthropometric Phenotypes: Analyzing Genetic and Environmental Contribution

Abstract Obesity has become a public-health and policy problem in many parts of the world. Epidemiological and population studies in this field are usually based on different anthropometric measures; however, common genetic and environmental factors between these phenotypes have been scarcely studied. The objective of this article is to assess the strength of these factors on the covariation among a large set of obesity-related traits. The subject group consisted of 533 nuclear families living in the Greater Bilbao (Spain), and included 1,702 individuals aged 2–61 years. Detailed anthropometric measurements (stature, breadths, circumferences and skinfolds) were carried out in each subject. Bivariate quantitative genetic analyses were performed using a variance-components procedure implemented in the software SOLAR. The results revealed that the majority of these traits is affected by common genetic and environmental factors. All correlations were significantly different from 1 and varied from non-significant to very high (>0.90, P < 0.0001), with clearly lower pleiotropic effects among pairs including fat-distribution traits. Despite the strong common genetic effects detected among phenotypes determining the amount of body fat and mass, there is a residual genetic influence on the local fatness measures that cannot be explained exclusively by the genetic influence on overall fatness. Moreover, the observed relationships confirm a partially different genetic control of truncal and peripheral fat. In conclusion, our findings highlight the relevance of considering different types of traits in the prevention and treatment of obesity, as well as in the search for genes involved in its development.
Wavelet Transform in Image Processing : Denoising, Segmentation and Compression of Digital Images

Wavelet transform is a one of the most powerful concept used in image processing. Wavelet transform can divide a given function into different scale components and can find out frequency information without losing temporal information. Wavelet Transform is more suitable technique as compared to fourier transform because it is not possible with fourier transform to observe varying frequencies with time. Image processing is simply a processing of images or digital images in which processing is a collection of number of steps like denoising, segmentation, compression, representation and recognition. This paper will introduce basic concept of wavelet transform and use of wavelet transform in image denoising, image segmentation and image compression.
Reduced Pattern Training In Pattern Distributor Networks

In this paper, we propose a new task decomposition method, Task Decomposition with Pattern Distributor (PD), for multilayered feedforward neural networks. The method uses a combination of network modules in parallel and series to generate the overall solution for a complex problem. We also introduce a method called reduced pattern training in PD networks. This method aims to improve the performance of the pattern distributor network. Our analysis and the experimental results show that reduced pattern training improves the performance of pattern distributor network significantly. Experimental results confirm that this new method can reduce training time and improve network generalization accuracy significantly when compared to ordinary task decomposition methods such as Output Parallelism. ACM Classification: I.2
Simulating moisture diffusion in polymers using thermal-moisture analogy

The present paper illustrates moisture diffusion using advanced thermal-moisture analogy approach. Experimental procedure to measure the diffusivity and solubility of epoxy based encapsulation material to be implemented in simulation has been discussed. The moisture weight gain of the sample is measured till its saturated state over time at 5 different relative humidity (RH%) and temperature combination. Then %weight gain as a function of time results are fitted with the analytical solution of 3-D diffusion equation using nonlinear regression analysis to obtain the diffusivity property. Since the saturated concentration at the boundary of the polymer can be described by Henry's law i.e. Csat = SPvp, where S is solubility (kg /m3/ Pa) and Pvp is the ambient vapor pressure (Pa), which is related to RH% and the saturated vapor pressure Pvp, sat as Pvp=RH% Pvp, sat; this relation is used to obtain modified solubility and solubility at each temperature. The temperature dependence of solubility and diffusivity are described by Arrhenius relation. The results are utilized in Finite Element (FE) analysis of the moisture diffusion model. Only Fickian moisture absorption has been attempted to be modeled. It has been shown that the moisture diffusion properties obtained from such characterization technique fits satisfactorily with the experimental results. Further the analogy scheme's degree of simplicity, boundary conditions and applicable situations have been highlighted.
Inferring Past Demography Using Spatially Explicit Population Genetic Models

Abstract Inferring the past demography of human populations has been classically approached through data from the archaeological record but more recently by the use of genetic data from contemporary samples. Building realistic demographic models at the continental scale is a necessary step toward the improvement of current genomic methods aimed at finding genes under selection. In light of recent advances in Bayesian statistical inference, we discuss here the importance of considering spatially explicit approaches for modeling population expansion and dispersal. Neutral processes, such as the surfing phenomenon, that occur at the front of a range expansion may indeed mimic selection, and they may have played a significant role in spreading particular alleles over large geographic areas. Finally, we discuss a few important issues that require further investigation, notably the use of archaeological data to inform population genetic models, the simulation of range contraction and reexpansion, and the importance of long-distance dispersal.
DREAM Mediates cAMP-Dependent, Ca2+-Induced Stimulation of GFAP Gene Expression and Regulates Cortical Astrogliogenesis

