Miracle-dz/UniFAR-FTUs huggingface dataset:
'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.
Learning Relational Bayesian Classifiers on the Semantic Web

With the advent of the Semantic Web, there is an increased availability of meta data (ontologies) that make explicit the semantic commitments associated with data and an urgent need for machine learning algorithms for building predictive models from such data. Usually, there is no unique global interpretation of data from semantically disparate, autonomous sources. Furthermore, it is neither feasible nor desirable to integrate data from sources on the Semantic Web in a centralized data warehouse. In this paper, we formulate the problem of learning classifiers from a set of related, semantically heterogeneous data sources on the Semantic Web from a user’s point of view. We describe a general strategy for transforming algorithms for learning classifiers from data into algorithms for learning classifiers from a set of semantically heterogeneous distributed data sources. We apply this strategy to the task of learning relational Bayesian classifiers from a collection of such data sources. The proposed approach can be generalized to other relational learning algorithms. Our results provide some of the essential elements of approaches for acquiring useful knowledge from information sources that are becoming available on the Semantic Web.
Measurement and Adaptive Decoupling of Cross-Saturation Effects and Secondary Saliencies in Sensorless-Controlled IPM Synchronous Machines

This paper analyzes effects of magnetic saturation, including cross-saturation and secondary saliencies, on saliency- based sensorless control of interior PM synchronous machines. These effects are mitigated by adaptively decoupling saturation induced-saliencies via a structured neural network. The paper includes identification of the dominant, saturation-induced components of the carrier signal current interfering with the rotor position-dependent component being tracked, characterization of these components, and implementation of a non-linear, adaptive, saturation-induced components structured neural network model to perform their decoupling.
Patterns for Effective Management of Virtual Projects: Theory and Evidence

The management of virtual projects is fundamentally different from that of traditional projects. Furthermore, the research in this area comes from different reference disciplines and perspectives, and a unified view or theory of best practices does not yet exist. Being able to combine perspectives in a seamless way with skills and technology could provide integrative blueprints for best practices in virtual projects. We use the theoretical frame of patterns to propose such a view. We focus on three concepts as the underlying theoretical elements for identifying patterns of effectiveness in virtual project management: (1) coordination, (2) communication, and (3) control. As a first step in the identification of specific patterns, we conducted a series of virtual focus groups with participants from industry who had real experience with virtual projects. The brainstorming data from the focus groups was analyzed to develop an initial set of patterns. The study represents a first step in an iterative and evolutionary process.
An application of the supervoxel-based Fuzzy C-Means with a GPU support to segmentation of volumetric brain images

In this paper the problem of segmentation of volumetric medical images is considered. The fast and effective segmentation is obtained by applying the proposed approach which combines the idea of supervoxels and the Fuzzy C-Means algorithm. In particular, Fuzzy C-Means is used to cluster supervoxels produced by the fast 3D region growing. Additional acceleration of the method is achieved with the support of graphical processor (GPU). The detailed description of the proposed approach is given. The results of applying the method to volumetric CT and MRI brain images and CT images of various phantoms are presented, analysed and discussed. The issues related to accuracy of the method, memory workload and the running time are also considered.
TM-align: a protein structure alignment algorithm based on the TM-score

We have developed TM-align, a new algorithm to identify the best structural alignment between protein pairs that combines the TM-score rotation matrix and Dynamic Programming (DP). The algorithm is ∼4 times faster than CE and 20 times faster than DALI and SAL. On average, the resulting structure alignments have higher accuracy and coverage than those provided by these most often-used methods. TM-align is applied to an all-against-all structure comparison of 10 515 representative protein chains from the Protein Data Bank (PDB) with a sequence identity cutoff <95%: 1996 distinct folds are found when a TM-score threshold of 0.5 is used. We also use TM-align to match the models predicted by TASSER for solved non-homologous proteins in PDB. For both folded and misfolded models, TM-align can almost always find close structural analogs, with an average root mean square deviation, RMSD, of 3 Å and 87% alignment coverage. Nevertheless, there exists a significant correlation between the correctness of the predicted structure and the structural similarity of the model to the other proteins in the PDB. This correlation could be used to assist in model selection in blind protein structure predictions. The TM-align program is freely downloadable at .
Knowledge reuse for software reuse

