Miracle-dz/UniFAR-FTUs huggingface dataset:
Domain-Specific Control of Selective Attention

Previous research has shown that loading information on working memory affects selective attention. However, whether the load effect on selective attention is domain-general or domain-specific remains unresolved. The domain-general effect refers to the findings that load in one content (e.g. phonological) domain in working memory influences processing in another content (e.g., visuospatial) domain. Attentional control supervises selection regardless of information domain. The domain-specific effect refers to the constraint of influence only when maintenance and processing operate in the same domain. Selective attention operates in a specific content domain. This study is designed to resolve this controversy. Across three experiments, we manipulated the type of representation maintained in working memory and the type of representation upon which the participants must exert control to resolve conflict and select a target into the focus of attention. In Experiments 1a and 1b, participants maintained digits and nonverbalized objects, respectively, in working memory while selecting a target in a letter array. In Experiment 2, we presented auditory digits with a letter flanker task to exclude the involvement of resource competition within the same input modality. In Experiments 3a and 3b, we replaced the letter flanker task with an object flanker task while manipulating the memory load on object and digit representation, respectively. The results consistently showed that memory load modulated distractibility only when the stimuli of the two tasks were represented in the same domain. The magnitude of distractor interference was larger under high load than under low load, reflecting a lower efficacy of information prioritization. When the stimuli of the two tasks were represented in different domains, memory load did not modulate distractibility. Control of processing priority in selective attention demands domain-specific resources.
Multilinear locality preserving canonical correlation analysis for face recognition

We propose in this paper a multilinear locality preserving canonical correlation analysis (MLPCCA) method for face recognition. Motivated by the fact that both spatial structure information within each face sample and local geometry information among multiple face samples are useful for facial image feature extraction, we utilize them simultaneously and derive an improved canonical correlation analysis algorithm — MLPCCA — to seek multiple sets of pairwise projection bases to maximize the correlation of two facial image sets. The proposed MLPCCA method is designed to characterize the potential nonlinear correlation of two image sets by utilizing both the spatial and local geometrical information, hence is more suitable for face recognition across large pose and illumination variants. Experimental results are presented to demonstrate the efficacy of the proposed method.
Searching the Web: from keywords to semantic queries

Within the emergent Semantic Web framework, the use of traditional Web search engines based on keywords provided by the users is not adequate any more. Instead, new methods based on the semantics of user keywords must be defined to search in the vast Web space without incurring in an undesirable loss of information. In this paper we propose a system that takes as input a list of plain keywords provided by the user and outputs equivalent semantic queries expressed in a knowledge representation language, that could be used to retrieve relevant data. For the translation task, specialized agents manage a third-party thesaurus and a pool of pre-existing ontologies to obtain the different meanings of the user keywords and discover semantic relationships between them in run-time.
To Cache or Not To Cache? Experiments with Adaptive Models in Statistical Machine Translation

We report results of our submissions to the WMT 2010 shared translation task in which we applied a system that includes adaptive language and translation models. Adaptation is implemented using exponentially decaying caches storing previous translations as the history for new predictions. Evidence from the cache is then mixed with the global background model. The main problem in this setup is error propagation and our submissions essentially failed to improve over the competitive baseline. There are slight improvements in lexical choice but the global performance decreases in terms of BLEU scores.
A Survey of Distributed Data Structures in Peer-to-Peer Systems

Abstract. We present a survey of Distributed Data Structures (DDSs) in the Peer-to-Peer domain. We start from one of the earliest designs that were presented in the literature and build the survey from there. We try to classify the predominant DDSs in the literature and discuss their architecture, working, salient features and performance briefly. The paper is broadly divided in to two categories: Hash-Based DDS and Order-Based DDS. We highlight the pros, cons, similarities and differences of both these categories and review some examples of each.
A novel method for accurate operon predictions in all sequenced prokaryotes

We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacter pylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from six phylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC 6803 has many operons even though it has unusually wide spacings between conserved adjacent genes.
Novel fabrication of an Au nanocone array on polycarbonate for high performance surface-enhanced Raman scattering

Surface-enhanced Raman scattering (SERS) with enormous enhancements has been applied for ultra-sensitive detection in various fields, but the fabrication of large-scale, controllable and cost-effective substrates is a major challenge. We propose a novel fabrication process with a gas-assisted hot embossing process and an anodic aluminum oxide template to obtain the SERS substrate on a 1 × 1 cm polycarbonate film. The SERS spectra of 4-mercaptobenzoic acid (PMBA) on the gold substrate have been measured. The enhancement factors are between 3.99 × 107 and 4.92 × 107, depending on the heights of nanocones, which can be controlled by the embossing temperature and pressure. The simple and inexpensive SERS substrate has potential for wide application in SERS-based sensors.
Distributed Simulation: A Case Study in Design and Verification of Distributed Programs

