Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA-26a Targets the Histone Methyltransferase Enhancer of Zeste homolog 2 during Myogenesis*

MicroRNA (miRNA) are important regulators of many bio×logical processes, but the targets for most miRNA are still poorly defined. In this study, we profiled the expression of miRNA during myogenesis, from proliferating myoblasts through to terminally differentiated myotubes. Microarray results identified six significantly differentially expressed miRNA that were more than 2-fold different in myotubes. From this list, miRNA-26a (miR-26a), an up-regulated miRNA, was further examined. Overexpression of miR-26a in murine myogenic C2C12 cells induced creatine kinase activity, an enzyme that markedly increases during myogenesis. Further, myoD and myogenin mRNA expression levels were also up-regulated. These results suggest that increased expression of miR-26a promotes myogenesis. Through a bioinformatics approach, we identified the histone methyltransferase, Enhancer of Zeste homolog 2 (Ezh2), as a potential target of miR-26a. Overexpression of miR-26a suppressed the activity of a luciferase reporter construct fused with the 3′-untranslated region of Ezh2. In addition, miR-26a overexpression decreased Ezh2 mRNA expression. These results reveal a model of regulation during myogenesis whereby the up-regulation of miR-26a acts to post-transcriptionally repress Ezh2, a known suppressor of skeletal muscle cell differentiation.
Pilot-Scale Testing of Non-Activated Biochar for Swine Manure Treatment and Mitigation of Ammonia, Hydrogen Sulfide, Odorous Volatile Organic Compounds (VOCs), and Greenhouse Gas Emissions

Managing the environmental impacts associated with livestock production is a challenge for farmers, public and regulatory agencies. Sustainable solutions that take into account technical and socioeconomic factors are needed. For example, the comprehensive control of odors, ammonia (NH3), hydrogen sulfide (H2S), and greenhouse gas (GHG) emissions from swine production is a critical need. Stored manure is a major source of gaseous emissions. Mitigation technologies based on bio-based products such as biochar are of interest due to the potential benefits of nutrient cycling. The objective of this study was to test non-activated (non-functionalized) biochar for the mitigation of gaseous emissions from stored manure. Specifically, this included testing the effects of: (1) time; and (2) dosage of biochar application to the swine manure surface on gaseous emissions from deep-pit storage. The biochar surface application was tested with three treatments (1.14, 2.28 and 4.57 kg·m−2 manure) over a month. Significant reductions in emissions were observed for NH3 (12.7–22.6% reduction as compared to the control). Concomitantly, significant increases in CH4 emissions (22.1–24.5%) were measured. Changes to emissions of other target gases (including CO2, N2O, H2S, dimethyl disulfide/methanethiol, dimethyl trisulfide, n-butyric-, valeric-, and isovaleric acids, p-cresol, indole, and skatole) were not statistically significant. Biochar treatment could be a promising and comparably-priced option for reducing NH3 emissions from stored swine manure.
Introducing CrossMapper: Another Tool for Mapping Musical Control Parameters

Development of new musical interfaces often requires experimentation with the mapping of available controller inputs to output parameters. Useful mappings for a particular application may be complex in nature, with one or more inputs being linked to one or more outputs. Existing development environments are commonly used to program such mappings, while code libraries provide powerful data-stream manipulation. However, room exists for a standalone application with a simpler graphical user interface for dynamically patching between inputs and outputs. This paper presents an early prototype version of a software tool that allows the user to route control signals in real time, using various messaging formats. It is cross-platform and runs as a standalone application in desktop and Android OS versions. The latter allows the users of mobile devices to experiment with mapping signals to and from physical computing components using the inbuilt multi-touch screen. Potential uses therefore include real-time mapping during performance in a more expressive manner than facilitated by existing tools.
Recognition of ATGA sequences by the unfused aromatic dication DB293 forming stacked dimers in the DNA minor groove.

