Miracle-dz/UniFAR-FTUs huggingface dataset:
Importin α/β mediates nuclear import of individual SUMO E1 subunits and of the holo-enzyme

SUMOylation is an essential modification that regulates predominantly nuclear proteins. Here we describe two pathways for the generation of nuclear SUMO E1 enzyme, import of individual subunits, and transport of the holo-enzyme. The NLS in Uba2 is required for transport of the complex; the c-Myc–like NLS in Aos1 functions only in the free subunit.
A status protocol for system-operation in a fault-tolerant system — Verification and testing with SPIN

This paper presents a status protocol for a fault-tolerant distributed real-time system. The protocol aims to give all nodes a consistent view of the status of processing operations during one communication cycle; despite the occurrence of asymmetric omission failures. The system consists of nodes interconnected with a time-triggered network. A part of the protocol is performed only on-demand i.e. when failure is detected and can thus make use of event-triggered messages in e.g. FlexRay. The protocol is studied in several configurations of nodes and processes. Model checking with SPIN shows that it is not possible to guarantee a consistent decision when more than one failure occurs. SPIN is then used to enumerate the success-ratio (at least 90%) of the protocol in failure scenarios for a number of configurations of the protocol.
Learning Geodesic Metric for Out-of-Sample Extension of Isometric Embedding

Geodesic distance calculation is a crucial stage in the distance-based manifold learning algorithms. Owning to the nonparametric of Isomap, however, it is not economic and convenient to compute the geodesic distances for an unseen new sample via neighborhood graph. In this paper, we proposed a geodesic metric learning (GML) scheme based on iterative majorization, to obtain a parametric geodesic metric function. Once the parametric geodesic metric is produced, one can calculate the geodesic distance directly and have no longer use for reconstructing the neighborhood graph for those unseen samples. Integrating distance-based triangulation with the parametric geodesic metric, it is easy to accomplish the task of feature extraction based on geodesic distance. Experiments on benchmark database have demonstrated the encouraged results
The Effect of Strategic Planning Training on Cohesion in EFL Learners’ Essays

Abstract This study aims to examine the effect of strategic planning training on cohesion in English as a foreign language (EFL) learners’ writing. We recruited 62 Chinese learners of English and divided them evenly into experimental and control groups. We trained the experimental group in 4 sessions to master strategic planning. Then we selected 4 participants from the experimental group to undergo semistructured interviews to track change in their attentional focus throughout the training. We measured cohesion in essays before and after training using Coh-Metrix and analyzed it using the least significant difference in analysis of variance. The findings showed that strategic planning training had a limited effect on cohesion in EFL writing, which could be explained by EFL learners’ improved awareness of cohesion and limited English proficiency. This study suggests that (a) EFL learners should improve their linguistic proficiency to channel their attentional focus on cohesion and (b) writing instruction should help these learners to balance their focus.
Enzymatic Depilation of Animal Hide: Identification of Elastase (LasB) from Pseudomonas aeruginosa MCM B-327 as a Depilating Protease

Conventional leather processing involving depilation of animal hide by lime and sulphide treatment generates considerable amounts of chemical waste causing severe environmental pollution. Enzymatic depilation is an environmentally friendly process and has been considered to be a viable alternative to the chemical depilation process. We isolated an extracellular protease from Pseudomonas aeruginosa strain MCM B-327 with high depilation activity using buffalo hide as a substrate. This 33 kDa protease generated a peptide mass fingerprint and de novo sequence that matched perfectly with LasB (elastase), of Pseudomonas aeruginosa. In support of this data a lasB mutant of MCM B-327 strain lacked depilatory activity and failed to produce LasB. LasB heterologously over-produced and purified from Escherichia coli also exhibited high depilating activity. Moreover, reintroduction of the lasB gene to the P. aeruginosa lasB mutant via a knock-in strategy also successfully restored depilation activity thus confirming the role of LasB as the depilating enzyme.
HQSAR: A New, Highly Predictive QSAR Technique

QSAR techniques have proven to be extremely valuable in pharmaceutical research, particularly 3D QSAR. However, the necessity of descriptor calculation and selection or conformer generation, and structural alignment makes use of QSAR non-trivial. Demands for analysis of large data sets such as those being generated by combinatorial chemistry and high throughput screening have compounded this problem. Hologram QSAR (HQSAR) is a new technique which employs specialised fragment fingerprints (molecular holograms) as predictive variables of biological activity or other structural related data. By removing the necessity for molecular alignment, models by HQSAR can be obtained more rapidly than other by techniques, which makes HQSAR readily applicable to both small and large data sets. HQSAR models are comparable in predictive ability to those derived from CoMFA studies and allow extension to database searching capability.
Unsupervised object exploration using context