In the developing mouse brain, once the generation of neurons is mostly completed during the prenatal period, precisely coordinated signals act on competent neural precursors to direct their differentiation into astrocytes, which occurs mostly after birth. Among these signals, those provided by neurotrophic cytokines and bone morphogenetic proteins appear to have a key role in triggering the neurogenic to gliogenic switch and in regulating astrocyte numbers. In addition, we have reported previously that the neurotrophic peptide pituitary adenylate cyclase-activating polypeptide (PACAP) is able to promote astrocyte differentiation of cortical precursors via activation of a cAMP-dependent pathway. Signals acting on progenitor cells of the developing cortex to generate astrocytes activate glial fibrillary acidic protein (GFAP) gene expression, but the transcriptional mechanisms that regulate this activation are unclear. Here, we identify the previously known transcriptional repressor downstream regulatory element antagonist modulator (DREAM) as an activator of GFAP gene expression. We found that DREAM occupies specific sites on the GFAP promoter before and after differentiation is initiated by exposure of cortical progenitor cells to PACAP. PACAP raises intracellular calcium concentration via a mechanism that requires cAMP, and DREAM-mediated transactivation of the GFAP gene requires the integrity of calcium-binding domains. Cortical progenitor cells from dream−/− mice fail to express GFAP in response to PACAP. Moreover, the neonatal cortex of dream−/− mice exhibits a reduced number of astrocytes and increased number of neurons. These results identify the PACAP-cAMP-Ca2+-DREAM cascade as a new pathway to activate GFAP gene expression during astrocyte differentiation.
Facilitating Current Terminals Accessing to Cognitive Radio Networks

More users are overcrowding into the partial band, which leads to relative scarcity of the spectrum. In the last decade, cognitive radio is widely regarded as promising technology, which promotes secondary users dynamically accessing to network in the spectrum overlay or underlay way. In the previous blueprint, individual terminals must first cognize spectrum holes, and then utilize the available band. However, there are many challenges for personal terminals with limited software and hardware to achieve the sensing task. We propose the strategy transferring spectrum sensing role of cognitive user to the centralized entity, minimizing terminal cost. We introduce spectrum-cognizing server (SCS) to determine the vacant spectrum. The server can further allocate unutilized spectrum to secondary users in the overlay way and control their transmission power in underlay mode. We argue that network with central SCS provides transparent spectrum service to end-users who can focus on data transmission. Consequently, subscribers who satisfy the wide band operation can seamlessly work in cognitive radio networks. We compare SCS, cooperative sensing and other database-enabled schemes in terms of terminal cost, sensing interference, solution to the hidden node problem and so on, thereby find that SCS has more advantages.
On the Link Between R & D , Innovation and Productivity : Panel Evidence for Dutch and French Manufacturing

This paper studies the relationship between R&D, innovation and productivity in Dutch and French manufacturing using an unbalanced panel of enterprise data from three waves of the Community Innovation Survey pertaining to the period 1994-2004. We estimate by FIML a simultaneous-equation model of R&D, innovation and productivity accounting for individual effects and correcting for sample selection bias. Four-year lagged R&D affects positively and significantly innovation which itself is positively related to productivity. Individual effects play an important role in the relationship and selectivity bias must be accounted for. Significant differences across countries are observed. ∗University of Maastricht, P.O. Box 616, 6200 MD Maastricht, The Netherlands; Room A4.27; Tel. : (+31) 43 388 4962; Fax: (+31) 43 388 4874; w.raymond@maastrichtuniversity.nl †CREST-INSEE, NBER and Maastricht University; mairesse@ensae.fr ‡Cirano and Maastricht University, p.mohnen@maastrichtuniversity.nl §CESifo fellow and Maastricht University, f.palm@maastrichtuniversity.nl
The great trasformismo

