Miracle-dz/UniFAR-FTUs huggingface dataset:
UniMoG—a unifying framework for genomic distance calculation and sorting based on DCJ

Summary: UniMoG is a software combining five genome rearrangement models: double cut and join (DCJ), restricted DCJ, Hannenhalli and Pevzner (HP), inversion and translocation. It can compute the pairwise genomic distances and a corresponding optimal sorting scenario for an arbitrary number of genomes. All five models can be unified through the DCJ model, thus the implementation is based on DCJ and, where reasonable, uses the most efficient existing algorithms for each distance and sorting problem. Both textual and graphical output is possible for visualizing the operations. Availability and implementation: The software is available through the Bielefeld University Bioinformatics Web Server at http://bibiserv.techfak. uni-bielefeld.de/dcj with instructions and example data. Contact: rhilker@cebitec.uni-bielefeld.de
Semi-quantitative analysis of Ruminococcus flavefaciens, Fibrobacter succinogenes and Streptococcus bovis in the equine large intestine using real-time polymerase chain reaction

There is a need to further our understanding of the role that the equine hindgut ecosystem plays in digestive processes and diseases. The aim of the present study was to utilise the real-time PCR technique to determine the abundance of candidate cellulolytic (Ruminococcus flavefaciens; Fibrobacter succinogenes) and non-cellulolytic (Streptococcus bovis) bacteria in lumen contents from the caecum, ventral and dorsal colon, and rectum of healthy horses (n 14). Total DNA was extracted from frozen and lyophilised lumen contents, and PCR primers and Taqman® probes were designed based on 16S rDNA sequences for specific detection of candidate bacterial species. Overall, in frozen and lyophilised digesta, there were significantly (P < 0·01) fewer candidate bacteria in the caecum than the dorsal colon and rectum. In frozen digesta, candidate bacteria levels were similar between the ventral colon, dorsal colon and rectum, but in lyophilised digesta there were significantly (P < 0·05) higher levels of bacteria in the dorsal colon and rectum. Frozen digesta contained disparate levels of candidate bacteria such that R. flavefaciens > F. succinogenes > S. bovis (P < 0·05), while in lyophilised digesta R. flavefaciens was present in significantly (P < 0·05) greater amounts than F. succinogenes and S. bovis. R. flavefaciens and F. succinogenes were abundant at significantly (P < 0·05) greater levels in lyophilised digesta v. frozen digesta, with no difference in S. bovis levels. These data indicate that for these bacteria at least, faeces are a suitable model for studying the bacterial ecosystem within the equine colon. The present study also indicates that the preservation method of digesta affects levels of bacteria detected.
Urdu Caption Text Detection using Textural Features

The amount of multimedia data has increased manifolds in the recent years. This calls for development of efficient retrieval techniques. Among various aspects of content based retrieval, textual content appearing in videos and images serves as a powerful semantic index. Development of such a retrieval system requires detection of text regions, recognition of detected text and generation of indices on keywords. Among these, the focus of the present study lies on detection of textual content from video frames. More specifically, we target the caption Urdu text appearing in News and entertainment channels. A series of image analysis operations is first carried out to identify candidate text blocks in the image. Features extracted from text and non-text regions using Gabor filters and Curvelet transform are fed to two classifiers namely artificial neural network and support vector machine. Evaluations on a database of 1000 video frames reported promising precision and recall.
Breaking the Bandwidth Barrier: Geometrical Adaptive Entropy Estimation

Estimators of information theoretic measures, such as entropy and mutual information, are a basic workhorse for many downstream applications in modern data science. State-of-the-art approaches have been either geometric [nearest neighbor (NN)-based] or kernel-based (with a globally chosen bandwidth). In this paper, we combine both these approaches to design new estimators of entropy and mutual information that outperform the state-of-the-art methods. Our estimator uses local bandwidth choices of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-NN distances with a finite <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>, independent of the sample size. Such a local and data dependent choice ameliorates boundary bias and improves performance in practice, but the bandwidth is vanishing at a fast rate, leading to a non-vanishing bias. We show that the asymptotic bias of the proposed estimator is <italic>universal</italic>; it is independent of the underlying distribution. Hence, it can be precomputed and subtracted from the estimate. As a byproduct, we obtain a unified way of obtaining <italic>both</italic> the kernel and NN estimators. The corresponding theoretical contribution relating the asymptotic geometry of nearest neighbors to order statistics is of independent mathematical interest.
Incremental algorithm based on wedge sampling for estimating clustering coefficient with MapReduce

