Miracle-dz/UniFAR-FTUs huggingface dataset:
Defects in Mitochondrial and Peroxisomal β-Oxidation Influence Virulence in the Maize Pathogen Ustilago maydis

ABSTRACT An understanding of metabolic adaptation during the colonization of plants by phytopathogenic fungi is critical for developing strategies to protect crops. Lipids are abundant in plant tissues, and fungal phytopathogens in the phylum basidiomycota possess both peroxisomal and mitochondrial β-oxidation pathways to utilize this potential carbon source. Previously, we demonstrated a role for the peroxisomal β-oxidation enzyme Mfe2 in the filamentous growth, virulence, and sporulation of the maize pathogen Ustilago maydis. However, mfe2 mutants still caused disease symptoms, thus prompting a more detailed investigation of β-oxidation. We now demonstrate that a defect in the had1 gene encoding hydroxyacyl coenzyme A dehydrogenase for mitochondrial β-oxidation also influences virulence, although its paralog, had2, makes only a minor contribution. Additionally, we identified a gene encoding a polypeptide with similarity to the C terminus of Mfe2 and designated it Mfe2b; this gene makes a contribution to virulence only in the background of an mfe2Δ mutant. We also show that short-chain fatty acids induce cell death in U. maydis and that a block in β-oxidation leads to toxicity, likely because of the accumulation of toxic intermediates. Overall, this study reveals that β-oxidation has a complex influence on the formation of disease symptoms by U. maydis that includes potential metabolic contributions to proliferation in planta and an effect on virulence-related morphogenesis.
Multi-Hop Broadcasting in VANETs Integrating Intra-Flow and Inter-Flow Network Coding

Multi-hop data dissemination in vehicular ad hoc networks (VANETs) is very important for the realization of collision avoidance systems and other many interesting applications. However, designing an efficient data dissemination protocol in VANETs has been a challenging issue due to vehicle movements, limited wireless resources and lossy characteristics of wireless communication. In this paper, we propose a protocol which employs intra-flow and inter-flow network coding to reduce the protocol overhead as compared to traditional protocols. The protocol also can improve the packet reception probability at the receiver nodes by using the network coding. Therefore, the protocol can provide a lightweight and reliable solution for data dissemination in VANETs. We use theoretical analysis and computer simulations to show the advantage of the proposed protocol over other existing alternatives.
Dyadic-based factorizations for regular paraunitary filter banks [image coding examples]

M-channel paraunitary filter banks (PUFBs) can be designed and implemented using either degree-one or order-one dyadic-based factorization. This paper summarizes how regularity of a desired degree is structurally imposed on such factorizations for any number of channels M/spl ges/2 and any phase responses. The regularity conditions are found to be conveniently expressed in terms of recently reported M-channel lifting structures, which allow fast and reversible implementations. Design examples are presented and they outperform previously reported ones in transform-based image coding.
“It is about taking grips and not let myself be ravaged by my body”: A qualitative study of outcomes from in-patient multidisciplinary rehabilitation for patients with chronic rheumatic diseases

Purpose: To explore how patients experience the process and personal impact of deriving outcomes from a rheumatological rehabilitation program. Methods: Semi-structured interviews were conducted with 23 patients with inflammatory rheumatic diseases approximately 2 months after a 4-week hospital based multidisciplinary rehabilitation program. A thematic analysis was applied. Results: Overarching themes were increased dignity and self-respect. Initial uncertainty regarding illness management was exchanged with confident coping and of becoming an active agent in ones own life. Strategies and coping tools tried out during the rehabilitation stay, do by their experienced effect become primary sources of gained insight into illness and symptom manifestation. Both elements give a sense of control and influence self-confidence and motivation to engage in self-management. The process from gained insight and experienced effect of coping tools, to active self management, is however, not automatic. Psychological factors play a key role, and there is a need to take individual psychological themes into account and tailor interventions accordingly. Conclusions: Specialized multidisciplinary rehabilitation is an ongoing active process, in which psychological factors play a key role and must be accounted for. Well targeted rehabilitation has the potential to create outcomes of major personal impact. Implications for Rehabilitation Well targeted multidisciplinary rehabilitation has the potential to create outcomes of major personal impact Rehabilitation interventions should be tailored according to the patient’s subjective perception of challenges. A secure and supportive environment where patients are met with respect and interest represents a crucial element in rehabilitation.
Cognitive Strategies Dependent on the Hippocampus and Caudate Nucleus in Human Navigation: Variability and Change with Practice

