Miracle-dz/UniFAR-FTUs huggingface dataset:
cAR: Contact Augmented Reality with Transparent-Display Mobile Devices

We present Contact Augmented Reality (cAR), a form of AR where a mobile device with a transparent display rests on top of the augmented object. cAR is based on the notion that interactions with digital content are enriched by the tangibility of physically moving a device on and off the augmented object. We propose and implement three categories of cAR interaction techniques: contact-based, off-contact and content-aware. We built two cAR prototypes and explore how cAR can be applied to the domain of active reading. A first low-fidelity prototype, consisting of an interactive tabletop and transparent acrylic tangibles, allowed us to iteratively design and test interaction techniques. The second and higher-fidelity prototype, called a tPad, uses a semi-transparent touch-enabled 7" LCD display that is placed on top of back-lit paper documents. The tPad uses an external camera and feature matching algorithms to identify the document and to determine its location and orientation. We report on user feedback and elaborate on the salient technical challenges for cAR devices.
The complete mitochondrial genome of the Linwu duck

Abstract In this study, the complete mitochondrial genome sequence of the Linwu duck was first reported in Human Province, which was determined through PCR-based method. Linwu duck is one of the famous native breed in China. The total length of the mitogenome is 16,604 bp, with the base composition of 29.20% for A, 22.21% for T, 32.82% for C, 15.78% for G, in the order C > A > T > G feature occurring in the Linwu duck. It is made up of 2 ribosomal RNA genes, 13 protein-coding genes, 22 transfer RNA genes and one non-coding control region (D-loop region). The complete mitochondrial genome sequence of the Linwu duck in Human Province provides an important data for further study about genetic mechanism and breeding.
Neural Basis of Linearization in Speech Production

An initial stage of speech production is conceptual planning, where a speaker determines which information to convey first (the linearization problem). This fMRI study investigated the linearization process during the production of “before” and “after” sentences. In “after” sentences, a series of events is expressed in the order of event occurrence. In “before” sentences, however, the order of event mention is achieved by reversing the chronological order. We suggested that the linearization process may be supported by a neural network connecting the left middle temporal gyrus (MTG) with the medial superior frontal gyrus, left middle frontal gyrus, and left angular gyrus/inferior parietal gyrus. Within this network, regions were more activated and interregional interactions were strongly enhanced for producing “before” than “after” sentences. The left MTG was also functionally connected with the left orbital inferior frontal gyrus, contributing to the retrieval of necessary world knowledge and linguistic knowledge. Connectivity between these two regions was not different between conditions.
TGFβ (transforming growth factor β) and keratocyte motility in 24 h zebrafish explant cultures

Fish keratocytes are used as a model system for the study of the mechanics of cell motility because of their characteristic rapid, smooth gliding motion, but little work has been done on the regulation of fish keratocyte movement. As TGFβ (transforming growth factor β) plays multiple roles in primary human keratinocyte cell migration, we investigated the possible involvement of TGFβ in fish keratocyte migration. Studying the involvement of TGFβ1 in 24 h keratocyte explant allows the examination of the cells before alterations in cellular physiology occur due to extended culture times. During this initial period, TGFβ levels increase 6.2‐fold in SFM (serum‐free medium) and 2.4‐fold in SFM+2% FBS (fetal bovine serum), while TGFβ1 and TGFβRII (TGFβ receptor II) mRNA levels increase ∼3‐ and ∼5‐fold respectively in each culture condition. Two measures of motility, cell sheet area and migration distance, vary with the amount of exogenous TGFβ1 and culture media. The addition of 100 ng/ml exogenous TGFβ1 in SFM increases both measures [3.3‐fold (P=4.5 × 10−5) and 26% (P=2.1 × 10−2) respectively]. In contrast, 100 ng/ml of exogenous TGFβ1 in medium containing 2% FBS decreases migration distance by 2.1‐fold (P=1.7 × 10−7), but does not affect sheet area. TGFβ1 (10 ng/ml) has little effect on cell sheet area in SFM cultures, but leads to a 1.8‐fold increase (P=1.5 × 10−2) with 2% FBS. The variable response to TGFβ1 may be, at least in part, explained by the effect of 2% FBS on cell morphology, mode of motility and expression of endogenous TGFβ1 and TGFβRII. Together, these results suggest that expression of TGFβ and its receptor are up‐regulated during zebrafish keratocyte explant culture and that TGFβ promotes fish keratocyte migration.
Experimental implementation of asynchronous rendezvous protocols using microsoft sora