Furamidine and related diamidines represent a promising series of drugs active against widespread parasites, in particular the Pneumocystic carinii pathogen. In this series, the phenylfuranbenzimidazole diamidine derivative DB293 was recently identified as the first unfused aromatic dication capable of forming stacked dimers in the DNA minor groove of GC-containing sequences. Here we present a detailed biochemical and biophysical characterization of the DNA sequence recognition properties of DB293. Three complementary footprinting techniques using DNase I, Fe(II)-EDTA, and an anthraquinone photonuclease were employed to locate binding sites for DB293 in different DNA restriction fragments. Two categories of sites were identified by DNase I footprinting: (i) 4/5 bp sequences containing contiguous A.T pairs, such as 5'-AAAA and 5'-ATTA; and (ii) sequences including the motif 5'-ATGA.5'-TCAT. In particular, a 13-bp sequence including two contiguous ATGA motifs provided a highly preferential recognition site for DB293. Quantitative footprinting analysis revealed better occupancy of the 5'-ATGA site compared to the AT-rich sites. Preferential binding of DB293 to ATGA sites was also observed with other DNA fragments and was confirmed independently by means of hydroxyl radical footprinting generated by the Fe(II)-EDTA system, as well as by a photofootprinting approach using the probe anthraquinone-2-sulfonate (AQS). In addition, this photosensitive reagent revealed the presence of sites of enhanced cutting specific to DB293. This molecule, but not other minor groove binders such as netropsin, induces specific local structural changes in DNA near certain binding sites, as independently shown by DNase I and the AQS probe. Recognition of the ATGA sequence by DB293 was investigated further using melting temperature experiments and surface plasmon resonance (SPR). The use of different hairpin oligonucleotides showed that DB293 can interact with AT sites via the formation of 1:1 drug-DNA complexes but binds much more strongly, and cooperatively, to ATGA-containing sequences to form 2:1 drug-DNA complexes. DB293 binds strongly to ATGA sequences with no significant context dependence but is highly sensitive to the orientation of the target sequence. The formation of 2:1 DB293/DNA complexes is abolished by reversing the sequence 5'-ATGA-->3'-ATGA, indicating that directionality plays an important role in the drug-DNA recognition process. Similarly, a single mutation in the A[T-->G]GA sequence is very detrimental to the dimer interactions of DB293. From the complementary footprinting and SPR data, the 5'-ATGA sequence is identified as being a highly favored dimer binding site for DB293. The data provide clues for delineating a recognition code for diamidine-type minor groove binding agents, and ultimately to guide the rational design of gene regulatory molecules targeted to specific sites of the genetic material.
Assessing the accuracy of non-rigid registration with and without ground truth

We compare two methods for assessing the performance of groupwise non-rigid registration algorithms. The first approach, which has been described previously, utilizes a measure of overlap between ground-truth anatomical labels. The second, which is new, exploits the fact that, given a set of nonrigidly registered images, a generative statistical model of appearance can be constructed. We observe that the quality of this model depends on the quality of the registration, and define measures of model specificity and generalisation - based on comparing synthetic images sampled from the model, with those in the original image set - that can be used to assess model/registration quality. We show that both approaches detect the loss of registration accuracy as the alignment of a set of correctly registered MR images of the brain is progressively perturbed. We compare the sensitivities of the two approaches and show that, as well as requiring no ground truth, specificity provides the most sensitive measure of misregistration
Predicting User Reactions to System Error

This paper focuses on the analysis and prediction of so-called aware sites, defined as turns where a user of a spoken dialogue system first becomes aware that the system has made a speech recognition error. We describe statistical comparisons of features of these aware sites in a train timetable spoken dialogue corpus, which reveal significant prosodic differences between such turns, compared with turns that 'correct' speech recognition errors as well as with 'normal' turns that are neither aware sites nor corrections. We then present machine learning results in which we show how prosodic features in combination with other automatically available features can predict whether or not a user turn was a normal turn, a correction, and/or an aware site.
Robust image segmentation for overhead real time motorbike counting