Software reuse can provide significant improvements in software productivity and quality whilst reducing development costs. Expressing software reuse intentions can be difficult though. A developer may aspire to reuse a software component but experience difficulty expressing their reuse intentions in a manner that is compatible with, or understood by, the component retrieval system. Various intelligent retrieval techniques have been developed that assist a developer in locating or discovering components in an efficient manner. These solutions share a common shortcoming: the developer must be capable of anticipating all reuse opportunities and initiating the retrieval process. There is a need for a comprehensive technique that not only assists with retrievals but that can also identify reuse opportunities. This paper advocates that component-based reuse can be supported through knowledge collaboration. Often programming tasks and solutions are replicated; this characteristic of software can be exploited for the benefit of future developments. Through the mining of existing source code solutions, knowledge, relating to how components are used by developers, can be extracted. Based on a developer's current programming task, this knowledge can subsequently be filtered and used to recommend a candidate set of reusable components. This novel recommendation approach applies and extends commonly used Information Retrieval and Information Filtering techniques such as Collaborative Filtering, Content-Based Filtering, and Bayesian Clustering Models, to the software reuse domain. This recommendation technology is applied to several thousand open-source Java classes. The most effective recommendation algorithm produces recommendations of a high quality at a low cost.
A Mathematical Motivation for Complex-Valued Convolutional Networks

Abstract A complex-valued convolutional network (convnet) implements the repeated application of the following composition of three operations, recursively applying the composition to an input vector of nonnegative real numbers: (1) convolution with complex-valued vectors, followed by (2) taking the absolute value of every entry of the resulting vectors, followed by (3) local averaging. For processing real-valued random vectors, complex-valued convnets can be viewed as data-driven multiscale windowed power spectra, data-driven multiscale windowed absolute spectra, data-driven multiwavelet absolute values, or (in their most general configuration) data-driven nonlinear multiwavelet packets. Indeed, complex-valued convnets can calculate multiscale windowed spectra when the convnet filters are windowed complex-valued exponentials. Standard real-valued convnets, using rectified linear units (ReLUs), sigmoidal (e.g., logistic or tanh) nonlinearities, or max pooling, for example, do not obviously exhibit the same exact correspondence with data-driven wavelets (whereas for complex-valued convnets, the correspondence is much more than just a vague analogy). Courtesy of the exact correspondence, the remarkably rich and rigorous body of mathematical analysis for wavelets applies directly to (complex-valued) convnets.
Relaxin decreases the severity of established hepatic fibrosis in mice

Hepatic fibrosis is characterized by excess collagen deposition, decreased extracellular matrix degradation and activation of the hepatic stellate cells. The hormone relaxin has shown promise in the treatment of fibrosis in a number of tissues, but the effect of relaxin on established hepatic fibrosis is unknown. The aim of this study was to determine the effect of relaxin on an in vivo model after establishing hepatic fibrosis
Performance Analysis of a Built-In Planar Inverted F Antenna for 800 MHz Band Portable Radio Units

The pattern averaging gain (PAG) method to estimate the average gain of mobile antennas in a multipath propagation environment is proposed. By using this method and a wire-grid model, the radiation characteristics of the planar inverted F antenna (PIFA) mounted on a portable radio case is analyzed. In particular, the variation of the antenna gain with the radio case dimensions and inclination angle of the radio case during operation is clarified. Also, the effect on antenna patterns of the operator holding the portable radio is experimentally investigated. Based on this analysis, the antenna configuration with the PIFA element mounted on the lateral side of the radio case is found to be most suitable for portable radio units. In addition, an appropriate selection of the radio case dimensions is found to result in further improvements in the antenna bandwidth.
Application of Serial Analysis of Gene Expression to the Study of the Gene Expression Profile of Leishmania infantum chagasi Promastigote

