Miracle-dz/UniFAR-FTUs huggingface dataset:
Word segmentation refinement by Wikipedia for textual entailment

Textual entailment in Chinese differs from the way handling English because of the lack of word delimiters and capitalization. Information from word segmentation and Wikipedia often plays an important role in textual entailment recognition. However, the inconsistency of boundaries of word segmentation and matched Wikipedia titles should be resolved first. This paper proposed 4 ways to incorporate Wikipedia title matching and word segmentation, experimented in several feature combinations. The best system redoes word segmentation after matching Wikipedia titles. The best feature combination for BC task uses content words and Wikipedia titles only, which achieves a macro-average F-measure of 67.33% and an accuracy of 68.9%. The best MC RITE system also achieves a macro-average F-measure of 46.11% and an accuracy of 58.34%. They beat all the runs in NTCIR-10 RITE-2 CT tasks.
Designing Creative Programing Experiences for 15 Years Old Students

It is well known in the computer science education community that is important to encourage students to acquire programming skills and become cre- ators and not only mere consumers. Different students have different needs and learning styles when introduced to programming and making activities, however it is challenging to accommodate all these needs while you design a workshop activity. In our approach we have designed and implemented a workshop pro- gram of 23 students' total, with the final goal of exploring and improving the design of appropriate workshops using the current learning environments. This paper presents an initial exploratory evaluation of a workshop program and the development of a set of guidelines for improving student experience. A set of best practices was developed through a focus group with experts using the tech- nique of affinity diagrams. The results should be useful for designers and re- searchers who work with design and evaluation of programming workshop pro- grams.
Parallel Niche Pareto AlineaGA – an Evolutionary Multiobjective approach on Multiple Sequence Alignment

Summary Multiple sequence alignment is one of the most recurrent assignments in Bioinformatics. This method allows organizing a set of molecular sequences in order to expose their similarities and their differences. Although exact methods exist for solving this problem, their use is limited by the computing demands which are necessary for exploring such a large and complex search space. Genetic Algorithms are adaptive search methods which perform well in large and complex spaces. Parallel Genetic Algorithms, not only increase the speed up of the search, but also improve its efficiency, presenting results that are better than those provided by the sum of several sequential Genetic Algorithms. Although these methods are often used to optimize a single objective, they can also be used in multidimensional domains, finding all possible tradeoffs among multiple conflicting objectives. Parallel AlineaGA is an Evolutionary Algorithm which uses a Parallel Genetic Algorithm for performing multiple sequence alignment. We now present the Parallel Niche Pareto AlineaGA, a multiobjective version of Parallel AlineaGA.We compare the performance of both versions using eight BAliBASE datasets. We also measure up the quality of the obtained solutions with the ones achieved by T-Coffee and ClustalW2, allowing us to observe that our algorithm reaches for better solutions in the majority of the datasets.
Multipoint Organizational Evolutionary Algorithm for Globally Minimizing Functions of Many Variables

In this paper, we design a variant of the organizational evolutionary algorithm (OEA), called the multipoint organizational evolutionary algorithm (mOEA), for global optimization of multimodal functions. Our objective is to apply crossover strategy of multiple points to enhance the OEA, so that the resulting algorithm can improve the precision of the solutions and have a fast convergence rate. In the mOEA, crossover among many leaders enables the diversity of the leader swarm to be preserved to discourage premature convergence. Another new organizational operator, the integrating operation replacing Annexing manipulation, guarantees members of each organization to converge to the leader fast and also have a good diversity due to mutation. Experiments on six complex optimization benchmark functions with 30 or 100 dimensions and very large numbers of local minima show that, comparing with the original OEA and CLPSO, mOEA effectively converges faster, results in better optima, is more robust.
Simultaneous Human Segmentation, Depth and Pose Estimation via Dual Decomposition