Clustering coefficient is widely used in many real-world applications, such as social network analysis and community mining. However, it is expensive to compute clustering coefficient for the large and dynamic networks. To improve the performance of clustering coefficient computing for these dynamic graphs, we propose an incremental algorithm based on random wedge sampling and implement the proposed algorithm upon MapReduce. The proposed algorithm reuses previous result and updates the estimate incrementally, instead of computing the whole dynamic graph from scratch. Experiments on real-world graphs demonstrate that the proposed algorithm is accurate and efficient. Compared with a state-of-the-art MapReduce algorithm, the proposed algorithm runs faster without scarifying accuracy of estimate.
The sound insulation of autoclaved aerated concrete panels lined with gypsum plasterboard

This paper gives the results of 27 laboratory measurements of the sound insulation of 75mm thick tongue and groove autoclaved aerated concrete (AAC) panels with stated nominal dry density of 510kg/m3 (a surface density of 38.2kg/m2). which are lined with 13mm thick gypsum plasterboard. Two configurations that are presently common forms of construction in a region of Australia were tested; 1. Furring channel one side and stud wall the other that maintained an overall wall width of 243mm, and 2. Direct fix one side and stud wall the other. In both cases the gypsum plasterboard is mounted on 64mm steel studs. The gap between the panels and the steel studs is 20, 35 or 48mm. With the exception of one empty cavity, the cavity on this side contains 11kg/m3 glass fibre batts with thickness of 50, 75, 90 or 110mm. On the other side of the panels, the gypsum plasterboard is mounted on furring channels and adjustable clips which are screwed to the panels or in 6 cases directly screwed to the panels. Except for the directly screwed cases, the gap between the panels and the gypsum plasterboard is 30, 43 or 58mm. The cavity is empty or contains 50 or 70mm thick 11kg/m3 glass fibre batts or 25mm thick 24kg/m3 glass fibre batts. The 13mm gypsum plasterboard has nominal surface densities of 7.2, 8.5 or 10.5kg/m2. The aim was to develop a system which has a laboratory measured Rw+Ctr equal to or greater than 50dB which is required by the National Construction Code (NCC) of Australia for walls between separate dwellings. A system with cavities on both sides of the wall is desirable because it allows services to be accommodated without the need for chasing which is not permitted. The undesirable effect is a resultant large Ctr making it difficult to achieve an Rw +Ctr equal to or greater than 50dB.
ProtoHole: Prototyping Interactive 3D Printed Objects Using Holes and Acoustic Sensing

A prototype process of a physical user interface includes not only connection of electronic parts and an enclosure design, but also the arrangement and configuration of the electronic parts in the enclosure. This process is complicated and difficult for people who do not have modeling skills. We propose ProtoHole, a system for prototyping interactive 3D printed objects using holes, internal cavity and swept-frequency acoustic sensing. By emitting a high-frequency sweep signal inside the object, our system enables to classify changes in resonance properties when closing holes using a machine learning technique. Therefore, an object can be easily made interactive without considering an arrangement of internal electronic parts and wiring. We show examples of prototypes created with our system.
Grand Challenges in Shape-Changing Interface Research

Shape-changing interfaces have emerged as a new method for interacting with computers, using dynamic changes in a device's physical shape for input and output. With the advances of research into shape-changing interfaces, we see a need to synthesize the main, open research questions. The purpose of this synthesis is to formulate common challenges across the diverse fields engaged in shape-change research, to facilitate progression from single prototypes and individual design explorations to grander scientific goals, and to draw attention to challenges that come with maturity, including those concerning ethics, theory-building, and societal impact. In this article we therefore present 12 grand challenges for research on shape-changing interfaces, derived from a three-day workshop with 25 shape-changing interface experts with backgrounds in design, computer science, human-computer interaction, engineering, robotics, and material science.
Investigating the Effect of the Multiple Comparisons Problem in Visual Analysis

