Miracle-dz/UniFAR-FTUs huggingface dataset:
Laser microcutting of sheet metal for prototyping expandable stent-like structures in permanent and biodegradable alloys

For biomedical devices, cardiovascular stents in particular, the employed material plays a crucial role in controlling the mechanical and biological behavior. However, the material properties are directly influenced by the production route and the stent geometry. Conventional stent manufacturing route consists of laser microcutting of microtubes. Microtube extrusion and drawing are both costly and time consuming at a prototyping level. Instead, sheet material can be obtained relatively easier using non-dedicated tooling. This work, proposes the use of laser microcutting of thin sheets for producing mesh structures that can be expanded in a tubular form with the aim of assessing processability and expandability. AISI 316L stainless steel and AZ31 Mg alloy are studied representing the well-established permanent stent material and a candidate biodegradable alloy. Surface finishing is carried out with chemical etching. A conventional balloon catheter is used for comparative expandability tests.
Energy minimization of 3D cache-stacked processor based on thin-film thermoelectric coolers

In this paper, we explore the energy optimization of the processor with 3D stacked cache memory based on thin-film thermoelectric coolers (TFTEC). 3D integrated circuit is suitable for applications requiring small size, high performance and memory capacity. However, 3D integration incurs high power density owing to high temperature and high leakage power. TFTEC as active cooler can be used to deal with high temperature and high leakage energy consumption and eventually to reduce overall energy consumption. Experimental results show that 3D processor with TFTEC achieves a reduction of total energy consumption of both processor and TFTEC by up to 20% compared with processor without TFTEC under a given task's deadline and temperature constraints
Cluster-Based Maximum Consensus Time Synchronization in IWSNs

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs). Considering the demand of low energy consumption, fast convergence and robustness for IWSNs, this paper presents a novel Cluster-based Maximum consensus Time Synchronization method. Based on the theory of distributed consensus, the method utilizes the maximum consensus approach to realize the intra-cluster time synchronization. In the inter-cluster time synchronization, adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. In addition, the clustering technique is incorporated in the method, which can effectively reduce the redundant data. And the hops can be controlled, which improves the energy efficiency and convergence rate very well. At last, the simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works.
1 Video Compression for Desktop Applications

This paper discusses the current state of compression for digital video on the desktop. Today there are many choices for video compression that yield different performance in terms of compression factor, quality, bitrate, and cost. Users want a single low cost solution which, unfortunately, today is non-existent. Consequently, users will have to develop applications in an environment with multiple representations for digital video unless PC’s can be assigned to dedicated applications. Alternatively, programmable compression/decompression boards can be used to solve the problem. Eventually, special-purpose hardware solutions will be replaced by general-purpose software running on desktop parallel processors which will be implemented by multiple CPU’s per chip.
Language Conflict in the Bilingual Brain

The large majority of humankind is more or less fluent in 2 or even more languages. This raises the fundamental question how the language network in the brain is organized such that the correct target language is selected at a particular occasion. Here we present behavioral and functional magnetic resonance imaging data showing that bilingual processing leads to language conflict in the bilingual brain even when the bilinguals’ task only required target language knowledge. This finding demonstrates that the bilingual brain cannot avoid language conflict, because words from the target and nontarget languages become automatically activated during reading. Importantly, stimulus-based language conflict was found in brain regions in the LIPC associated with phonological and semantic processing, whereas response-based language conflict was only found in the pre-supplementary motor area/anterior cingulate cortex when language conflict leads to response conflicts.
Deterministic OpenMP for Race-Free Parallelism

Recent deterministic parallel programming models show promise for their ability to replay computations and reproduce bugs, but they currently require the programmer to adopt restrictive or unfamiliar parallel constructs. Deterministic OpenMP (DOMP) is a new deterministic parallel environment built on the familiar OpenMP framework. By leveraging OpenMP's block-structured synchronization annotations, which are largely compatible with the constraints of a deterministic model, DOMP eases the parallelization of legacy serial code and preserves substantial compatibility with OpenMP software. A few OpenMP constructs, however, such as atomic and critical, are semantically nondeterministic and unsupported in DOMP. In three well-known parallel benchmark suites, we find that most (81%) uses of these nondeterministic constructs express programming idioms that are compatible with determinism but not directly expressible in OpenMP. DOMP therefore adds new OpenMP constructs to express such idioms deterministically, supporting pipelines and generalized reductions.
Nature Genetics Advance Online Publication Population Genomics of Populus Trichocarpa Identifies Signatures of Selection and Adaptive Trait Associations