In order for robots to function in unstructured environments in interaction with humans, they must be able to reason about the world in a semantic meaningful way. An essential capability is to segment the world into semantic plausible object hypotheses. In this paper we propose a general framework which can be used for reasoning about objects and their functionality in manipulation activities. Our system employs a hierarchical segmentation framework that extracts object hypotheses from RGB-D video. Motivated by cognitive studies on humans, our work leverages on contextual information, e.g., that objects obey the laws of physics, to formulate object hypotheses from regions in a mathematically principled manner.
Automated use case similarity computation can aid the assessment cohesion and method complexity of classes

Use cases are widely used in early software development phases such requirements analysis. In this paper, we investigate how use case similarity could impact the classes that implement them. We studied if the similarity of use cases could have impact on the lines of code shared between them and on metrics of classes that implement them, such as, coupling, cohesion and method complexity of classes. We also have successfully applied an automated approach to assess the similarity of use case names. We found that there is a statistically significant correlation, altough not strong, between use case similarity and sharing of lines of code. Interestingly, we also have found that classes that are shared between different use cases tend to have lower cohesion. Moreover, classes that are shared between similar use cases tend to have higher method complexity in classes. We found no relation between use case similarity and coupling. Keywords—Use Case Similarity, Software Metrics, Software Maintenance
Pfair scheduling of fixed and migrating periodic tasks on multiple resources

This paper concerns the problem of scheduling sets of preemptable, periodic tasks on multiple resources. We consider a task model that allows arbitrary mixes of fixed and migratable tasks, and prove the existence of an optimal pfair scheduler in this model. Fixed tasks must always be scheduled on a given resource, while migratable tasks can be scheduled on different resources at different times. A pfair scheduler produces a periodic schedule in which the times each task is allocated a processor are approximately evenly spread throughout its period. This paper extends work of Baruah et al., who proved a similar result for systems in which all tasks are migratable.
Advances in Arabic broadcast news transcription at RWTH

This paper describes the RWTH speech recognition system for Arabic. Several design aspects of the system, including cross-adaptation, multiple system design and combination, are analyzed. We summarize the semi-automatic lexicon generation for Arabic using a statistical approach to grapheme-to-phoneme conversion and pronunciation statistics. Furthermore, a novel ASR-based audio segmentation algorithm is presented. Finally, we discuss practical approaches for parallelized acoustic training and memory efficient lattice rescoring. Systematic results are reported on recent GALE evaluation corpora.
Enhancing the anti-islanding capability and power quality of microgrid through a series compensator

This paper presents an improved power quality control strategy based on inverter. In grid-connected mode, the series inverter between the microgrid and utility gird (UG) can compensate the power quality of the micro grid under the condition of the voltage fluctuation, imbalance, and harmonic distortion, and prevent the harmonic currents from microgrid flowing into the UG. Especially, when there is an instantaneous short circuit fault of the UG, the topology can also function well, enhancing the anti-islanding and fault tolerance capability, avoiding the transient process in the mode transfer and improving energy efficiency. In islanding mode, the series inverter is converted to the shunt inverter by switching ground, which can work as the shunt active power filter. The unified device is applied to two operating modes, saving the cost of operation. The effectiveness and reliability of the control strategy is certified through the Simulink.
Corpus Callosum Microstructural Changes Correlate with Cognitive Dysfunction in Early Stages of Relapsing-Remitting Multiple Sclerosis: Axial and Radial Diffusivities Approach

The corpus callosum is the largest fiber bundle in the central nervous system and it takes part in several cognitive pathways. It can be affected by multiple sclerosis (MS) early in the disease. DTI is capable of infering the microstructural organization of the white matter. The vectorial analysis of the DTI offers the more specific indices of axial diffusivity (AD) and radial diffusivity (RD), which have shown to be useful to discriminate myelin damage from axon loss, respectively. This study presents DTI results (mean diffusivity (MD), fractional anisotropy (FA), RD, and AD) of 23 relapsing-remitting MS patients and its correlation with cognitive performance. There were 47.8% of cognitive impaired patients (MS CI). We found signs of demyelination, reflected by increased RD, and incipient axon loss, reflected by AD increase, which was slightly higher in the MS CI. The cognitive changes correlated with the DTI parameters, suggesting that loss of complexity in CC connections can impair neural conduction. Thus, cognitive impairment can be related to callosal disconnection, and DTI can be a promising tool to evaluate those changes.
This review identified high-quality studies on teaching conditional use of requesting and rejecting skills, but points to the need for more research and for analyses of study outcomes1

Data sources: The author used a search string to conduct two electronic searches of four databases (Academic Search Premier, PsycINFO, ERIC, Education Full Text). Following the electronic searches, hand searches were conducted of the journals that produced at least two articles included from the electronic search. The author also conducted an ancestral search of the reference lists of included articles.
A Novel Distributed Clustering-based MDS Algorithm for Nodes Localization in WSNs