The problem of system simulation is typically solved in a sequential manner due to the wide and intensive sharing of variables by all parts of the system. We propose a distributed solution where processes communicate only through messages with their neighbors; there are no shared variables and there is no central process for message routing or process scheduling. Deadlock is avoided in this system despite the absence of global control. Each process in the solution requires only a limited amount of memory. The correctness of a distributed system is proven by proving the correctness of each of its component processes and then using inductive arguments. The proposed solution has been empirically found to be efficient in preliminary studies. The paper presents formal, detailed proofs of correctness.
Differential Function of N-Cadherin and Cadherin-7 in the Control of Embryonic Cell Motility

Similar amounts of N-cadherin and cadherin-7, the prototypes of type I and type II cadherin, induced cell-cell adhesion in murine sarcoma 180 transfectants, Ncad-1 and cad7-29, respectively. However, in the initial phase of aggregation, Ncad-1 cells aggregated more rapidly than cad7-29 cells. Isolated Ncad-1 and cad7-29 cells adhered and spread in a similar manner on fibronectin (FN), whereas aggregated cad7-29 cells were more motile and dispersed than aggregated Ncad-1 cells. cad7-29 cells established transient contacts with their neighbors which were stabilized if FN-cell interactions were perturbed. In contrast, Ncad-1 cells remained in close contact when they migrated on FN. Both β-catenin and cadherin were more rapidly downregulated in cad7-29 than in Ncad-1 cells treated with cycloheximide, suggesting a higher turnover rate for cadherin-7–mediated cell-cell contacts than for those mediated by N-cadherin. The extent of FN-dependent focal adhesion kinase phosphorylation was much lower if the cells had initiated N-cadherin–mediated rather than cadherin-7–mediated cell adhesion before plating. On grafting into the embryo, Ncad-1 cells did not migrate and remained at or close to the graft site, even after 48 h, whereas grafted cad7-29 cells dispersed efficiently into embryonic structures. Thus, the adhesive phenotype of cadherin-7–expressing cells is regulated by the nature of the extracellular matrix environment which also controls the migratory behavior of the cells. In addition, adhesions mediated by different cadherins differentially regulate FN-dependent signaling. The transient contacts specifically observed in cadherin- 7–expressing cells may also be important in the control of cell motility.
The modification of ultra‐high‐molecular‐weight polyethylene supramolecular structures induced by irradiation and thermal treatment

The effect of γ-radiation and subsequent thermal treatment on the crystallinity and rheological characteristics of ultra-high-molecular-weight polyethylene (UHMWPE) has been investigated. Irradiation of the polymer was performed using a 60Co γ-emitter at laboratory temperatures. Five irradiation doses (25, 50, 100, 150 and 200 kGy), two dose rates (0.25 and 2.5 kGy/h) and two (atmosphereic environments) (air and nitrogen) were used. Some irradiated samples were thermally treated at 190°C. The crystallinity changes were determined using wide-angle X-ray diffraction (WAXS), while the rheological characteristics were measured with a rotation rheometer. In addition to the expected effect of γ-rays on the structural changes and rheological behaviour of UHMWPE at higher radiation doses (from about 50 kGy), two interesting results were obtained. First, a minimum on the dependence of the radiation dose as a function of crystallinity was found for all of the measured samples. The crystallinity decrease in UHMWPE is also associated with substantial changes in its rheological properties at temperature above the melting point. Secondly, a remarkable effect of the dose rate on the measured characteristics has been proved. Copyright © 2003 John Wiley & Sons, Ltd.
Low oxygen reduces the modulation to an oxidative phenotype in monolayer‐expanded chondrocytes