A suite of forces and factors, including mutation, recombination, selection, population history and gene duplication influence patterns of intraspecific genetic variation. Distinguishing which factors have shaped sequence variation across a genome requires extensive whole-genome sequencing of multiple individuals, which has only recently become tractable 1. Most large-scale whole-genome resequencing studies have focused on model and domesticated species 1–5. However, extensive sequencing of natural populations holds great promise for advancing understanding of evolutionary biology, including identifying functional variation and the molecular bases of adaptation. Recent work in a number of species has identified genomic regions that show signatures of positive selection, suggesting that such regions contain loci that control adaptive traits 4,6–8. Relatively few studies, however, have combined genome-wide scans with phenotypic data to determine whether computationally identified selected regions influence adap-tive phenotypic variation 5,9–13. Genome-wide studies of large natural populations combined with phenotypic measurements are necessary to determine which factors shape patterns of genetic variation within species and, therefore, enhance understanding of adaptation. With large geographic ranges spanning wide environmental gradients and a long history of research showing local adaptation 14 , forest trees are ideal for examining the processes shaping genetic variation in natural populations. Forest trees cover approximately 30% of terrestrial land area 15 , provide direct feedback to global climate 15 and are often foundation species that organize entire biotic communities and biogeochemical systems 16,17. Clearly, biotic and abiotic interactions have influenced population sizes and distributions of forest trees, leaving diagnostic signatures in the genomes of present-day populations 14,18,19. A deeper understanding of the evolutionary and ecological forces that shaped these patterns will offer insights and options for ecosystem management, applied tree improvement and accelerated domestication efforts 20. Black cottonwood, Populus trichocarpa Torr. & Gray, is a dominant riparian tree that has become a model for the advancement of genome-level insights in forest trees 21. The sequencing of 16 P. trichocarpa genomes revealed widespread patterns of linkage disequilibrium (LD) and population structure 22 and extensive genecological studies have revealed a high degree of adaptive phenotypic variation in growth, vegetative phenology and physiological traits such as water-use efficiency and photosynthesis 23–25 , suggesting that local adaptation is prevalent. To date, candidate gene–association analyses have revealed loci with significant effects on phenotypic traits 26,27. However, thus far there have been no publications describing whole-genome associations for adaptive traits in P. trichocarpa, or their relationship to signatures of selection in …
The Effects of Cognitive Reappraisal and Expressive Suppression on Memory of Emotional Pictures

In the field of emotion research, the influence of emotion regulation strategies on memory with emotional materials has been widely discussed in recent years. However, existing studies have focused exclusively on regulating negative emotion but not positive emotion. Therefore, in the present study, we investigated the influence of emotion regulation strategies for positive emotion on memory. One hundred and twenty college students were selected as participants. Emotional pictures (positive, negative and neutral) were selected from Chinese Affective Picture System (CAPS) as experimental materials. We employed a mixed, 4 (emotion regulation strategies: cognitive up-regulation, cognitive down-regulation, expressive suppression, passive viewing) × 3 (emotional pictures: positive, neutral, negative) experimental design. We investigated the influences of different emotion regulation strategies on memory performance, using free recall and recognition tasks with pictures varying in emotional content. The results showed that recognition and free recall memory performance of the cognitive reappraisal groups (up-regulation and down-regulation) were both better than that of the passive viewing group for all emotional pictures. No significant differences were reported in the two kinds of memory scores between the expressive suppression and passive viewing groups. The results also showed that the memory performance with the emotional pictures differed according to the form of memory test. For the recognition test, participants performed better with positive images than with neutral images. Free recall scores with negative images were higher than those with neutral images. These results suggest that both cognitive reappraisal regulation strategies (up-regulation and down-regulation) promoted explicit memories of the emotional content of stimuli, and the form of memory test influenced performance with emotional pictures.
Local Algorithms for Distributed Constraint Optimization in Dynamic , Anytime Environments

Many challenges in multi-agent coordination can be modeled as distributed constraint optimization problems (DCOPs) but existing complete algorithms do not scale well nor respond e ffectively to dynamic or anytime environments. As we move towards a future of ambient intelligence, in which large groups of agents must quickly coordinate, these deficiencies must be addressed. We decompose DCOP into a graphical game and investigate the evolution of various stochastic and deterministic algorithms. We also develop techniques that allow for coordinated negotiation while maintaining distributed control of variables. We prove monotonicity properties of certain approaches and detail arguments about equilibrium sets that o ffer insight into the tradeo ffs between e fficiency and solution quality. The ideas were tested in a simulated sensor network domain as well as a randomized, abstract domain.
A study of web content analysis on cultural heritage

The following text presents a research project focusing on cultural heritage through the Internet. The main goal of this study is to identify the mechanisms used to spread the Spanish cultural heritage through municipalities' websites. It is well known that cultural heritage represents one of the tourism industry bases, which is very important to Spanish economy. However, cultural heritage is also an element that helps to shape the social identity of Spanish citizens. Thus, this research aims to carry out content analysis of 500 websites, and then make a cultural portrait of our society in the Digital Age.
A Dirty Word or a Dirty World?