The human brain activity related to strategies for navigating in space and how it changes with practice was investigated with functional magnetic resonance imaging. Subjects used two different strategies to solve a place-learning task in a computer-generated virtual environment. One-half of the subjects used spatial landmarks to navigate in the early phase of training, and these subjects showed increased activation of the right hippocampus. The other half used a nonspatial strategy and showed, with practice, sustained increased activity within the caudate nucleus during navigation. Activation common to both groups was observed in the posterior parietal and frontal cortex. These results provide the first evidence for spontaneous variability and shift in neural mechanisms during navigation in humans.
Force model for CAD selection

In this paper we investigate attraction techniques, using the haptic modality, for CAD applications. An important issue in CAD systems is the modification of the Boundary Representation (B-Rep) of 3D objects. However, this fundamental task is possible only if a geometric element (vertex, edge, face) has already been selected. This paper focuses on a generic force feedback model of haptic attraction for CAD applications. Our model is flexible and allows the experimentation of several behaviours. Several evaluation studies are carried out to compare the impact of the model parameters on the user performance and comfort of use.
Multilevel algorithms for linear ordering problems

Linear ordering problems are combinatorial optimization problems that deal with the minimization of different functionals by finding a suitable permutation of the graph vertices. These problems are widely used and studied in many practical and theoretical applications. In this paper, we present a variety of linear--time algorithms for these problems inspired by the Algebraic Multigrid approach, which is based on weighted-edge contraction. The experimental result for four such problems turned out to be better than every known result in almost all cases, while the short (linear) running time of the algorithms enables testing very large graphs.
Genomes, diversity and resistance gene analogues in Musa species

Resistance genes (R genes) in plants are abundant and may represent more than 1% of all the genes. Their diversity is critical to the recognition and response to attack from diverse pathogens. Like many other crops, banana and plantain face attacks from potentially devastating fungal and bacterial diseases, increased by a combination of worldwide spread of pathogens, exploitation of a small number of varieties, new pathogen mutations, and the lack of effective, benign and cheap chemical control. The challenge for plant breeders is to identify and exploit genetic resistances to diseases, which is particularly difficult in banana and plantain where the valuable cultivars are sterile, parthenocarpic and mostly triploid so conventional genetic analysis and breeding is impossible. In this paper, we review the nature of R genes and the key motifs, particularly in the Nucleotide Binding Sites (NBS), Leucine Rich Repeat (LRR) gene class. We present data about identity, nature and evolutionary diversity of the NBS domains of Musa R genes in diploid wild species with the Musa acuminata (A), M. balbisiana (B), M. schizocarpa (S), M. textilis (T), M. velutina and M. ornata genomes, and from various cultivated hybrid and triploid accessions, using PCR primers to isolate the domains from genomic DNA. Of 135 new sequences, 75% of the sequenced clones had uninterrupted open reading frames (ORFs), and phylogenetic UPGMA tree construction showed four clusters, one from Musa ornata, one largely from the B and T genomes, one from A and M. velutina, and the largest with A, B, T and S genomes. Only genes of the coiled-coil (non-TIR) class were found, typical of the grasses and presumably monocotyledons. The analysis of R genes in cultivated banana and plantain, and their wild relatives, has implications for identification and selection of resistance genes within the genus which may be useful for plant selection and breeding and also for defining relationships and genome evolution patterns within the genus using the multi-copy and variable resistance genes.
Privacy-preserving, indoor occupant localization using a network of single-pixel sensors

We propose an approach to indoor occupant localization using a network of single-pixel, visible-light sensors. In addition to preserving privacy, our approach vastly reduces data transmission rate and is agnostic to eavesdropping. We develop two purely data-driven localization algorithms and study their performance using a network of 6 such sensors. In one algorithm, we divide the monitored floor area (2.37m×2.72m) into a 3×3 grid of cells and classify location of a single person as belonging to one of the 9 cells using a support vector machine classifier. In the second algorithm, we estimate person's coordinates using support vector regression. In cross-validation tests in public (e.g., conference room) and private (e.g., home) scenarios, we obtain 67-72% correct classification rate for cells and 0.31-0.35m mean absolute distance error within the monitored space. Given the simplicity of sensors and processing, these are encouraging results and can lead to useful applications today.
Combining Multiple, Large-Scale Resources in a Reusable Lexicon for Natural Language Generation

A lexicon is an essential component in a generation system but few efforts have been made to buiht a rich, large-scale lexicon and make it reusable for different generation applications. In this paper, we describe our work to build 'inch a lexicon by combining multiple, heterogeneous linguistic resources which have been developed for other purposes. Novel transformation and integration of resources is required to reuse them for generation. We also applied the lexicon to the lexical choice and realization component of a practical generation application by using a multi-level feedback architecture. The integration of the lexicon and the architecture is able to effectively improve the system paraphrasing power, minimize the chance of grammatical errors, and simplify the development process substantially.
Graph-based retrieval model for semi-structured data