Autologous chondrocyte implantation requires a phase of in vitro cell expansion, achieved by monolayer culture under atmospheric oxygen levels. Chondrocytes reside under low oxygen conditions in situ and exhibit a glycolytic metabolism. However, oxidative phosphorylation rises progressively during culture, with concomitant reactive oxygen species production. We determine if the high oxygen environment in vitro provides the transformation stimulus. Articular chondrocytes were cultured in monolayer for up to 14 days under 2%, 5%, or 20% oxygen. Expansion under 2% and 5% oxygen reduced the rate at which the cells developed an oxidative phenotype compared to 20% oxygen. However, at 40 ± 4 fmol cell−1 h−1 the oxygen consumption by chondrocytes expanded under 2% oxygen for 14 days was still 14 times the value observed for freshly isolated cells. Seventy‐five to 78% of the increased oxygen consumption was accounted for by oxidative phosphorylation (oligomycin sensitive). Expansion under low oxygen also reduced cellular proliferation and 8‐hydroxyguanosine release, a marker of oxidative DNA damage. However, these parameters remained elevated compared to freshly isolated cells. Thus, expansion under physiological oxygen levels reduces, but does not abolish, the induction of an oxidative energy metabolism. We conclude that simply transferring chondrocytes to low oxygen is not sufficient to either maintain or re‐establish a normal energy metabolism. Furthermore, a hydrophobic polystyrene culture surface which promotes rounded cell morphology had no effect on the development of an oxidative metabolism. Although the shift towards an oxidative energy metabolism is often accompanied by morphological changes, this study does not support the hypothesis that it is driven by them. J. Cell. Physiol. 222:248–253, 2010. © 2009 Wiley‐Liss, Inc.
Introduction of apple ANR genes into tobacco inhibits expression of both CHI and DFR genes in flowers, leading to loss of anthocyanin

Three genes encoding anthocyanidin reductase (ANR) in apple (Malus×domestica Borkh.), designated MdANR1, MdANR2a, and MdANR2b, have been cloned and characterized. MdANR1 shows 91% identity in coding DNA sequences with MdANR2a and MdANR2b, while MdANR2a and MdANR2b are allelic and share 99% nucleotide sequence identity in the coding region. MdANR1 and MdANR2 genes are located on linkage groups 10 and 5, respectively. Expression levels of both MdANR1 and MdANR2 genes are generally higher in yellow-skinned cv. Golden Delicious than in red-skinned cv. Red Delicious. Transcript accumulation of MdANR1 and MdANR2 genes in fruits gradually decreased throughout fruit development. Ectopic expression of apple MdANR genes in tobacco positively and negatively regulates the biosynthesis of proanthocyanidins (PAs) and anthocyanin, respectively, resulting in white, pale pink-coloured, and white/red variegated flowers. The accumulation of anthocyanin is significantly reduced in all tobacco transgenic flowers, while catechin and epicatechin contents in transgenic flowers are significantly higher than those in flowers of wild-type plants. The inhibition of anthocyanin synthesis in tobacco transgenic flowers overexpressing MdANR genes is probably attributed to down-regulation of CHALCONE ISOMERASE (CHI) and DIHYDROFLAVONOL-4-REDUCTASE (DFR) genes involved in the anthocyanin pathway. Interestingly, several transgenic lines show no detectable transcripts of the gene encoding leucoanthocyanidin reductase (LAR) in flowers, but accumulate higher levels of catechin in flowers of transgenic plants than those of wild-type plants. This finding suggests that the ANR gene may be capable of generating catechin via an alternative route, although this mechanism is yet to be further elucidated.
Influence of technological parameters on additive manufacturing steel parts in Selective Laser Sintering

Purpose: The investigations have been carried out on test pieces of 316L stainless steel parts fabricated by Selective Laser Sintering technique. The effect of selective laser sintering parameters such as power output, laser distance between the points sintered metal powder during additive manufacturing as well as the orientation of models relative to the laser beam and substrate on the roughness, surface morphology and wear resistance of manufactured models were performed. Design/methodology/approach: To fabricate 316L stainless steel parts, the method using selective laser sintering (SLS) technique, using Renishaw AM 125 machine is utilised. Wear resistance, roughness and surface morphology of SLS produced samples prepared via different process parameters are investigated. Findings: The results show that the wear resistance and surface morphology are strongly influenced by orientation of the parts relative to the laser beam, power output of laser and laser distance between the points sintered metal powder during additive manufacturing. Research limitations/implications: In the nearest future, studies will be conducted to establish influence of laser parameters such as scan speed, focus offset, exposure time, diameter of laser beam and hatch parameters such as hatch type and hatch distance on the quality and density of AM steel parts. Practical implications: Stainless steel is one of the most popular materials used for selective laser sintering (SLS) processing to produce nearly fully dense components from 3D CAD models. Reduction of surface roughness is one of the key research issues within the additive manufacturing technique SLS, since one of the major cost factors is the post processing of surfaces by means of milling, turning, grinding and polishing. Originality/value: This paper can serve as an aid in understanding the importance of technological parameters on quality and wear resistance of manufactured AM parts made by SLS technique.
Color-based face detection using skin locus model and hierarchical filtering