ABSTRACT The purpose of this article is to explore the commonalities and differences between Karl Polanyi and Antonio Gramsci in their assessment of the origins of fascism as located within the rise of capitalism in the nineteenth century and its structural impasse in the twentieth century. Specifically, the aim is to trace a set of associations between Polanyi and Gramsci on the transformations wrought across the states-system of Europe prior to the crises that engulfed capitalism leading to the rise of fascism in the twentieth century. Focusing on the class structures that emerged out of the expansion of capitalism across Europe in the nineteenth century reveals that there was less a ‘great transformation’ in terms of a rupture with the past through the rise of liberal capitalism. Rather, there was more a slow and protracted process of class restoration known as passive revolution, or a ‘Great Trasformismo’, referring to the molecular absorption of class contradictions marking the consolidation and expansion of capitalist social relations. In sum, it is argued that The Great Transformation is understood better if read through the epoch of passive revolution, or The Great Trasformismo, which entailed the restoration and maintenance of class dominance through state power. This approach therefore opens up questions, rather than forecloses answers, about the historical geographies constituting the spaces and places of the political economy of modern capitalism.
Evaluating User Representations for the Trustworthiness of Interaction Partners

Trust in Ubiquitous Computing is about finding trustworthy partners for risky interactions in presence of uncertainty about identity, motivation, and goals of the potential interactions partners. For the integration of users in the selection of interaction partners it is not sufficient to provide robust algorithms for trust establishment in service provision and recommendations, but there is a need for a user interface, which allows for intuitive interpretation of the collected information about the trustworthiness of the potential interaction partners. In this paper, we evaluate three representations for trust based on collected evidences in a user study. The results show that the graphical representation which we have developed for our trust model, called CertainTrust, fits to the needs of the users. Author
An Algorithm for Coplanar Camera Calibration

This paper proposes an algorithm to determine the camera parameters for coplanar camera calibration. The proposed method requires only one image to compute the camera parameters. The intermediate parameters defined in terms of the camera parameters are determined by a linear method. Then, the final intermediate parameters and the lens distortion coefficients are computed iteratively using a nonlinear optimization method in which the parameters obtained from the linear method are used as initial parameters. Finally, the camera parameters are determined from the final intermediate parameters. The proposed method is tested and compared with the conventional method using the synthetic images. The experimental results show that the camera parameters determined by the proposed method give accurate and stable.
Prions Adhere to Soil Minerals and Remain Infectious

An unidentified environmental reservoir of infectivity contributes to the natural transmission of prion diseases (transmissible spongiform encephalopathies [TSEs]) in sheep, deer, and elk. Prion infectivity may enter soil environments via shedding from diseased animals and decomposition of infected carcasses. Burial of TSE-infected cattle, sheep, and deer as a means of disposal has resulted in unintentional introduction of prions into subsurface environments. We examined the potential for soil to serve as a TSE reservoir by studying the interaction of the disease-associated prion protein (PrPSc) with common soil minerals. In this study, we demonstrated substantial PrPSc adsorption to two clay minerals, quartz, and four whole soil samples. We quantified the PrPSc-binding capacities of each mineral. Furthermore, we observed that PrPSc desorbed from montmorillonite clay was cleaved at an N-terminal site and the interaction between PrPSc and Mte was strong, making desorption of the protein difficult. Despite cleavage and avid binding, PrPSc bound to Mte remained infectious. Results from our study suggest that PrPSc released into soil environments may be preserved in a bioavailable form, perpetuating prion disease epizootics and exposing other species to the infectious agent.
Arcademis: a framework for object‐oriented communication middleware development

This paper presents Arcademis, a Java‐based framework for communication middleware development. Arcademis consists of a set of abstract classes, interfaces and concrete components that define the general architecture of middleware systems. Its main objective is to support the implementation of non‐monolithic and easily configurable middleware platforms. Arcademis can be used by middleware developers to deploy systems that meet the requirements of a particular network or technology. Instances of Arcademis can also be customized by distributed systems engineers to meet the requirements of a particular application. For example, new transport protocols, connection management policies, authentication algorithms or invocation semantics can be easily configured in middleware platforms derived from Arcademis. In order to illustrate the use of the framework, the paper describes the RME system, a middleware derived from Arcademis that adds a remote method invocation service to the CLDC configuration of Java 2 Micro Edition (J2ME). Copyright © 2006 John Wiley & Sons, Ltd.
In Anticipation: Educational (Im)mobilities, Structural Disadvantage, and Young People’s Futures

ABSTRACT This paper draws upon qualitative fieldwork undertaken in Hong Kong, over the space of a decade, to reflect upon how educational (im)mobilities are folded into the structures that would seem to determine young people’s anticipation of futures. It draws upon two large research projects in particular – one which involved children’s international migration in search of education; the other which examined examples of young people ‘stuck’ in Hong Kong and prescribed, by virtue of their ‘failure’ in the school system, particular circumscribed life chances. The paper attempts to change the spatial lens through which international education is viewed – away from the focus on ‘exodus’ (Abelmann, N., and Kang, J., 2014. Memoir/manuals of South Korean Pre‐College Study Abroad: Defending Mothers and Humanizing Children. Global Networks 14 (1), 1–22) towards a sense of ‘internalisation’ (and the impact that international education is having ‘at home’). The paper speaks to wider debates concerning educational migrations (the role of students as migrants) and the formative role that education (both domestic and international) plays in contemporary societies.
Supervised image segmentation via ground truth decomposition