Motorbikes are often difficult to detect in overhead road traffic images due to the variability of color, size, shape as well as trajectories. This paper tackles the problem of robust and real time image segmentation for motorbike counting. First of all, we perform background subtraction. Foreground blobs are then refined with Laplacian densities. This fusion enables to achieve a significant robustness to cast shadows. Thus, simple features, such as area, height and width, can be used to discriminate motorbikes from other vehicles. Our real time algorithm achieves interesting performances on multiple real traffic video sequences.
Algorithmic approach to quantifying the hydrophobic force contribution in protein folding

Though the electrostatic, ionic, van der Waals, Lennard-Jones, hydrogen bonding, and other forces play an important role in the energy function minimized at a protein's native state, it is widely believed that the hydrophobic force is the dominant term in protein folding. Here we attempt to quantify the extent to which the hydrophobic force determines the positions of the backbone alpha-carbon atoms in PDB data, by applying Monte-Carlo and genetic algorithms to determine the predicted conformation with minimum energy, where only the hydrophobic force is considered (i.e. Dill's HP-model, and refinements using Woese's polar requirement). This is done by computing the root mean square deviation between the normalized distance matrix D = (di,j) (di,j is normalized Euclidean distance between residues ri and rj) for PDB data with that obtained from the output of our algorithms. Our program was run on the database of ancient conserved regions drawn from GenBank 101 generously supplied by W. Gilbert's lab, as well as medium-sized proteins (E. Coli RecA, 2reb, Erythrocruorin, 1eca, and Actinidin 2act). The root mean square deviation (RMSD) between distance matrices derived from the PDB data and from our program output is quite small, and by comparison with RMSD between PDB data and random coils, allows a quantification of the hydrophobic force contribution. A preliminary version of this paper appeared at GCB'99 (http:¿bibiserv.techfak.uni-bielefeld.de/gcb9 9/).
WCET-aware Software Based Cache Partitioning for Multi-Task Real-Time Systems

Caches are a source of unpredictability since it is very difficult to predict if a memory access results in a cache hit or miss. In systems running multiple tasks steered by a preempting scheduler, it is even impossible to determine the cache behavior since interrupt-driven schedulers lead to unknown points of time for context switches. Partitioned caches are already used in multi-task environments to increase the cache hit ratio by avoiding mutual eviction of tasks from the cache. For real-time systems, the upper bound of the execution time is one of the most important metrics, called the Worst-Case Execution Time (WCET). In this paper, we use partitioning of instruction caches as a technique to achieve tighter WCET estimations since tasks can not be evicted from their partition by other tasks. We propose a novel WCET-aware cache partitioning algorithm, which determines the optimal partition size for each task with focus on decreasing the system's WCET for a given set of possible partition sizes. Employing this algorithm, we are able to decrease the WCET depending on the number of tasks in a set by up to 34%. On average, reductions between 12% and 19% can be achieved.
Sliding Mode Control of Magnetic Levitation System using Nonlinear Time-Varying Sliding Surface

A new sliding surface design approach for magnetic levitation system is proposed that varies the sliding surface in a nonlinear and time-varying fashion. The control law is designed by using the surface that is defined in a new co-ordinate axis. The nonlinear surface is then moved in a proper direction by using a timevarying function. Simulations have been performed on a secondorder nonlinear model of a magnetic levitation system. The result of the new design method is compared with the classical sliding mode controller possessing a discretely moving sliding surface. From the results we can conclude that the reaching time has considerably reduced and robustness to disturbance has increased. Also the phase plane portrait has much smoother trajectories. Keywords--Magnetic levitation system, nonlinear time varying sliding surface, sliding mode control, sliding surface design
Using the Pn Potts model with learning methods to segment live cell images