The goal of a visualization system is to facilitate dataset-driven insight discovery. But what if the insights are spurious? Features or patterns in visualizations can be perceived as relevant insights, even though they may arise from noise. We often compare visualizations to a mental image of what we are interested in: a particular trend, distribution or an unusual pattern. As more visualizations are examined and more comparisons are made, the probability of discovering spurious insights increases. This problem is well-known in Statistics as the multiple comparisons problem (MCP) but overlooked in visual analysis. We present a way to evaluate MCP in visualization tools by measuring the accuracy of user reported insights on synthetic datasets with known ground truth labels. In our experiment, over 60% of user insights were false. We show how a confirmatory analysis approach that accounts for all visual comparisons, insights and non-insights, can achieve similar results as one that requires a validation dataset.
On arabic search: improving the retrieval effectiveness via a light stemming approach

The inflectional structure of a word impacts the retrieval accuracy of information retrieval systems of Latin-based languages. We present two stemming algorithms for Arabic information retrieval systems. We empirically investigate the effectiveness of surface-based retrieval. This approach degrades retrieval precision since Arabic is a highly inflected language. Accordingly, we propose root-based retrieval. We notice a statistically significant improvement over the surface-based approach. Many variant word senses are based on an identical root; thus, the root-based algorithm creates invalid conflation classes that result in an ambiguous query which degrades the performance by adding extraneous terms. To resolve ambiguity, we propose a novel light-stemming algorithm for Arabic texts. This automatic rule-based stemming algorithm is not as aggressive as the root extraction algorithm. We show that the light stemming algorithm significantly outperforms the root-based algorithm. We also show that a significant improvement in retrieval precision can be achieved with light inflectional analysis of Arabic words.
PPARγ Antagonizes Hypoxia-Induced Activation of Hepatic Stellate Cell through Cross Mediating PI3K/AKT and cGMP/PKG Signaling

Background and Aims Accumulating evidence reveals that PPARγ plays a unique role in the regulation of hepatic fibrosis and hepatic stellate cells (HSCs) activation. This study was aimed at investigating the role of PPARγ in hypoxia-induced hepatic fibrogenesis and its possible mechanism. Methods Rats used for CCl4-induced hepatic fibrosis model were exposed to hypoxia for 8 hours each day. Rats exposed to hypoxia were treated with or without the PPARγ agonist rosiglitazone. Liver sections were stained with HE and Sirius red staining 8 weeks later. HSCs were exposed to hypoxic environment in the presence or absence of rosiglitazone, and expression of PPARγ and two fibrosis markers, α-SMA and desmin, were measured using western blot and immunofluorescence staining. Next, levels of PPARγ, α-SMA, and desmin as well as PKG and cGMP activity were detected using PI3K/AKT and a cGMP activator or inhibitor. Results Hypoxia promoted the induction and progress of hepatic fibrosis and HSCs activation. Meanwhile, rosiglitazone significantly antagonized the effects induced by hypoxia. Signaling by sGC/cGMP/PKG promoted the inhibitory effect of PPARγ on hypoxia-induced activation of HSCs. Moreover, PI3K/AKT signaling or PDE5 blocked the above response of PPARγ. Conclusion sGC/cGMP/PKG and PI3K/AKT signals act on PPARγ synergistically to attenuate hypoxia-induced HSC activation.
A Novel Hybrid Filter-Based PLL to Eliminate Effect of Input Harmonics and DC Offset

Synchronous reference frame phase locked loop (SRF-PLL) is widely used for grid synchronization and control in grid-connected applications. A major problem with SRF-PLL is how to improve its dynamic performance and filtering capability under complex grid conditions such as unbalance, distortion, and dc offset mixing without affecting its phase tracking performance and stability. In order to achieve this goal, a novel second-order generalized integrator (NSOGI) and a modified NSOGI (MNSOGI) with dc offset rejection capability based on NSOGI are proposed, and then, an effective hybrid filter is designed and incorporated into the inner loop of a SRF-PLL. The proposed hybrid filter is a combination of a dual MNSOGI and a moving average filter (MAF), it can block the fundamental frequency negative sequence component, dc offset component, and the rest of harmonic components in the SRF-PLL input three-phase voltages at the same time with a simple complexity. The proposed PLL in this paper has a faster transient response due to reducing the window length of the MAF. A small-signal model of the proposed PLL is derived. The stability is analyzed, and parameters design guidelines are given. The effectiveness of the proposed PLL is confirmed through simulation experimental results.
Fault tolerance techniques for scientific applications in cloud