This study describes the application of the LongSAGE methodology to study the gene expression profile in promastigotes of Leishmania infantum chagasi. A tag library was created using the LongSAGE method and consisted of 14,208 tags of 17 bases. Of these, 8,427 (59.3%) were distinct. BLAST research of the 1,645 most abundant tags showed that 12.8% of them identified the coding sequences of genes, while 82% (1,349/1,645) identified one or more genomic sequences that did not correspond with open reading frames. Only 5.2% (84/1,645) of the tags were not aligned to any position in the L. infantum genome. The UTR size of Leishmania and the lack of CATG sites in some transcripts were decisive for the generation of tags in these regions. Additional analysis will allow a better understanding of the expression profile and discovering the key genes in this life cycle.
A genetic algorithm for scratch removal in static images

This paper investigates the removal of line scratches from old moving pictures and gives a twofold contribution. First, it presents a simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, which is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conventional linear interpolation; this transformation is the starting point of the optimisation process.
Persistence of CTL Clones Targeting Melanocyte Differentiation Antigens Was Insufficient to Mediate Significant Melanoma Regression in Humans

Purpose: Adoptive transfer of autologous tumor infiltrating lymphocytes (TIL) can mediate durable cancer regression in selected patients with metastatic melanoma. However, the tumor antigens associated with these favorable responses remain unclear. We hypothesized that a clinical strategy involving the iterative adoptive transfer of selected autologous antigen-specific T-cell clones could help systematically define immunologic targets associated with successful cancer therapy, without the interpretative ambiguity of transferring polyclonal populations. Here, we evaluated the clinical efficacy of CD8+ T-cell clones specific for the melanocyte differentiation antigens (MDA), gp100 and MART-1, respectively. Experimental Design: We conducted two consecutive phase II clinical trials involving the adoptive transfer of highly selected autologous antigen-specific CD8+ T-cell clones against gp100 and MART-1, respectively. Fifteen patients with HLA-A2+ treatment-refractory metastatic melanoma received highly avid MDA-specific CD8+ T-cell clones specific for either gp100 (n = 10) or MART-1 (n = 5) with or without intravenous interleukin-2 (IL2) after a lymphodepleting myeloablative preparative regimen. Results: Of the 15 treated patients, we observed immune-mediated targeting of skin melanocytes in 11 patients (73%) and clonal engraftment in eight patients (53%) after cell transfer. There were only transient minor tumor regressions observed, but no objective tumor responses based on Response Evaluation Criteria in Solid Tumor (RECIST) criteria. Conclusions: Despite successful clonal repopulation and evidence of in vivo antigen targeting, the poor therapeutic efficacy after the adoptive transfer of autologous MDA-specific T cells raises significant concerns regarding future immunotherapy efforts targeting this class of tumor antigens. Clin Cancer Res; 21(3); 534–43. ©2014 AACR.
Modalities for the Assessment of Burn Wound Depth

Objective: Burn wound depth is a significant determinant of patient treatment and morbidity. While superficial partial-thickness burns generally heal by re-epithelialization with minimal scarring, deeper wounds can form hypertrophic or contracted scars, often requiring surgical excision and grafting to prevent a suboptimal result. In addition, without timely intervention, more superficial burn wounds can convert to deeper wounds. As such, the rapid and accurate assessment of burn wound depth is a priority in treating burn-injured patients. The object of this article is to review current research on modalities useful in the assessment of burn wound depth with emphasis on the relative costs and benefits of each technique. Methods: PubMed and Cochrane computerized databases were used for data retrieval, using the search terms “burns,” “burn wounds,” “burn depth,” “burn depth measurement,” and “burn depth progression. ” In addition, bibliographic references from prior reviews of burn depth were reviewed. All peer-reviewed, English-language articles relevant to the topic of burn depth measurement were reviewed, including those focusing on animal and human populations. Where appropriate, conclusions drawn from review articles and expert analyses were included. Results: Although bedside evaluation remains the most common modality of diagnosing the depth of burn wounds, recent technological advances have broadened the scope of depth assessment modalities available to clinicians. Other depth assessment techniques include biopsy and histology, and perfusion measurements techniques such as thermography, vital dyes, indocyanine green video angiography, and laser Doppler techniques. Conclusion: Of the depth assessment modalities currently used in clinical practice, LDI and ICG video angiography offer the best data-supported estimates of accuracy. Until the future of new modalities unfolds, a combination of clinical evaluation and another modality—thermography, biopsy, or, ideally, ICG video angiography or LDI—is advised to best assess the depth of acute burn wounds.
The Inner Sense of Action