We present a segmentation method for live cell images, using graph cuts and learning methods. The images used here are particularly challenging because of the shared grey-level distributions of cells and background, which only differ by their textures, and the local imprecision around cell borders. We use the Pn Potts model recently presented by Kohli et al. [9]: functions on higher-order cliques of pixels are included into the traditional Potts model, allowing us to account for local texture features, and to find the optimal solution efficiently. We use learning methods to define the potential functions used in the Pn Potts model. We present the model and the learning methods we used, and compare our segmentation results with similar work in cytometry. While our method performs similarly, it requires little manual tuning and thus is straightforward to adapt to other images.
A test for the origin of quasar redshifts

It is commonly accepted that quasar redshifts have a cosmological character and that most of the quasars are at Gpc distances. However, there are some cases where several quasars with completely different redshifts and a nearby active galaxy are aligned in a certain way or occupy a very small patch on the sky, which is claimed by some authors to be unlikely to happen by chance. Is there a small subset of quasars with non-cosmological redshifts? For quasars apparently associated with galaxies, we consider two scenarios for the origin of their redshift: (i) a change in the scale factor of the whole Universe (standard, cosmological scenario), and (ii) a velocity-induced Doppler shift of the spectrum of a nearby object (local, ejection scenario). We argue for a simple astrometric test which can distinguish between these two sources of quasar redshifts by constraining their proper motions. We give the predictions for the maximum possible proper motions of a quasar for the cosmological and local scenarios of the origin of their redshifts. We apply these theoretical results to the Bukhmastova catalogue, which contains more than 8000 close quasi-stellar object–galaxy associations. In the standard interpretation of quasar redshifts, their typical proper motions are a fraction of μas, and beyond the reach of planned astrometric missions such as GAIA and SIM. On the other hand, the quasars ejected from local active galactic nuclei at velocities close to the speed of light would have proper motions 5–6 orders of magnitude larger, which would easily be measurable with future astrometric missions, or even in some cases with HST, VLT and Keck telescope. The distributions of proper motions for the cosmological and local scenarios are very well separated. Moreover, the division corresponds nicely to the expected accuracy from GAIA and SIM.
Developmental Stability and Fitness: The Evidence Is Not Quite So Clear

Commonwealth Scientific and Industrial Research Organisation, such an approach is that, on average, half of the studies Division of Entomology, GPO Box 1700, Canberra, ACT 2601, examined will show an effect, significant or not, in the Australia predicted direction. In order to reject the null hypothesis, greater than half the studies should support the predicSubmitted January 21, 1998; Accepted April 29, 1998 tion. For such an approach to be valid, all studies examined (i.e., votes cast) must specifically address the hypothesis of concern, in this case, the relationship between developmental stability and one or more individual fit
The modified Cramer-Rao bound for channel estimation in quantize-and-forward cooperative systems

The quantize-and-forward (QF) cooperative protocol can effectively be used to combat fading in systems using half-duplex relay terminals. While the outage behavior of the QF protocol has been extensively investigated, few research has been performed on the impact of imperfect channel estimates. In this contribution, a lower bound (LB) on the estimation error is obtained for a one-hop relaying channel with data quantization at the relay. To this purpose the modified Cramer-Rao (MCRB) bound is calculated, which, compared to the true Cramer-Rao bound (CRB), is a looser and computationally less complex bound that converges to the CRB in the high signal-to-noise ratios. By using a general system model for the relay channel, the obtained results can be utilized to benchmark a wide variety of systems.
Enhancing Information Retrieval using Concept- Based Mining Model with Feature Extraction and Clustering