Cloud computing can describe on-demand administration and prerequisite of resources, and information as services on the cloud. The dynamic environment of the cloud causes various unexpected obstacles. The ability of a system to respond normally to unexpected equipment and programming fault is called fault tolerance. In order to realize robustness and reliability in cloud computing, it is necessary to evaluate and process obstacles effectively. Various fault detection methods and architecture models have been proposed to increase the fault tolerance capability of the cloud. Consider the fact, this paper has been paying attention on solving the problem of faults in the cloud computing. This research has conducted to outline the work that has been done in this field which represents the basic concept of fault tolerance developed by different researchers and various algorithms used to resolve the fault tolerance problem in cloud computing.
Maturation of the 90S pre-ribosome requires Mrd1 dependent U3 snoRNA and 35S pre-rRNA structural rearrangements

Abstract In eukaryotes, ribosome biogenesis requires folding and assembly of the precursor rRNA (pre-rRNA) with a large number of proteins and snoRNPs into huge RNA-protein complexes. In spite of intense genetic, biochemical and high-resolution cryo-EM studies in Saccharomyces cerevisiae, information about the structure of the 35S pre-rRNA is limited. To overcome this, we performed high-throughput SHAPE chemical probing on the 35S pre-rRNA within 90S pre-ribosomes. We focused our analyses on external (5′ETS) and internal (ITS1) transcribed spacers as well as the 18S rRNA region. We show that in the 35S pre-rRNA, the central pseudoknot is not formed and the central core of the 18S rRNA is in an open configuration but becomes more constrained in 20S pre-rRNA. The essential ribosome biogenesis protein Mrd1 influences the structure of the 18S rRNA region locally and is involved in organizing the central pseudoknot and surrounding structures. We demonstrate that U3 snoRNA dynamically interacts with the 35S pre-rRNA and that Mrd1 is required for disrupting U3 snoRNA base pairing interactions in the 5′ETS. We propose that the dynamic U3 snoRNA interactions and Mrd1 are essential for establishing the structure of the central core of 18S rRNA that is required for processing and 40S subunit function.
Colonisation of the Non-Indigenous Pacific Oyster Crassostrea gigas Determined by Predation, Size and Initial Settlement Densities

Survival of incipient non-indigenous populations is dramatically altered by early predation on new colonisers. These effects can be influenced by morphological traits, such as coloniser size and density. The Australian non-native Pacific Oyster Crassostrea gigas is generally more fecund and faster growing compared to the native Saccostrea glomerata found in the same habitat. It is therefore important to quantify how the two species differ in survival across coloniser density and predation gradients. This information could become pertinent to the management of wild and aquaculture populations of the non-native C. gigas. Using a field-based factorial experiment we model the survival of incipient populations of both the native S. glomerata and the non-indigenous C. gigas as a function of coloniser density, predator reduction and individual size. Unexpectedly, survival of the non-indigenous C. gigas increased compared to S. glomerata when individuals were larger. The proportional survival of newly colonised oyster populations also increased with larger initial populations, regardless of species identity. Further, predator reduction resulted in increased survival of both oyster species, irrespective of coloniser size or initial density. Here we quantitatively demonstrate the effects of recruit density and size on enhancing the survivability of incipient oyster populations.
Anomalous collapse of interacting bubbles in a fluidized bed: A magnetic resonance imaging study