In opportunistic networks, mobile devices can communicate with each other via connections between them that are not always available. After a device discovers another device in its transmission range, communication is enabled. Without any knowledge about geographical positions of mobile devices, neighbor discovery is energy consumption process. For example, continuous scanning is the fastest way to find neighbors but most mobile devices are battery-powered and cannot afford persistent scanning. So, neighbor discovery with minimal energy consumption is very important. Most neighbor discovery schemes adopt periodic sleep-wake scheduling associated with rendezvous capability. This means that each device just explores neighbors while they wake-up. Many rendezvous protocols have been proposed to reduce energy consumption. In this paper, we implement three promising asynchronous rendezvous protocols using Microsoft Research Software Radio (Sora) board and present the experimental results. Our experiment provides experimental insight into the implementation of rendezvous protocols in real situations.
Humans as feature extractors: Combining prosody and personality perception for improved speaking style recognition

This paper presents experiments where natural and spontaneous cognitive processes, in particular those who lead to the attribution of personality traits to unacquainted people, are used as a natural form of feature extraction. In particular, personality assessments provided by human judges are used as features to distinguish between professional and non-professional speakers. The same task is performed with prosodic features extracted with a fully automatic process for comparison purposes. Furthermore both prosodic features and personality assessments are combined. The results show that the discrimination between professional and non-professional speaking styles can be performed with an accuracy of 87.2% when using prosodic features, of 75.5% when using personality assessments, and of 90.0% when using the combination of the two.
Design Research Through Practice: From the Lab, Field, and Showroom

The authors of this volume (Ilpo Koskinen, John Zimmerman, Thomas Binder, Johan Redstrom, and Stephan Wensveen) argue that design research needs more than mathematics: it needs many other vocabularies as well, including art, cultural studies, anthropology, cognitive psychology, and communication. The book is clearly written and helpfully designed, with focused case studies and incisive cartoon-like summaries of key concepts. The reference section is extensive and truly useful: international in scope and broadly multidisciplinary. The authors, all academics, work in art, design, computer science, social science, filmmaking, engineering, and philosophy.
Image-based Localization and Pose Recovery Using Scale Invariant Features

In this paper, we propose a vision based mobile robot localization strategy. Local scale-invariant features are used as natural landmarks in unstructured and unmodified environment. The local characteristics of the features we use prove to be robust to occlusion and outliers. In addition, the invariance of the features to viewpoint change makes them suitable landmarks for mobile robot localization. Scale-invariant features detected in the first exploration are indexed into a location database. Indexing and voting allow efficient recognition of global localization. The localization result is verified by epipolar geometry between the representative view in database and the view to be localized, thus the probability of false localization will be decreased. The localization system can recover the pose of the camera mounted on the robot by essential matrix decomposition. Then the position of the robot can be computed easily. Both calibrated and un-calibrated cases are discussed and relative position estimation based on calibrated camera turns out to be the better choice. Experimental results show that our approach is effective and reliable in the case of illumination changes, similarity transformations and extraneous features
A Method of Learning Implication Networks from Empirical Data: Algorithm and Monte-Carlo Simulation-Based Validation

The paper describes an algorithmic means for inducing implication networks from empirical data samples. The induced network enables efficient inferences about the values of network nodes if certain observations are made. This implication induction method is approximate in nature as probabilistic network requirements are relaxed in the construction of dependence relationships based on statistical testing. In order to examine the effectiveness and validity of the induction method, several Monte Carlo simulations were conducted, where theoretical Bayesian networks were used to generate empirical data samples-some of which were used to induce implication relations, whereas others were used to verify the results of evidential reasoning with the induced networks. The values in the implication networks were predicted by applying a modified version of the Dempster-Shafer belief updating scheme. The results of predictions were, furthermore, compared to the ones generated by Pearl's (1986) stochastic simulation method, a probabilistic reasoning method that operates directly on the theoretical Bayesian networks. The comparisons consistently show that the results of predictions based on the induced networks would be comparable to those generated by Pearl's method, when reasoning in a variety of uncertain knowledge domains-those that were simulated using the presumed theoretical probabilistic networks of different topologies.
Contrasting patterns of genetic and phenotypic differentiation in two invasive salmonids in the southern hemisphere

Invasion success may be expected to increase with residence time (i.e., time since first introduction) and secondary releases (i.e., those that follow the original introduction), but this has rarely been tested in natural fish populations. We compared genetic and phenotypic divergence in rainbow trout and brown trout in Chile and the Falkland Islands to test the prediction that adaptive divergence, measured as PST/FST, would increase with residence time and secondary releases. We also explored whether interspecific competition between invaders could drive phenotypic divergence. Residence time had no significant effect on genetic diversity, phenotypic divergence, effective population size, or signatures of expansion of invasive trout. In contrast, secondary releases had a major effect on trout invasions, and rainbow trout populations mostly affected by aquaculture escapees showed significant divergence from less affected populations. Coexistence with brown trout had a positive effect on phenotypic divergence of rainbow trout. Our results highlight an important role of secondary releases in shaping fish invasions, but do not support the contention that older invaders are more differentiated than younger ones. They also suggest that exotic trout may not have yet developed local adaptations in these recently invaded habitats, at least with respect to growth‐related traits.
Inflation and relative price variability in the euro area: evidence from a panel threshold model