The tasks of stereo matching, segmentation, and human pose estimation have been popular in computer vision in recent years, but attempts to combine the three tasks have so far resulted in compromises: either using infra-red cameras, or a greatly simplified body model. We propose a framework for estimating a detailed human skeleton in 3D from a stereo pair of images. Within this framework, we define an energy function that incorporates the relationship between the segmentation results, the pose estimation results, and the disparity space image. Specifically, we codify the assertions that foreground pixels should relate to some body part, should correspond to a continuous surface in the disparity space image, and should be closer to the camera than the surrounding background pixels. Our energy function is NP-hard, however we show how to efficiently optimize a relaxation of it using dual decomposition. We show that applying this approach leads to improved results in all three tasks, and also introduce an extensive and challenging new dataset, which we use as a benchmark for evaluating 3D human pose estimation.
Traffic-Aware Multiple Regular Expression Matching Algorithm for Deep Packet Inspection

Deep packet inspection sometimes is called application level semantic detection, which is capable of examining the content of data packets in order to provide application-specific services and improve network security. Application traffic classification based on regular expressions is an essential step for deep packet inspection. However regular expression, especially multiple regular expression matching is known to require intensive system resources and is often a performance bottleneck. Currently, the DFAs of regular expression are constructed in the preprocessing stage and the context of network streams is excluded which leads to low throughputs. In this paper, we analyzed the application level protocols and found that the protocols are asymmetrically distributed and it is changing dynamically. From the protocol distribution characteristic, we proposed an adaptive multiple regular expression matching method for application traffic classification with deep packet inspection. The adaptive method, schedule the multiple DFAs through splay tree by matching probability other than linear scheduling in linked list, can adjust scheduling sequence according with the changing dynamic traffics. We evaluate the proposed method with the L7 rules; experiments proved that our method can improve the throughputs more than three times.
The cost of running uphill: linking organismal and muscle energy use in guinea fowl (Numida meleagris)

SUMMARY Uphill running requires more energy than level running at the same speed, largely due to the additional mechanical work of elevating the body weight. We explored the distribution of energy use among the leg muscles of guinea fowl running on the level and uphill using both organismal energy expenditure (oxygen consumption) and muscle blood flow measurements. We tested each bird under four conditions: (1) rest, (2) a moderate-speed level run at 1.5 m s–1, (3) an incline run at 1.5 m s–1 with a 15% gradient and (4) a fast level run at a speed eliciting the same metabolic rate as did running at a 15% gradient at 1.5 m s–1 (2.28–2.39 m s–1). The organismal energy expenditure increased by 30% between the moderate-speed level run and both the fast level run and the incline run, and was matched by a proportional increase in total blood flow to the leg muscles. We found that blood flow increased significantly to nearly all the leg muscles between the moderate-speed level run and the incline run. However, the increase in flow was distributed unevenly across the leg muscles, with just three muscles being responsible for over 50% of the total increase in blood flow during uphill running. Three muscles showed significant increases in blood flow with increased incline but not with an increase in speed. Increasing the volume of active muscle may explain why in a previous study a higher maximal rate of oxygen consumption was measured during uphill running. The majority of the increase in energy expenditure between level and incline running was used in stance-phase muscles. Proximal stance-phase extensor muscles with parallel fibers and short tendons, which have been considered particularly well suited for doing positive work on the center of mass, increased their mass-specific energy use during uphill running significantly more than pinnate stance-phase muscles. This finding provides some evidence for a division of labor among muscles used for mechanical work production based on their muscle–tendon architecture. Nevertheless, 33% of the total increase in energy use (40% of the increase in stance-phase energy use) during uphill running was provided by pinnate stance-phase muscles. Swing-phase muscles also increase their energy expenditure during uphill running, although to a lesser extent than that required by running faster on the level. These results suggest that neither muscle–tendon nor musculoskeletal architecture appear to greatly restrict the ability of muscles to do work during locomotor tasks such as uphill running, and that the added energy cost of running uphill is not solely due to lifting the body center of mass.
Optimal risk-sensitive control for bilinear stochastic systems