This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning algorithms that induce a mapping from pixel features to individual pixel labels. In contrast we propose to first extract features from both images and labels. Subsequently we induce a mapping from pixel features to label features and synthesize the final output by combining the newly derived label components. We demonstrate the effectiveness of the proposed approach by applying log-Gabor filters to both input and ground truth images of mineral ore. Subsequently we train perceptrons and regression trees to produce individual output components that are combined in frequency space to create the final segmentation. Experimental results show significant improvements over contextual pixel labeling and over ensemble methods.
Development and validation of transgene constructs in order to generate bi-transgenic mice models for Diabetic Peripheral Neuropathy research

Diabetic peripheral neuropathy (DPN), a common complication of diabetes, involves nerve damage in the arms and legs. Segmental demyelination is one of the basic patterns observed in the pathology of DPN. Demyelinating neuropathies are those in which the Schwann cells (SCs) are primarily affected and these undergo substantial degeneration in diabetic neuropathy. Hence, it is of pertinence to investigate possible mechanisms which may contribute to the demyelination of SCs and the progression of DPN. To address this issue, this project aims to generate three different bi-transgenic mouse models that provide for the SC-specific expression of several transgenes that can be induced by the addition of the antibiotic doxycycline. For temporal, spatial and cell-specific control of transgene expression in mice, the above mentioned transgenes were constructed based on the Tet-On gene regulation system. In order to yield spatially regulated transgene expression, rtTA (reverse tetracycline transactivator) was placed under the control of the SC-specific promoter for 2 " , 3 "-cyclic nucleotide 3 "-phosphodiesterase. Placement of genes under the control of the rtTA-P tight system has been shown to display excellent dose-response characteristics, which allows not only a qualitative off-on transition but also a fine tuning of gene expression and the study of quantitative aspects of gene activity. The above mentioned transgenes constructed in this project were validated in Hek293T cells to ensure that they expressed in a tight and highly inducible manner. The transgene transfected cell lines when treated with doxycycline showed a dose-dependent expression of the gene of interest. Maximum gene induction was observed when treated with 0. 5μg/ml doxycycline. In the absence of doxycycline, almost no or minimal gene expression was observed. The transgenes were iv then excised out of the vector backbone for pronuclear microinjection. Once the transgenic mice are born, identified and validated, they shall be used for diabetic peripheral neuropathy research in the laboratory.
Visualization & Layout for Personal Photo Libraries

In this paper, we present visualization and layout algorithms that can enhance informal storytelling using personal digital data s uch as photos in a face-to-face social setting. In order to build a more intuitive browser for retr i val, navigation and story-telling, we introduce a novel optimized layout technique for la rge image sets which respects (contextsensitive) mutual similarities as visualized on a s hared 2-D display (a table-top). The experimental results show a more perceptually intui tive and informative visualization of traditional CBIR-based retrievals, providing not on ly a better understanding of the query context but also aiding the user in forming new queries. A framework for user-modeling is also introduced and tested. This allows the system to ad apt to the user’s preferences and relevance feedback.
Probabilistic modeling for IPTV network diagnosis and troubleshooting

In this paper, we propose two probabilistic modeling methods for IPTV network diagnosis, namely intolerable quality detection and device alarm analysis. The proposed methods can provide auxiliary information during troubleshooting processes, as well as inferring problematic devices automatically. Experimental results show that our models can distinguish problematic devices from normal ones and are more accurate than previous work under two evaluation criteria. Furthermore, we also demonstrate how we utilize these models in our actual network management system. It reveals that our methodologies are useful in finding out the service degradation proactively.
Model for English-Urdu Statistical Machine Translation

There are above 60 million first language speakers of Urdu and above 104 million second language speakers. Lot of knowledge on the internet available/useful to these speakers of Urdu is in English. The contrast in typology of both languages is interesting to study for Statistical Machine Translation. However, there is almost no parallel aligned data available freely for the selected language pair (English-Urdu). In this paper we discuss the issues of corpus alignment and share the results of baseline system prepared using Moses Decoder and other supporting tools.