We live in a meaningful world. Our capacity to deal with the ‘external world’ is constituted by the possibility of modifying the world by means of our actions; by the possibility of representing the world as an objective reality; and by the possibility of experiencing phenomenally this same objective reality, from a situated, self-conscious perspective. It is tempting to address these different articulations of the sense of ‘being related to the world’, of our intentional relation to the world, by using different languages, different methods of investigations, perhaps even different ontologies. In the present paper I will start to explore the possibility of reconciling some of these different articulations of intentionality from a neurobiological perspective. I will confine my analysis to the relationship between agency and representation and I will show how representation is intrinsically related to action control. To that purpose, I will present a new account of action, arguing against what is still commonly held as its proper definition, namely the final outcome of a cascade-like process that starts from the analysis of sensory data, incorporates the result of decision processes, and ends up with responses (actions) to externallyor internally-generated stimuli. I will argue against this account of action by presenting and discussing recent findings from the investigation of neural mechanisms that are at the basis of sensorimotor integration. It will become clear that the so-called ‘motor functions’ of the nervous system not only provide the means to control and execute action but also to represent it. Actually, following this view, action control and action representation become two sides of the same coin. One of the advantages of this approach is its empirical testability. If the results of this analysis turn out to be correct, we have, as philosophical pay-off, the possibility of overcoming the dichotomy between functional and semantic properties, by showing that causal properties are content properties. The neurophysiological
Single- and multi- carrier IDMA schemes with cyclic prefixing and zero padding techniques

In this paper, we investigate single-carrier (SC) and multi-carrier IDMA schemes with cyclic prefixing (CP) and zero padding (ZP) techniques. These schemes are called SC-IDMA-CP, SC-IDMA-ZP, orthogonal frequency-division multiplexing (OFDM)-IDMA-CP and OFDM-IDMA-ZP, respectively. By exploiting the circulant property of channel matrices, the multi-user detection of these schemes can be efficiently realised with per-user complexity independent of the number of users and the length of inter-symbol interference (ISI) channels. We show the potential advantages of ZP-based schemes in power efficiency and convergence speed. Simulation results are provided to compare the four schemes. Copyright © 2008 John Wiley & Sons, Ltd.
The Relevance of Voice Quality Features in Speaker Independent Emotion Recognition

This paper investigates the classification of different emotional states using presodic and voice quality information. We want to exploit the usage of different phonation types within the production of emotions. Therefore, as features we use prosodic features, voice quality parameters, and different combinations of both types. We study how prosodic and voice quality features overlap or complement each other in the application of emotion recognition. The classification is speaker independent and uses a reduced subset of 8 features and a Bayesian classifier.
Discussion of "Reserve Requirements for Price and Financial Stability: When Are They Effective?" ∗

Since the onset of the 2008 financial crisis, many economists have studied the effects of unconventional monetary policies such as credit-easing policies or actions aimed at altering the maturity structure of the private sector’s asset holdings. But surprisingly, there has been relatively little work on one of the traditional policy tools of a central bank—required reserve ratios—and how required reserves might be used as a cyclical policy instrument. Christian Glocker and Peter Towbin fill this gap by employing a modern dynamic stochastic general equilibrium (DSGE) model of a small open economy to analyze the use of reserve requirements as a tool for cyclical stabilization. At one time, we all learned that central banks had three policy instruments—the quantity of non-borrowed reserves, the interest rate charged on discount window borrowing, and the required reserve ratio. The first two instruments operated by affecting the supply of bank reserves; the third worked by affecting the demand for reserves. Then, many central banks adopted a short-term interbank rate as their primary policy instrument. Doing so made the quantity of non-borrowed reserves an endogenous variable, adjusting to ensure reserve supply and demand were consistent with the policy interest rate. Under such a policy regime, the discount rate and reserve requirement became irrelevant. Of course, this wasn’t (and isn’t) true of developing economies. There, central banks continued to