The optimal exponential-quadratic control problem is considered for stochastic Gaussian systems with polynomial bilinear drift terms and intensity parameters multiplying diffusion terms in the state equation. The closed-form optimal control algorithm is obtained using a quadratic value function as a solution to the corresponding Hamilton-Jacobi-Bellman equation. The performance of the obtained risk-sensitive regulator for stochastic bilinear polynomial systems is verified in a numerical example, through comparing the exponentialquadratic criteria values for the optimal risk-sensitive control and bilinear control algorithms. The simulation results reveal strong advantages in favor of the designed risk-sensitive algorithm in regard to the final criteria values for all values of the parameter ε.
ISOSPECTRAL PAIRS OF METRICS ON BALLS, SPHERES, AND OTHER MANIFOLDS WITH DIFFERENT LOCAL GEOMETRIES

The first isospectral pairs of metrics are constructed on the most simple simply connected domains, namely, on balls and spheres. This long-standing problem, concerning the existence of such pairs, has been solved by a new method called "anticommutator technique". Among the wide range of such pairs, the most striking examples are provided on the spheres S4k-1, where k > 3. One of these metrics is homogeneous (since it is the metric on the geodesic sphere of a 2-point homogeneous space), while the other is locally inhomogeneous. These examples demonstrate the surprising fact that no information about the isometries is encoded in the spectrum of the Laplacian acting on functions. In other words, the group of isometries, even the local homogeneity property, is lost to the nonaudible in the debate of audible versus nonaudible geometry. In this article we settle a long-standing and intensively studied problem of spectral geometry by constructing the first examples of nontrivial isospectral metrics on the simplest simply connected manifolds, namely, on balls and spheres. This result is achieved by a new isospectral construction technique called anticommutator technique. It provides a whole cornucopia of such examples, not just on balls and spheres, but on other types of manifolds too. The most striking examples are constructed on the geodesic spheres of the hyperbolic quaternionic 2-point homogeneous spaces. The induced metrics on these spheres are obviously homogeneous. While the metrics constructed isospectrally to these are locally inhomogeneous. This shows the weakness of the information about the local geometry encoded in the spectrum of Laplacian acting on functions.
The luminosity–metallicity relation in the local Universe from the 2dF Galaxy Redshift Survey

We investigate the Luminosity ‐ Metallicity (L Z) relation in the local universe (0 0.3) galaxies. Oxygen-to-hydrogen (O/H) abundance ratios are estimated using the ”strong-line” method, which relates the strength of following bright emission lines [O II] �3727, [O III] �5007, and H� (parametersR23 andO32)
Plaquage omnidirectionnel de textures provenant de séquences vidéo

Nous proposons dans cet article d’identifier clairement les problemes rencontres lorsque l’on veut effectuer un texturage omnidirectionnel d’un modele 3D. Nous proposons aussi des solutions a chacun de ces problemes. Une version anglaise, plus detaillee, se trouve en deuxieme partie.
Fast interprocedual alias analysis

We present a new algorithm for computing interprocedural aliases due to passing parameters by reference. This algorithm runs in O(<italic>N<supscrpt>2</supscrpt></italic>+<italic>NE</italic>) time and, when combined with algorithms for alias-free, flow-insensitive data-flow problems, yields algorithms for solution of the general flow-insensitive problems that also run in O(<italic>N<supscrpt>2</supscrpt></italic>+<italic>NE</italic>) time.
Some problems of directional sensor networks

Wireless sensor networks are often based on omni-sensing and communication models. In contrast, in this paper, we investigate sensor networks with directional sensing and communication capability. Due to the distinct characteristics and potential effects on coverage and connectivity of the network, novel analysis and solutions are demanded. Towards this end, this paper analyses deployment strategies for satisfying given coverage probability requirements with directional sensing models. Moreover, for sensors with directional communication model, we propose methods for checking and repairing the connectivity of the network. We design efficient protocols to implement our idea. A set of experiments are also performed to prove the effectiveness of our solution.
Comparison of electrophysiological effects of calcium channel blockers on cardiac repolarization