Introduces an architecture for face detection in color images. Based on skin locus and successive detectors, the method allows high efficiency, under drastically varying illumination conditions. While most color-based approaches work only if the camera was calibrated and detect faces if the features (eyes, mouth, eyebrows.) are visible and detectable, our system detects faces even when these features are not well defined. The detection is based on a robust modeling of skin color, called skin locus, which is used to extract the skin-like regions. After orientation normalization and based on verifying a set of criteria (face symmetry, presence of some facial features, variance of pixel intensities and connected component arrangement), only facial regions are selected. We show that our system can detect faces and deal with different conditions (size, orientation, illumination, and complex background).
Energy Consumption Data Based Machine Anomaly Detection

The ever increasing of product development and the scarcity of the energy resources that those manufacturing activities heavily rely on have made it of great significance the study on how to improve the energy efficiency in manufacturing environment. Energy consumption sensing and collection enables the development of effective solutions to higher energy efficiency. Further, it is found that the data on energy consumption of manufacturing machines also contains the information on the conditions of these machines. In this paper, methods of machine anomaly detection based on energy consumption information are developed and applied to cases on our Syil X4 computer numerical control (CNC) milling machine. Further, given massive amount of energy consumption data from large amount machining tasks, the proposed algorithms are being implemented on a Storm and Hadoop based framework aiming at online real-time machine anomaly detection.
Black-Box Classifier Interpretation Using Decision Tree and Fuzzy Logic-Based Classifier Implementation

Black-box classifiers, such as artificial neural network and support vector machine, are a popular classifier because of its remarkable performance. They are applied in various fields such as inductive inferences, classifications, or regressions. However, by its characteristics, they cannot provide appropriate explanations how the classification results are derived. Therefore, there are plenty of actively discussed researches about interpreting trained black-box classifiers. In this paper, we propose a method to make a fuzzy logic-based classifier using extracted rules from the artificial neural network and support vector machine in order to interpret internal structures. As an object of classification, an anomalous propagation echo is selected which occurs frequently in radar data and becomes the problem in a precipitation estimation process. After applying a clustering method, learning dataset is generated from clusters. Using the learning dataset, artificial neural network and support vector machine are implemented. After that, decision trees for each classifier are generated. And they are used to implement simplified fuzzy logic-based classifiers by rule extraction and input selection. Finally, we can verify and compare performances. With actual occurrence cased of the anomalous propagation echo, we can determine the inner structures of the black-box classifiers.
Automatic Coreference Annotation in Basque

This paper presents a hybrid system for annotating nominal and pronominal coreferences by combining ML and rule-based methods. The system automatically annotates different types of coreferences; the results are then verified and corrected manually by linguists. The system provides automatically generated suggestions and a framework for easing the manual portion of the annotation process. This facilitates the creation of a broader annotated corpus, which can then be used to reiteratively improve our ML and rule-based techniques.
New horizon in the tribology of diamondlike carbon films

Carbon is the building block of numerous solid materials possessing some of the most unusual properties, such as super-high hardness and thermal conductivity, as in diamond, or unusual softness and lubricity, as in graphite. It is the main constituent of various exotic nanomaterials like nanotubes, nanofibres, nano-onions and buckyballs, as well as numerous bulk composites, glassy carbons, carbides, etc. During the past three decades or so, carbon has also been used in the synthesis of thin diamond, diamondlike carbon (DLC), carbon nitride, and boron carbide coatings. Because of their exceptional mechanical and tribological properties, all these coatings are now used in a wide range of engineering applications to control friction and wear.
The Quick Inventory of Depressive Symptomatology (Clinician and Self-Report Versions) in Patients With Bipolar Disorder

ABSTRACT Introduction: The clinical and self-report versions of the Quick Inventory of Depressive Symptomatology (QIDS-C16 and QIDS-SR16) have been well studied in patients with major depressive disorder and in one recent study using patients with bipolar disorder. This article examines these measures in a second sample of 141 outpatients with bipolar disorder in different phases of the illness. Methods: At baseline, 61 patients were depressed and 30 were euthymic; at exit, 50 were depressed and 52 were euthymic. The remaining patients (at baseline or exit) were in either a manic or mixed phase and were pooled for statistical reasons. Results: Similar results were found for the QIDS-C16 and QIDS-SR16. Scores were reasonably reliable to the extent that variability within groups permitted. As expected, euthymic patients showed less depressive symptomatology than depressed patients. Sad mood and general interest were tne most discriminating symptoms between depressed and euthymic phases. Changes in illness phase (baseline to exit) were associated with substantial changes in scores. The relation of individual depressive symptoms to the overall level of depression was consistent across phases. Conclusion: Both the QIDS-SR16 and QIDS-C16 are suitable measures of depressive symptoms in patients with bipolar disorder.