Localization of sensors nodes is a key and fundamental issue in wireless sensor networks due to random deployment. In this paper, we propose a tree based clustering (TBC) multidimensional scaling algorithm for wireless sensor networks with the purpose of overcoming the shortage of classical MDS algorithms in its localization accuracy and computing complexity. Clustering is adopted to degrade the problem scale in our approach and a moderate number of common nodes between clusters are kept during clustering. Inner cluster local coordinates are calculated and then mapped into global coordinates according to the tree structure formed by clustering. Simulations on MATLAB are conducted and the results show that the proposed algorithm has better localization coverage and higher accuracy than the traditional MDS based algorithms.
Continuing the Contradictions: A Multimodal Investigation into the Front Covers of Real-Life Magazines

Abstract:Studies analyzing women's magazines note contradiction as a common theme, between the content of the magazines and either the ideological values presented therein or those at broader, political levels. This paper empirically investigates to what extent contradiction may occur on the covers of real-life magazines (a subgenre of women's magazines; N = 100). Employing a multimodal analysis of the textual, visual, and compositional modes, contradiction is posited to occur at various levels. Overall, while these covers present a seemingly upbeat character at a glance, themes of a distressing nature—including but not limited to abuse and violence—are present throughout. The interactions between associated texts and imagery, and the relative salience of these elements, are suggested as key factors in these contradictory compositions. Furthermore, these factors are posited as explanations for why real-life magazines are often in full view in magazine racks around the UK yet are omitted from the scrutiny that other (sub)genres of magazines undergo.
A Statistical Generative Model for Unsupervised Learning of Verb Argument Structures

We present a statistical generative model for unsupervised learning of verb argument structures. We use the model in order to automatically induce verb argument structures for a representative set of verbs. Approximately 80% of the induced argument structures are judged correct by human subjects. The structures overlap significantly with those in PropBank; they also exhibit correct patterns of usage that are not present in this manually developed semantic resource.
Polymorphic Pipeline Array: A flexible multicore accelerator with virtualized execution for mobile multimedia applications

Mobile computing in the form of smart phones, netbooks, and personal digital assistants has become an integral part of our everyday lives. Moving ahead to the next generation of mobile devices, we believe that multimedia will become a more critical and product-differentiating feature. High definition audio and video as well as 3D graphics provide richer interfaces and compelling capabilities. However, these algorithms also bring different computational challenges than wireless signal processing. Multimedia algorithms are more complex featuring more control flow and variable computational requirements where execution time is not dominated by innermost vector loops. Further, data access is more complex where media applications typically operate on multi-dimensional vectors of data rather than single-dimensional vectors with simple strides. Thus, the design of current mobile platforms requires reexamination to account for these new application domains. In this work, we focus on the design of a programmable, low-power accelerator for multimedia algorithms referred to as a Polymorphic Pipeline Array, or PPA. The PPA is designed with flexibility and programmability as first-order requirements to enable the hardware to be dynamically customizable to the application. PPAs exploit pipeline parallelism found in streaming applications to create a coarse-grain hardware pipeline to execute streaming media applications. PPA resources are allocated to each stage depending on its size and ability to exploit fine-grain parallelism. Experimental results show that real-time media applications can take advantage of the static and dynamic configurability for increased power efficiency.
MULTIPLE SENSOR APPLICATIONS USING SECURE DATA AGGREGATION

A wireless sensor network, data aggregation scheme that reduces a large amount of transmission is the most practical technique. In earlier studies, Homomorphic encryptions have been applied to conceal communication during aggregation such that enciphered data can be aggregated algebraically without decryption. Since aggregators collect data without decryption, adversaries are not able to forge aggregated results by compromising them. However, these schemes are not satisfy multi-application environments. Second, these schemes become insecure in case some sensor nodes are compromised. Third, these schemes do not provide secure counting; thus, they may suffer unauthorized aggregation attacks. Therefore, I use a new concealed data aggregation scheme extended from Boneh et al.’s Homomorphic public encryption system. The proposed scheme has three contributions. First, it is designed for a multi-application environment. The base station extracts application-specific data from aggregated cipher texts. Next, it mitigates the impact of compromising attacks in single application environments. Finally, it degrades the damage from unauthorized aggregations. To prove the proposed scheme’s robustness and efficiency, I also include the timer which is used to give alert message to base station prevent from attackers.
The Weibull-geometric distribution