Dihydropyridine (DHP) calcium channel blockers (CCBs) have been widely used to treat of several cardiovascular diseases. An excessive shortening of action potential duration (APD) due to the reduction of Ca2+ channel current (ICa) might increase the risk of arrhythmia. In this study we investigated the electrophysiological effects of nicardipine (NIC), isradipine (ISR), and amlodipine (AML) on the cardiac APD in rabbit Purkinje fibers, voltage-gated K+ channel currents (IKr, IKs) and voltage-gated Na+ channel current (INa). The concentration-dependent inhibition of Ca2+ channel currents (ICa) was examined in rat cardiomyocytes; these CCBs have similar potency on ICa channel blocking with IC50 (the half-maximum inhibiting concentration) values of 0.142, 0.229, and 0.227 nM on NIC, ISR, and AML, respectively. However, ISR shortened both APD50 and APD90 already at 1 µM whereas NIC and AML shortened APD50 but not APD90 up to 30 µM. According to ion channel studies, NIC and AML concentration-dependently inhibited IKr and IKs while ISR had only partial inhibitory effects (<50% at 30 µM). Inhibition of INa was similarly observed in the three CCBs. Since the IKr and IKs mainly contribute to cardiac repolarization, their inhibition by NIC and AML could compensate for the AP shortening effects due to the block of ICa.
Deterministic procedural generation of mesh detail through gradient tiling

Modern virtual reality systems support scenery of both vast scale and intricate detail at levels beyond that which can be manually created by teams of human content creators. Scene geometry must instead be created through procedural geometry generation. Deterministic tiling strategies that synthesize content over unbounded regions are extended in this paper to resolve issues with structure at tile boundaries, and also achieve required level of detail. The process is demonstrated through its application to the real-time terrain synthesis domain. The synthesis process described retains properties of the content domain by directly placing tiles sampled from exemplar data. Inconsistencies at tile boundaries are resolved through a novel refinement involving the use of a gradient field representation for the tiles. The synthesis algorithm lays down multiple layers of tiles containing gradient components and the geometric structure is reconstructed from this gradient field. The reconstruction uses an efficient formulation of a run-time Poisson solver well suited to parallelization on the GPU. This approach reduces seams, recombines exemplar features to increase variety, and supports deterministic generation of localized regions on demand. The process is well suited to progressive refinement schemes with large tiles providing rapid detail amplification. This is validated in the case of terrain data by showing that this process is more effective at preserving drainage properties than other terrain synthesis approaches. Performance exceeds typical requirements, with the GPU based prototype capable of completely regenerating the entire visible region at interactive frame rates.
Bayesian approaches to acoustic modeling: a review

This paper focuses on applications of Bayesian approaches to acoustic modeling for speech recognition and related speech-processing applications. Bayesian approaches have been widely studied in the fields of statistics and machine learning, and one of their advantages is that their generalization capability is better than that of conventional approaches (e.g., maximum likelihood). On the other hand, since inference in Bayesian approaches involves integrals and expectations that are mathematically intractable in most cases and require heavy numerical computations, it is generally difficult to apply them to practical speech recognition problems. However, there have been many such attempts, and this paper aims to summarize these attempts to encourage further progress on Bayesian approaches in the speech-processing field. This paper describes various applications of Bayesian approaches to speech processing in terms of the four typical ways of approximating Bayesian inferences, i.e., maximum a posteriori approximation, model complexity control using a Bayesian information criterion based on asymptotic approximation, variational approximation, and Markov chain Monte Carlo-based sampling techniques.
Bootstrapping Safe AGI Goal Systems