The continuous need to process semi-structured data in the more connected and semantic web requires a retrieval model that can truly reflect the user's intention and capture a user's understanding. As a semantic network shows great potential in representing the inherent structure of information in a document, recent studies have attempted to apply semantic networks into information retrieval. While many of the recent works on semi-structured data retrieval focused on the use of field structure within the data. Solely relying on the field structure is insufficient to portray the user's understanding, which is represented through the use of specific query terms. In this study, we seek to overcome this limitation by utilizing a semantic network to model semi-structured data and apply a graph-based semi-structured data retrieval model. Using both a popular testing environment and a real-life query data, we compare the performance of the suggested model with various competitive state-of-the-art retrieval models. The study's findings demonstrate the strength of the proposed model while providing intriguing opportunities for further application of the model.
Dream Recall and Total Sleep Time

It was predicted that diary and questionnaire measures of dream recall would be greater for long than for short sleep time. Total sleep time was a significant predictor variable for dream recall for males only. Results for females were in the predicted direction but consistently nonsignificant. This study confirms previously published findings on the significance of total sleep time for males but raises the question of sex differences in determinants of dream recall.
A Generalized Kernel Approach to Dissimilarity-based Classification

Usually, objects to be classified are represented by features. In this paper, we discuss an alternative object representation based on dissimilarity values. If such distances separate the classes well, the nearest neighbor method offers a good solution. However, dissimilarities used in practice are usually far from ideal and the performance of the nearest neighbor rule suffers from its sensitivity to noisy examples. We show that other, more global classification techniques are preferable to the nearest neighbor rule, in such cases.For classification purposes, two different ways of using generalized dissimilarity kernels are considered. In the first one, distances are isometrically embedded in a pseudo-Euclidean space and the classification task is performed there. In the second approach, classifiers are built directly on distance kernels. Both approaches are described theoretically and then compared using experiments with different dissimilarity measures and datasets including degraded data simulating the problem of missing values.
Switter: Supporting Exploration of Software Learning Materials on Social Media

There is always something new to learn about feature-rich software, even for experienced users. This paper focuses on a specific type of learning activity that we refer to as ad libitum exploration. Based on an interview study with 11 experienced software users, we define ad libitum exploration as the process of routinely seeking new software knowledge, without necessarily having a specific problem to solve. To support this activity, we designed Switter, an alternative Twitter client embedded in a replica of Photoshop's user interface. Given a tweet referencing a tutorial, Switter highlights the interface elements mentioned in the tutorial in the interface replica. Switter also allows users to filter tweets by clicking tools in the interface replica. Through a weeklong field study with nine Photoshop experts, we found that Switter supports a range of software learning objectives, from focused exploration targeting known weaknesses, to the discovery of novel command combinations.
Microgravity experiments on columnar–equiaxed transition in Al based alloys

Abstract The investigation on solidification of metallic alloys under well defined experimental conditions is of fundamental interest for the understanding of the physics involved in microstructure formation. In technical casting processes, these microstructures play an important role in the properties and the quality of the final cast product. The authors have investigated the transition from columnar to equiaxed grain growth (CET) in the framework of the ESA map CETSOL in Al–Si hypoeutectic alloys under microgravity conditions on the sounding rocket flight MAXUS-7. In the directionally solidified rod-like samples, the bulk melt flow is suppressed and diffusive mass and heat transport without sedimentation of refiner particles or equiaxed grains is obtained. The analysis of the processed samples creates benchmark data for validation and development of physical models for the formation of equiaxed grains and the CET. Here the authors present preliminary results from the analysis of two AlSi7 samples, one with and the other without addition of grain refiners (Ti and B) under identical experimental conditions. Critical parameters at the CET for temperature gradient and solidification rate are obtained from the experiments, as well as some characteristics of the grain structure. In a first approach the critical parameters are compared to predictions from Hunt's mechanical blocking model.
Elderly fall risk prediction based on a physiological profile approach using artificial neural networks

Falls play a critical role in older people’s life as it is an important source of morbidity and mortality in elders. In this article, elders fall risk is predicted based on a physiological profile approach using a multilayer neural network with back-propagation learning algorithm. The personal physiological profile of 200 elders was collected through a questionnaire and used as the experimental data for learning and testing the neural network. The profile contains a series of simple factors putting elders at risk for falls such as vision abilities, muscle forces, and some other daily activities and grouped into two sets: psychological factors and public factors. The experimental data were investigated to select factors with high impact using principal component analysis. The experimental results show an accuracy of ≈90 percent and ≈87.5 percent for fall prediction among the psychological and public factors, respectively. Furthermore, combining these two datasets yield an accuracy of ≈91 percent that is better than the accuracy of single datasets. The proposed method suggests a set of valid and reliable measurements that can be employed in a range of health care systems and physical therapy to distinguish people who are at risk for falls.
Determination of core structure periodicity and point defect density along dislocations