For the first time, we propose the Weibull-geometric (WG) distribution which generalizes the extended exponential-geometric (EG) distribution introduced by Adamidis et al. [K. Adamidis, T. Dimitrakopoulou, and S. Loukas, On a generalization of the exponential-geometric distribution, Statist. Probab. Lett. 73 (2005), pp. 259–269], the exponential-geometric distribution discussed by Adamidis and Loukas [K. Adamidis and S. Loukas, A lifetime distribution with decreasing failure rate, Statist. Probab. Lett. 39 (1998), pp. 35–42] and the Weibull distribution. We derive many of its standard properties. The hazard function of the EG distribution is monotone decreasing, but the hazard function of the WG distribution can take more general forms. Unlike the Weibull distribution, the new distribution is useful for modelling unimodal failure rates. We derive the cumulative distribution and hazard functions, moments, density of order statistics and their moments. We provide expressions for the Rényi and Shannon entropies. The maximum likelihood estimation procedure is discussed and an EM algorithm [A.P. Dempster, N.M. Laird, and D.B. Rubim, Maximum likelihood from incomplete data via the EM algorithm (with discussion), J. R. Stat. Soc. B 39 (1977), pp. 1–38; G.J. McLachlan and T. Krishnan, The EM Algorithm and Extension, Wiley, New York, 1997] is given for estimating the parameters. We obtain the observed information matrix and discuss inference issues. The flexibility and potentiality of the new distribution is illustrated by means of a real data set.
Thermodynamic parameters for DNA sequences with dangling ends.

The thermodynamic contributions to duplex formation of all 32 possible single-nucleotide dangling ends on a Watson-Crick pair are reported. In most instances, dangling ends are stabilizing with free energy contributions ranging from +0.48 (GT(A)) to-0.96 kcal/mol (). In comparison, Watson-Crick nearest-neighbor increments range from -0. 58 (TA/AT) to -2.24 (GC/CG) kcal/mol. Hence, in some cases, a dangling end contributes as much to duplex stability as a Watson-Crick A-T base pair. The implications of these results for DNA probe design are discussed. Analysis of the sequence dependence of dangling-end stabilities show that the nature of the closing base pair largely determines the stabilization. For a given closing base pair, however, adenine dangling ends are always more or equally as stable as the other dangling nucleotides. Moreover, 5' dangling ends are more or equally as stabilizing as their 3' counterparts. Comparison of DNA with RNA dangling-end motifs shows that DNA motifs with 5' dangling ends contribute to stability equally or more than their RNA counterparts. Conversely, RNA 3' dangling ends contribute to stability equally or more than their DNA counterparts. This data set has been incorporated into a DNA secondary structure prediction algorithm (DNA MFOLD) (http://mfold2.wustl.edu/mfold/dna/for m1.cgi) as well as a DNA hybridization prediction algorithm (HYTHERtrade mark) (http://jsl1.chem.wayne.edu/Hyther/hythermenu .html).
Differing Prevalence and Diversity of Bacterial Species in Fetal Membranes from Very Preterm and Term Labor

Background Intrauterine infection may play a role in preterm delivery due to spontaneous preterm labor (PTL) and preterm prolonged rupture of membranes (PPROM). Because bacteria previously associated with preterm delivery are often difficult to culture, a molecular biology approach was used to identify bacterial DNA in placenta and fetal membranes. Methodology/Principal findings We used broad-range 16S rDNA PCR and species-specific, real-time assays to amplify bacterial DNA from fetal membranes and placenta. 74 women were recruited to the following groups: PPROM <32 weeks (n = 26; 11 caesarean); PTL with intact membranes <32 weeks (n = 19; all vaginal birth); indicated preterm delivery <32 weeks (n = 8; all caesarean); term (n = 21; 11 caesarean). 50% (5/10) of term vaginal deliveries were positive for bacterial DNA. However, little spread was observed through tissues and species diversity was restricted. Minimal bacteria were detected in term elective section or indicated preterm deliveries. Bacterial prevalence was significantly increased in samples from PTL with intact membranes [89% (17/19) versus 50% (5/10) in term vaginal delivery p = 0.03] and PPROM (CS) [55% (6/11) versus 0% (0/11) in term elective CS, p = 0.01]. In addition, bacterial spread and diversity was greater in the preterm groups with 68% (13/19) PTL group having 3 or more positive samples and over 60% (12/19) showing two or more bacterial species (versus 20% (2/10) in term vaginal deliveries). Blood monocytes from women with PTL with intact membranes and PPROM who were 16S bacterial positive showed greater level of immune paresis (p = 0.03). A positive PCR result was associated with histological chorioamnionitis in preterm deliveries. Conclusion/Significance Bacteria are found in both preterm and term fetal membranes. A greater spread and diversity of bacterial species were found in tissues of women who had very preterm births. It is unclear to what extent the greater bacterial prevalence observed in all vaginal delivery groups reflects bacterial contamination or colonization of membranes during labor. Bacteria positive preterm tissues are associated with histological chorioamnionitis and a pronounced maternal immune paresis.