We explored the effect of attribute framing on choice, labeling charges for environmental costs as either an earmarked tax or an offset. Eight hundred ninety-eight Americans chose between otherwise identical products or services, where one option included a surcharge for emitted carbon dioxide. The cost framing changed preferences for self-identified Republicans and Independents, but did not affect Democrats’ preferences. We explain this interaction by means of query theory and show that attribute framing can change the order in which internal queries supporting one or another option are posed. The effect of attribute labeling on query order is shown to depend on the representations of either taxes or offsets held by people with different political affiliations.
β-Glucan from Two Sources of Oat Concentrates Affect Postprandial Glycemia in Relation to the Level of Viscosity

Objective: Soluble dietary fiber has been shown to attenuate the postprandial rise in blood glucose levels and reduce the risk of type 2 diabetes and cardiovascular disease. This effect seems to be related to its rheological properties including viscosity. We examined the intra-fiber variability between two different processing methods of concentrating β-glucan from oats (aqueous vs. enzymatic) in relation to the level of viscosity of β-glucan and its effect on postprandial glycemia in healthy individuals. Design: In an acute, randomized, double-blind, crossover study, 11 healthy subjects (gender: 5M:6F; age: 34 ± 5 years; BMI: 23 ± 0.8 kg/m2) were randomly assigned, on three separate occasions, to consume one of three fiber-matched treatments along with a 75g oral glucose drink. The enzymatically processed β-glucan (Oat-A) differed from β-glucan processed through the aqueous method (Oat-B) solely with regard to viscosity. Finger-prick capillary blood samples were obtained at fasting and at 15, 30, 45, 60, 90 and 120 min after the start of the test drink. The viscosities of the fiber drinks were determined (Paar Physica UDS200 viscometer). Results: Rheological measurements demonstrated that Oat-A had a significantly higher viscosity than Oat-B and control at 5, 15, 30, 60, and 120 min (p < 0.001). The incremental area under the glucose curve (AUC) on Oat-A was 19.6% and 17% lower than that of Oat-B and control, respectively (p < 0.01). Conclusions: This study shows that processing oat β-glucan through enzymatic, rather than by aqueous methods, preserves the viscosity and improves postprandial glycemic control.
LACS System Analysis on Retrieval Models for the MediaEval 2014 Search and Hyperlinking Task

We describe the LACS submission to the Search sub-task of the Search and Hyperlinking Task at MediaEval 2014. Our experiments investigate how different retrieval models interact with word stemming and stopword removal. On the development data, we segment the subtitle and Automatic Speech Recognition (ASR) transcripts into fixed length time units, and examine the effect of different retrieval models. We find that stemming provides consistent improvement; stopword removal is more sensitive to the retrieval models on the subtitles. These manipulations do not contribute to stable improvement on the ASR transcripts. Our experiments on test data focus on the subtitle. The gap in performance for different retrieval models is much less compared to the development data. We achieved 0.477 MAP on the test data.
FlexTag: A Highly Flexible PoS Tagging Framework

We present FlexTag, a highly flexible PoS tagging framework. In contrast to monolithic implementations that can only be retrained but not adapted otherwise, FlexTag enables users to modify the feature space and the classification algorithm. Thus, FlexTag makes it easy to quickly develop custom-made taggers exactly fitting the research problem.
TRT, a Vertebrate and Protozoan Tc1-Like Transposon: Current Activity and Horizontal Transfer

Abstract We report a Danio rerio transposon named DrTRT, for D. rerio Transposon Related to Tc1. The complete sequence of the DrTRT transposon is 1,563 base pairs (bp) in length, and its transposase putatively encodes a 338-amino acid protein that harbors a DD37E motif in its catalytic domain. We present evidence based on searches of publicly available genomes that TRT elements commonly occur in vertebrates and protozoa. Phylogenetic and functional domain comparisons confirm that TRT constitutes a new subfamily within the Tc1 family. Hallmark features of having no premature termination codons within the transposase, the presence of all expected functional domains, and its occurrence in the bony fish transcriptome suggest that TRT might have current or recent activity in these species. Further analysis showed that the activity of TRT elements in these species might have arisen about between 4 and 19 Ma. Interestingly, our results also implied that the widespread distribution of TRT among fishes, frog, and snakes is the result of multiple independent HT events, probably from bony fishes to snakes or frog. Finally, the mechanisms underlying horizontal transfer of TRT elements are discussed.
Signal & Image Denoising U S I N G C O N S T R a I N E D O P T I M I Z a T I O N I Background A. Adaptive Diffusion Equation