The impact of inflation on Relative Price Variability (RPV) generates an important channel for real effects of inflation. This article provides first evidence on the empirical relation between inflation and RPV in the euro area. Stirred by the widespread use of inflation caps or target bands in monetary policy practice, we are particularly interested in threshold effects of inflation. In line with the predictions of monetary search models, our results indicate that expected inflation significantly increases RPV only if inflation is either very low (below 0.95% per annum (p.a.)) or very high (above 4.96% p.a.).
Strictly Localized Sensor Self-Deployment for Optimal Focused Coverage

We consider sensor self-deployment problem, constructing FOCUSED coverage (F-coverage) around a Point of Interest (POI), with novel evaluation metric, coverage radius. We propose to deploy sensors in polygon layers over a locally computable equilateral triangle tessellation (TT) for optimal F-coverage formation, and introduce two types of deployment polygon, H-polygon and C-polygon. We propose two strictly localized solution algorithms, Greedy Advance (GA), and Greedy-Rotation-Greedy (GRG). The two algorithms drive sensors to move along the TT graph to surround POI. In GA, nodes greedily proceed as close to POI as they can; in GRG, when their greedy advance is blocked, nodes rotate around POI along locally computed H- or C-polygon to a vertex where greedy advance can resume. We prove that they both yield a connected network with maximized hole-free area coverage. To our knowledge, they are the first localized sensor self-deployment algorithms that provide such coverage guarantee. We further analyze their coverage radius property. Our study shows that GRG guarantees optimal or near optimal coverage radius. Through extensive simulation we as well evaluate their performance on convergence time, energy consumption, and node collision.
Degrasyn Potentiates the Antitumor Effects of Bortezomib in Mantle Cell Lymphoma Cells In vitro and In vivo: Therapeutic Implications

Mantle cell lymphoma (MCL) is an aggressive histotype of B-cell non–Hodgkin lymphoma that has increased in incidence over the past few decades and is incurable, usually poorly responsive to standard chemotherapy combinations, and associated with poor prognoses. Discovering new therapeutic agents with low toxicity that produce better outcomes in patients with MCL is an ongoing challenge. Recent studies showed that degrasyn, a novel small-molecule inhibitor of the Janus kinase/signal transducer and activation of transcription (JAK/STAT) pathway, exerts antitumor activity in lymphoid tumors by inhibiting key growth and survival signaling (JAK/STAT) pathways. In the present study, we found that treatment of both typical and blastoid-variant MCL cells with degrasyn in combination with bortezomib resulted in synergistic growth inhibition and apoptosis induction in vitro. The apoptosis in these cells was correlated with the downregulation of constitutive NF-κB and phosphorylated STAT3 activation, leading to the inhibition of c-Myc, cyclin D1, and bcl-2 protein expression and the upregulation of bax protein expression. In vivo, degrasyn and bortezomib interacted to synergistically prevent tumor development and prolong survival durations in a xenotransplant severe combined immunodeficient mouse model of MCL. These findings suggest that agents such as degrasyn that can pharmacologically target constitutively expressed NF-κB and STAT3 in MCL cells may be useful therapeutic agents for MCL when administered together with bortezomib. Mol Cancer Ther; 9(7); 2026–36. ©2010 AACR.
NICT-ATR Speech-to-Speech Translation System

This paper describes the latest version of speech-to-speech translation systems developed by the team of NICT-ATR for over twenty years. The system is now ready to be deployed for the travel domain. A new noise-suppression technique notably improves speech recognition performance. Corpus-based approaches of recognition, translation, and synthesis enable coverage of a wide variety of topics and portability to other languages.
An Ada-Random Forests based grammatical facial expressions recognition approach

The automatic recognition of facial expressions has a tremendous impact in many research fields, especially in the field of sign language since facial expressions contribute towards the formation of grammatical structure of the language that reduce the ambiguity of the sign language understanding. However, the automatic recognition of grammatical facial expressions is still a very challenging task due to the signer-based variation of the grammatical facial expressions, and the co-occurrence of manual and non-manual signs. This paper presents a novel Ada-Random Forests framework for recognizing the grammatical facial expressions used in Brazilian sign language. In this approach, an Ada-Boost feature selection algorithm is applied to select compact feature subsets from the numerous raw extracted features to reduce the computational time as well as to improve the recognition rate of the system; then, selected features are fed to a robust random forests classifier, given their capability to handle high-dimensional and unbalanced data, to recognize the grammatical facial expressions. The evaluation results of the experiments conducted on the first publicly available benchmark data set on Brazilian sign language indicate that the proposed technique improve the recognition metric by as much as 7.5% over the previously applied technique.
Sparse Solutions of Systems of Equations and Sparse Modeling of Signals and Images