Understanding the structure of defects in crystalline materials is essential for modern materials science. While most defect characterization involves the inverse and non-unique problem of fitting possible structural models to experimental data, which are in many cases average spectra from a variety of defects (Electron Paramagnetic Resonance (EPR) Spectroscopy, Deep Level Transient Spectroscopy (DLTS), Photoluminescense Spectroscopy (PL), etc.), being able to directly probe the atomic structure of single defects would also provide their electronic as well as mechanical properties, since those can be determined computationally, once the structure is known. This work will report on a new electron diffraction technique to directly determine the periodicity of dislocation core structures as well as a way to greatly enhance the accuracy of the forbidden reflection lattice imaging (FRLI) technique to image individual structural point defects along partial dislocations. Electron microdiffraction experiments with Silicon samples oriented along the [110] direction will be described, which will give direct experimental evidence for the double period reconstruction of the 90◦ and 30◦ partial dislocations. Also, Silicon and β-Silicon Carbide samples with atomically flat (111) surfaces have been prepared. Perfectly smooth surfaces are shown to be essential for imaging point defects such as kinks along partial dislocations in these materials. In addition to these experiments, advances in the theory of electron diffraction will be reported. A new imaging technique called ”Atomic String Holography” will be introduced, as well as a solution to the inversion problem in dynamical scattering theory based on a new expansion of the matrix exponential of two non-commuting matrices, one of which is diagonal.
Detection of Image Region Duplication Using Spin Image

SUMMARY Passive-blind image forensics is a technique that judges whether an image is forged in the absence of watermarking. In image forgery, region duplication is a simple and widely used method. In this paper, we proposed a novel method to detect image region duplication using the spin image which is an intensity-based and rotation invariant descriptor. The method can detect region duplication exactly and is robust to geometric transformations. Furthermore, it is superior to the popular SIFT-based detection method when the copied patch is from smooth background. The experiments have proved the method’s e ﬀ ectiveness.
Towards automatic acquisition of linguistic features

This paper proposes a method to acquire linguistic features from a corpus of short sentences by extracting analogous sentences like what ’s the next station ? : where ’s the bus station ? :: what is the next stop ? : where is the bus stop ? The procedures used to construct clusters of analogous sentences are presented. Experiments performed on roughly 40,000 short sentences from the tourism domain in English and Japanese are reported, and the clusters produced are analyzed and interpreted in terms of linguistic features.
In situ observation of polypropylene composites reinforced by nonmetals recycled from waste printed circuit boards during tensile testing

A great amount of work has been done over the past few years to reuse the nonmetals recycled from waste printed circuit boards in polypropylene (PP) composites. This is because of the very fast generation rate of nonmetal pollution in the world each year and the very fast growing rate of PP applications in industries. This work focuses on the dynamic effects of nonmetals of different particle sizes on the tensile properties and reinforcing mechanisms of nonmetal/PP composites by in situ scanning electron microscopy tensile testing. The observed results show that the dominant deformation mechanism in pure PP is shear yielding. When fine nonmetals are filled into PP, mass microcracks are initiated. The glass fibers first resist the cracks and undertake the loading when they propagate. The crazes propagate slowly and then break the glass fibers. When coarse nonmetals are filled into PP, interfacial debonding and mass microcracks are initiated. A crack is either terminated when it meets another fiber–particulate bundle or branched into finer mass crazing. Interfacial debonding, crack initiation and propagation, and fiber pullout and breakage dissipate tremendous energy. These factors cause improvements in the strength and rigidity of nonmetal/PP composites. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
Interoperability of CABRI services and biochemical pathways databases: Conference Reviews

Common Access to Biological Resources and Information (CABRI) service is a ‘one-stop-shop’ for materials that are collected by a number of European culture collections that engage themselves in a quality service for the scientific community by adhering to Quality Guidelines for the management of resources and related information. It includes collections' catalogues that can be searched in an SRS implementation. A simple search facility, including a synonym search and a shopping cart, is also available. Within the European Biological Resource Centres Network (EBRCN) project, an extension and improvement of the catalogues' information is under way. This includes adding links to bibliographic databanks and sequence databases. Revision of ‘in-house’ controlled vocabularies used by data annotators is under way, in order to improve the setting up of external links, and new links to biochemical pathways databases are being set up for some of the catalogues. Copyright © 2004 John Wiley & Sons, Ltd.