Denoising of images is an important task in image processing and analysis, and it plays a significant role in modern applications in different fields, including medical imaging and preprocessing for computer vision. Consider an image contaminated by noise (without loss of generality, we assume additive noise): () () () I f ξ = + x x x Our goal is to remove that noise, resulting in minimal damage to the image. Since in most cases the result consumer is human, the criterion for denoising fidelity would be the human visual perception of the result, rather than any of known mathematical criteria, such as minimal mean error (MSE) or minimal maximal difference (minimax). The most naïve approach would be performing some kind of low-pass filtering on the image, e.g. by convolution of Gaussian. Perona and Malik [1] claim that low-pass filtering by Gaussian kernel convolution can be equivalently formulated as forward diffusion () () 2 ; ; const t I t c I t c ∂ = ∇ = x x where t is the time parameter proportional to the Gaussian standard deviation and c is the diffusion coefficient. The disadvantage of low-pass filtering or homogenous adaptive diffusion in image enhancement applications is the fact that Gaussian blurring does not respect the natural edges of the image. Hence, it is impossible to use simple Gaussian blurring in order to enhance the natural features of the image, which the eye perceives the best. Figure 1.1: Gaussian blurring result: both the edges and the background are blurred (this image is a visualization of the " tree " example given by Perona & Malik, created in PhotoShop). The desired denoising algorithm must be edge-preserving, thus performing diffusion only in the regions divided by edges and leaving the edges untouched, what is termed as " strong intra-region diffusion " and " weak inter-region diffusion ". The formulation of edge criterion is part of the solution rather than of the problem itself, since different edge indicators may be used, leading to different results. One of the ways to implement such algorithm according to Perona and Malik [1] is by solving a non-homogenous diffusion equation. () 2 ; ; t I t c I t c I ϕ ∂ = ∇ = ∇ x x The diffusion coefficient achieves high value (strong blurring) in the interior of each region and low value (weak blurring) on the edges. …
Algebraic Meta-Theory of Processes with Data

There exists a rich literature of rule formats guaranteeing different algebraic properties for formalisms with a Structural Operational Semantics. Moreover, there exist a few approaches for automatically deriving axiomatizations characterizing strong bisimilarity of processes. To our knowledge, this literature has never been extended to the setting with data (e.g. to model storage and memory). We show how the rule formats for algebraic properties can be exploited in a generic manner in the setting with data. Moreover, we introduce a new approach for deriving sound and ground-complete axiom schemata for a notion of bisimilarity with data, called stateless bisimilarity, based on intuitive auxiliary function symbols for handling the store component. We do restrict, however, the axiomatization to the setting where the store component is only given in terms of constants.
Word Sense Annotation of Polysemous Words by Multiple Annotators

We describe results of a word sense annotation task using WordNet, involving half a dozen well-trained annotators on ten polysemous words for three parts of speech. One hundred sentences for each word were annotated. Annotators had the same level of training and experience, but interannotator agreement (IA) varied across words. There was some effect of part of speech, with higher agreement on nouns and adjectives, but within the words for each part of speech there was wide variation. This variation in IA does not correlate with number of senses in the inventory, or the number of senses actually selected by annotators. In fact, IA was sometimes quite high for words with many senses. We claim that the IA variation is due to the word meanings, contexts of use, and individual differences among annotators. We find some correlation of IA with sense confusability as measured by a sense confusion threshhold (CT). Data mining for association rules on a flattened data representation indicating each annotator's sense choices identifies outliers for some words, and systematic differences among pairs of annotators on others.
A Parameter-free Statistical Measurement of Halos with Power Spectra

We show that in the halo model of large-scale structure formation, the difference between the Fourier and the discrete wavelet transform (DWT) power spectra provides a statistical measurement of the halos. This statistical quantity is free from parameters related to the shape of the mass profile and the identification scheme of the halos. That is, the statistical measurement is invariant in the sense that models with reasonably defined and selected parameters of the halo models should yield the same difference of the Fourier and DWT spectra. This feature is useful to extract ensemble-averaged properties of halos, which cannot be obtained with the identification of individual halos. To demonstrate this point, we show with WIGEON hydrodynamic simulation samples that the spectrum difference provides a quantitative measurement of the discrepancy of the distribution of baryonic gas from that of the underlying dark matter field within halos. We also show that the mass density profile of halos in physical space can be reconstructed with this statistical measurement. This profile essentially is the average over an ensemble of halos, including well-virialized halos, as well as halos with significant internal substructures. Moreover, this reconstruction is sensitive to the tail of the mass density profile. We showed that the profile with a 1/r3 tail gives a very different result from that with 1/r2. Other possible applications of this method are discussed as well.