The field of machine ethics seeks methods to ensure that future intelligent machines will act in ways beneficial to human beings. Machine ethics is relevant to a wide range of possible artificial agents, but becomes especially difficult and especially important when the agents in question have at least humanlevel intelligence. This paper describes a solution, originally proposed by Yudkowsky (2004), to the problem of what goals to give such agents: rather than attempt to explicitly program in any specific normative theory (a project which would face numerous philosophical and immediate ethical difficulties), we should implement a system to discover what goals we would, upon reflection, want such agents to have. We discuss the motivations for and details of this approach, comparing it to other suggested methods for creating 'artificial moral agents' (Wallach & Collin 2007), and describe underspecified and uncertain areas for further research.
Evidence for Persistence of Ectromelia Virus in Inbred Mice, Recrudescence Following Immunosuppression and Transmission to Naïve Mice

Orthopoxviruses (OPV), including variola, vaccinia, monkeypox, cowpox and ectromelia viruses cause acute infections in their hosts. With the exception of variola virus (VARV), the etiological agent of smallpox, other OPV have been reported to persist in a variety of animal species following natural or experimental infection. Despite the implications and significance for the ecology and epidemiology of diseases these viruses cause, those reports have never been thoroughly investigated. We used the mouse pathogen ectromelia virus (ECTV), the agent of mousepox and a close relative of VARV to investigate virus persistence in inbred mice. We provide evidence that ECTV causes a persistent infection in some susceptible strains of mice in which low levels of virus genomes were detected in various tissues late in infection. The bone marrow (BM) and blood appeared to be key sites of persistence. Contemporaneous with virus persistence, antiviral CD8 T cell responses were demonstrable over the entire 25-week study period, with a change in the immunodominance hierarchy evident during the first 3 weeks. Some virus-encoded host response modifiers were found to modulate virus persistence whereas host genes encoded by the NKC and MHC class I reduced the potential for persistence. When susceptible strains of mice that had apparently recovered from infection were subjected to sustained immunosuppression with cyclophosphamide (CTX), animals succumbed to mousepox with high titers of infectious virus in various organs. CTX treated index mice transmitted virus to, and caused disease in, co-housed naïve mice. The most surprising but significant finding was that immunosuppression of disease-resistant C57BL/6 mice several weeks after recovery from primary infection generated high titers of virus in multiple tissues. Resistant mice showed no evidence of a persistent infection. This is the strongest evidence that ECTV can persist in inbred mice, regardless of their resistance status.
Hardware implementation of fast-sequency ordered complex hadamard transform

In this article hardware implementation of Sequency ordered Complex Hadamard Transform (SCHT) on FPGA is presented. SCHT is quite similar to Discrete Fourier Transform (DFT) but it consumes less computational time. DFT is replaceable by SCHT in several applications such as Communication, Spectrum analysis and estimation, Signal processing and image watermarking. The 8-point radix-2 fast SCHT is evaluated on FPGA to minimize its computational time, besides that certain parameters of fast SCHT matrices are analysed. Finally SCHT hardware implemented results and MATLAB simulated results are compared at the cost of time to verify the effectiveness of the SCHT on FPGA.
A graph matching based integrated scheduling framework for clustered VLIW processors

Scheduling for clustered architectures involves spatial concerns (where to schedule) as well as temporal concerns (when to schedule) and various clustered VLIW configurations, connectivity types, and inter-cluster communication models present different performance trade-offs to a scheduler. The scheduler is responsible for resolving the conflicting requirements of exploiting the parallelism offered by the hardware and limiting the communication among clusters to achieve better performance without stretching the overall schedule. This paper proposes a generic graph matching based framework that resolves the phase-ordering and fixedordering problems associated with scheduling on a clustered VLIW processor by simultaneously considering various scheduling alternatives of instructions. We observe approximately 16% and 28% improvement in the performance over an earlier integrated scheme and a phase-decoupled scheme respectively without extra code size penalty.