We are interested in finding sparse solutions to systems of linear equations Ax = b, where A is underdetermined and fully-ranked, as presented in [1]. In this report we examine an implementation of the orthogonal matching pursuit (OMP) algorithm, an algorithm to find sparse solutions to equations like the one described above, and present a logic for its validation and corresponding validation results. We also test OMP in the study of the compression properties of A in the context of image processing. We make a small modification in the stopping criteria of OMP that results in better compression ratio vs image quality as measured by the structural similarity (SSIM) and mean structural similarity (MSSIM) indices.
Hypothesis __________________________________________________________________________________ Evolutionary Trace Analysis at the Ligand Binding Site of Laccase

Laccase belongs to the family of blue multi-copper oxidases and are capable of oxidizing a wide range of aromatic compounds. Laccases have industrial applications in paper pulping or bleaching and hydrocarbon bioremediation as a biocatalyst. We describe the design of a laccase with broader substrate spectrum in bioremediation. The application of evolutionary trace (ET) analysis of laccase at the ligand binding site for optimal design of the enzyme is described. In this attempt, class specific sites from ET analysis were mapped onto known crystal structure of laccase. The analysis revealed 162PHE as a critical residue in structure function relationship studies. Background: White rot fungus such as Trametes versicolor is a good candidate for biodegradation of aromatic compound in soil. Their oxidative capacity using enzymatic methods for the transformation of aromatic compounds occur at an extra-cellular environment and hence do not require internalization prior to degradation. Among the oxidative enzymes, laccase from Trametes versicolor has been reported to be involved in degradation. Laccases (E.C. 1.10.3.2) are members of the ubiquitous blue multi-copper oxidase family. They catalyze the oxidation of a range of organic substrates such as phenols, aromatic amines and non-phenolic compounds by reducing molecular oxygen to water [1].
Black Identifying and Validating Alternative Splicing Events

GeneChip Exon Arrays are powerful tools for the discovery and study of mRNA transcript diversity. For the first time, researchers will obtain approximately 1.4 million data points from each sample in a single experiment. This increased data density also poses a number of data analysis challenges, including management of a higher number of potential false positives from the much larger data set. In addition, exon arrays provide a new dimension of genomic information beyond classical gene expression results from microarrays—alternative splicing. For the analysis of alternative splicing, new algorithms will need to be developed and tested in various data sets. This is an active area of research and we anticipate that new developments and methods will continue to emerge with the increasing availability of sample data sets on exon arrays. In this Technical Note, we present practical recommendations for managing some of these challenges based on our experience at Affymetrix. A sample workflow operating mainly within Affymetrix Expression ConsoleTM Software and other GeneChip-compatibleTM software programs for exon array analysis is described in detail. Our experience shows that systematic filtering of the raw array results, as detailed here, is critical to the improvement of validation rate in the subsequent RT-PCR validation experiments. Most of the analysis strategies discussed in this Technical Note will be applicable to any statistical method developed for identifying alternative splicing events. nn nn GeneChip Exon Arrays
Outreach Schools: An Educational Innovation

To benefit those students who cannot or will not pursue their educations in traditional high schools, that is, to prevent their leaving before graduation or to facilitate their return if they do leave prematurely, educators continue to address the problem of providing alternate educational programs. This study of Outreach Schools, a current system of alternative education, was conducted through staff and student interviews, student questionnaires, school visits, and an exploration of related literature. The school philosophy is outlined, the teachers and students are described, the operation of the schools is explained, and a case is made for this type of educational alternative.
Security Use Cases

Although use cases are a popular modeling approach for engineering functional requirements, they are often misused when it comes to engineering security requirements because requirements engineers unnecessarily specify security architectural mechanisms instead of security requirements. After discussing the relationships between misuse cases, security use cases, and security mechanisms, this column provides examples and guidelines for properly specifying essential (i.e., requirements-level) security use cases.
Leuconostoc sp. Meningitis in a Patient Treated with Rituximab for Mantle Cell Lymphoma

We present a 64-year-old man who was treated with R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisolone) chemoimmunotherapy for mantle cell lymphoma and developed purulent meningitis, probably caused by Leuconostoc sp. The patient had severe hypogammaglobulinemia, which is a possible complication of rituximab therapy. To our knowledge and after reviewing the available medical literature, this is the first described case of purulent meningitis caused by Leuconostoc sp. in a patient with mantle cell lymphoma that appeared after treatment with the R-CHOP protocol. The diagnosis of purulent meningitis was based on clinical, laboratory and cytological cerebrospinal fluid findings, in addition to blood culture results in which we isolated Leuconostoc sp. The patient was treated with meropenem with full recovery.