Most of the common techniques in text mining are based on the statistical analysis of a term, either word or phrase. Statistical analysis of a term frequency captures the importance of the term within a document only. However, two terms can have the same frequency in their documents, but one term contributes more to the meaning of its sentences than the other term. Thus, the underlying text mining model should indicate terms that capture the semantics of text. In this case, the mining model can capture terms that present the concepts of the sentence, which leads to discovery of the topic of the document. Now a day‟s all the information‟s are available with clear diagrammatic explanation or with related images. An image examination method can automate the recognition of landmarks and events in large image collections, significantly getting better Content utilization experience. The wide adoption of photo sharing applications and the enormous amounts of user-generated content uploaded to them raises an information overload issue for users. The concept-based mining model can effectively discriminate between non important terms with respect to sentence semantics and terms which hold the concepts that represent the sentence meaning. The proposed mining model consists of sentence-based concept analysis, document-based concept analysis, corpus-based concept-analysis, and concept-based similarity measure. The term which contributes to the sentence semantics is analyzed on the sentence, document, and corpus levels rather than the traditional analysis of the document only. An Automated Content Organization technique to defeat such an overload is to collect images into groups based on their similarity and then use the derived clusters to support navigation and browsing of the collection. In this paper, we present a community detection (i.e. graph-based clustering) approach that makes use of both visual and tagging features of images in order to efficiently extract groups of correlated images within large image collections. We perform clustering on such image similarity graphs by means of community detection, a process that identifies on the graph groups of nodes that are more closely associated to each other. We categorize the resultant image clusters as landmarks or events by use of features related to the temporal, community, and label characteristics of image clusters. Keywords— landmarks and events, Content Organization technique, similarity, clusters.
Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data

This paper considers nonparametric estimation in a varying coefficient model with repeated measurements (Y ij , X ij , t ij ), for i = 1 n and j = 1 n i , where X ij = (X ij .,,X ijk ) T and (Y ij , X ij , t ij ) denote the jth outcome, covariate and time design points, respectively, of the ith subject. The model considered here is Y ij = X ij T β(t ij )+ e i (t ij ), where β(t)=(β 0 (t). , β k (t)) T , for k≥ 0, are smooth nonparametric functions of interest and e i (t) is a zero-mean stochastic process. The measurements are assumed to be independent for different subjects but can be correlated at different time points within each subject. Two nonparametric estimators of β(t), namely a smoothing spline and a locally weighted polynomial, are derived for such repeatedly measured data. A crossvalidation criterion is proposed for the selection of the corresponding smoothing parameters. Asymptotic properties, such as consistency, rates of convergence and asymptotic mean squared errors, are established for kernel estimators, a special case of the local polynomials. These asymptotic results give useful insights into the reliability of our general estimation methods. An example of predicting the growth of children born to HIV infected mothers based on gender, HIV status and maternal vitamin A levels shows that this model and the corresponding nonparametric estimators are useful in epidemiological studies.
The association of retinal structure and macular pigment distribution.

PURPOSE Macular pigment optical density (MPOD) and age-related macular degeneration (AMD) are thought to be associated; however, the details are not yet understood clearly. This study aimed at investigating how retinal anatomic structures relate with the spatial MPOD distribution in single eyes. METHODS In a subgroup of the third follow-up examination of the Münster Aging and Retina Study (MARS) cohort (mean age, 78.4 years), 124 single eyes of 79 participants with early AMD were examined. The MPOD was assessed using 2-wavelength autofluorescence (AF). Retinal thickness (RT) and fovea pit profile slopes were measured using optical coherence tomography (OCT). The results were analyzed for interocular correlation in 58 pairs of eyes, and for the association of MPOD distribution patterns with RT using uni- and multivariate statistical methods. RESULTS The interocular correlations for several measures of RT and RT layers were high (P < 0.001). The RT was inversely and significantly related to MPOD at 1.0° and at 2.0° from the foveal center, but not to central MPOD. After controlling for sex, age, smoking, and spherical equivalent, RT was significantly thinner (-39.7 μm, P < 0.001) in eyes with ring-like compared to normal MPOD distribution. In particular, a thinner layer between internal and external limiting membrane showed strong associations with ring-like structures. CONCLUSIONS Higher values of MPOD at 1° and 2°, as well as a ring-like distribution of MPOD were associated significantly with thinner maculae, due to thinner inner retinal layers. The MPOD distribution was unrelated to the slope of the foveal pit or the choroidal thickness. Our results suggest that the retinal section between the internal and external limiting membrane is involved in the spatial distribution of MPOD.