The collapse, or reduction in size to zero volume, of bubbles injected into incipiently ﬂuidized beds was studied using rapid magnetic resonance imaging. The collapse of a smaller lower bubble trailing a larger upper bubble and the collapse of one bubble when two bubbles rose side by side were found to occur. Under the same conditions with the use of ﬁner particles or the injection of an isolated bubble, no collapse occurred. Thus, results indicate that gas leakage into the particulate phase of coarse particles and bubble interaction promote bubble collapse. Furthermore, injection of larger bubbles also resulted in bubbles rising to the bed surface instead of collapsing, indicating that bubbles must be below a critical size in order to collapse. For side-by-side bubbles, bubble collapse is attributed to gas ﬂow channeling to the larger bubble; for consecutive bubbles, bubble collapse is attributed to increased gas leakage in a dilated bubble wake.
Cyclic Fatigue Resistance of Mtwo Rotary Instruments with two Different Instrumentation Techniques

Introduction: The objective of this in vitro study was to evaluate whether cervical preparation with Mtwo files in a crown-down technique influences instrumentation time and the cyclic fatigue resistance of these instruments. Methods and Materials: Two instrumentation techniques were evaluated (manufacturer and crown-down). Each group consisted of 10 kits containing four Mtwo instruments (10/0.04, 15/0.05, 20/0.06, and 25/0.06), which were used to prepare three standard simulated curved resin canals. The mean instrumentation time and the corresponding number of cycles for each instrumentation (NCI) were recorded. The instruments were rotated at a constant speed of 300 rpm in a stainless-steel canal (diameter of 1.5 mm) at a 90° angle of curvature and 5-mm radius. The center of the curvature was 5 mm from the tip of the instrument. The cyclic fatigue resistance of the files was determined by counting the number of cycles to failure (NCF). Data were analyzed by the Mann-Whitney test. Results: The mean instrumentation time and NCI of files 10/0.04 and 15/0.05 were significantly lower (P<0.05) when the crown-down technique was used compared to the manufacturer’s method for the same tip size/taper file. There was no significant difference in the mean NCF between the two techniques. Conclusion: The crown-down technique did not interfere with resistance to cyclic fatigue. However, the shorter instrumentation time of files 10/0.04 and 15/0.05 could reduce the fracture risk in the case of reuse of these instruments.
IIT at TREC-2003 ( DRAFT ) Task Classification & Document Structure for Known-Item Search

This year’s TREC 2003 web task incorporated two retrieval tasks into a single set of experiments for Known-Item retrieval. We hypothesized that not all retrieval tasks should use the same retrieval approach when a single search entry point is used. We applied task classifiers on top of traditional web retrieval approaches. Our traditional retrieval is based on fusion of result sets generated by query runs over independent parts of the document structure. Our task classifiers combine query term analysis with known information resources and URL depth. This approach to task classification shows promise: our classified runs improved overall MRR effectiveness over our traditional retrieval results by ~10%; provided an MRR of . 665; ranked 87% of relevant results in the top 10; correctly ranked the #1result 56% of the time. 67% of the queries performed above the average, and 49% above the median.
Heterogeneous PCM array architecture for reliability, performance and lifetime enhancement

Conventional DRAM and flash memory are reaching their scaling limits thus motivating research in various emerging memory technologies as a potential replacement. Among these, phase change memory (PCM) has received considerable attention owing to its high scalability and multi-level cell (MLC) operation for high storage density. However, due to the resistance drift over time, the soft error rate in MLC PCM is high. Additionally, the iterative programming in MLC negatively impacts performance and cell endurance. The conventional methods to overcome the drift problem incur large overheads, impact memory lifetime and are inadequate in terms of acceptable soft error rate (SER). In this paper, we propose a new PCM memory architecture with heterogeneous PCM arrays to increase reliability, performance and lifetime. The basic storage unit in the proposed architecture consists of two single-level cells (SLCs) and one four-level cell (4LC). Using the reduced number of 4LCs compared to conventional homogeneous 4LC PCM arrays, the drift-induced error rate is considerably reduced. By alternating each cell operation between SLC and 4LC over time, the overall lifetime can also be significantly enhanced. The proposed architecture achieves up to 105 times lower soft error rate with considerably less ECC overhead. With simple ECC scheme, about 22% performance improvement is achieved and additionally, the overall lifetime is also enhanced by about 57%.