Miracle-dz/UniFAR-FTUs huggingface dataset:
Disruption-Free Green Traffic Engineering with NotVia Fast Reroute

We introduce a practical green traffic engineering technique in fast reroute (FRR) enabled IP networks which is able to avoid transient routing disruption caused by sleeping-mode reconfigurations during runtime. Following the description on the time-driven "delegate before sleep" operations based on the NotVia FRR platform, we also propose a simple optimization algorithm for selecting sleeping links and determining the sleeping duration according to dynamic traffic behaviors. The aim of the approach is to avoid traffic congestion due to reduced network capabilities during off-peak operation time.
Flow cytometric analysis and isolation of permeabilized dopamine nerve terminals from rat striatum

Fluorescence-activated cell sorting (FACS) was used to identify and isolate permeabilized dopaminergic nerve terminals from rat striatum based on immunofluorescent labeling of tyrosine hydroxylase (TH). Striatal synaptosomes were permeabilized by fixation with modified Zamboni fluid. A highly fluorescent subpopulation of particles was detected by FACS following sequential incubation with a monoclonal antibody to TH (LNC 1) and a fluorescein-conjugated secondary antibody. After correcting for nonsynaptosomal particles present in the synaptosomal fraction, analysis of these data suggested that approximately 12–15% of striatal synaptosomes were dopaminergic, consistent with previous estimates. Specific labelling by LNC 1 was decreased if synaptosomes were prepared from rats that had received intraventricular injections of 6-hydroxydopamine. The decrease in labeling was highly correlated with the extent of the lesion as determined by measurement of striatal dopamine levels, suggesting that LNC 1-labeled synaptosomes were derived from nigrostriatal dopamine terminals. In order to verify that LNC 1-labeled synaptosomes were enriched for TH, equal numbers of labeled and control synaptosomes were isolated by FACS and analyzed by SDS-PAGE. LNC 1-labeled synaptosomes were shown by Western blot techniques to be enriched 6-fold for TH compared with control synaptosomes, suggesting that the labeled population consisted almost entirely of dopaminergic synaptosomes.
The Ambiguous-Race Face Illusion

We discovered an interesting perceptual effect while developing a stimulus set to examine the cross-race face-recognition deficit. The cross-race effect occurs when people of one race have greater difficulty recognizing individuals of another race (MacLin and Malpass 2001; Malpass and Kravitz 1969; for meta-analytic review see Meissner and Brigham 2001). One problem with research on the cross-race effect is that a decrement in recognition performance for other-race faces can be attributed to differential experience with members of the various racial stimulus classes due to social contact (Malpass and Kravitz 1969) or due to perceptual expertise (O'Toole et al 1995). We originally sought to develop a stimulus set of same-race and other-race faces that were virtually identical in respect to facial features and facial configurations, yet would be perceived by observers as either Hispanic or Black. (1) If the cross-race effect persisted with virtually identical faces, it would be difficult to attribute the crossrace effect to a lack of exposure or expertise with the stimulus class, thus requiring a different hypothesis to explain the cross-race effect. Faces ambiguous to race were constructed with a Black/Hispanic overlap with the aid of a computerized facial composite program (Faces 3.
Oropharyngeal Dysphagia in Dermatomyositis: Associations with Clinical and Laboratory Features Including Autoantibodies

Objective Dysphagia develops with low frequency in patients with dermatomyositis. Our objective was to determine the clinical and laboratory features that can estimate the development of dysphagia in dermatomyositis. Methods This study included 92 Japanese patients with adult-onset dermatomyositis. The associations between dysphagia and clinical and laboratory features including disease-specific autoantibodies determined by immunoprecipitation assays were analyzed. Results Videofluoroscopy swallow study (VFSS) was performed for all patients with clinical dysphagia (n = 13, 14.1%) but not for patients without clinical dysphagia. Typical findings of dysphagia (pharyngeal pooling, n = 11 and/or nasal regurgitation, n = 4) was detected by VFSS in all patients with clinical dysphagia. Eleven patients with dysphagia (84.6%) had anti-transcription intermediary factor 1γ (TIF-1γ) antibody. By univariate analysis, the average age and the male to female ratio, internal malignancy, and anti-TIF-1γ antibody were significantly higher and the frequency of interstitial lung diseases and manual muscle testing (MMT) scores of sternomastoid and dertoid muscles were significantly lower in patients with dysphagia than in patients without dysphagia. Among patients with anti-TIF-1γ antibody, the mean age, the ratios of male to female and internal malignancy were significantly higher and mean MMT scores of sternomastoid muscle were significantly lower in patients with dysphagia compared with patients without dysphagia. By multivariable analysis, the risk of dysphagia was strongly associated with the existence of internal malignancy and ant-TIF-1γ antibody and was also associated with reduced scores of manual muscle test of sternomastoid muscle. Dysphagia was markedly improved after the treatment against myositis in all 13 patients. Conclusion These findings indicate that dysphagia can develop frequently in patients with internal malignancy, anti-TIF-1γ antibody, or severe muscle weakness of sternomastoid muscle.
Questioning the reliability of estimates of enzyme inhibitor constant: Case of competitive inhibition

Reliability of kinetic parameters are crucial in understanding enzyme kinetics within cellular system. The present study suggests a few cautions that need introspection for estimation of parameters like K(M), V(max) and K(I) using Lineweaver-Burk plots. The quality of IC(50) too needs a thorough reinvestigation because of its direct link with K(I) and K(M) values. Inhibition kinetics under both steady-state and non-steady-state conditions are studied and errors in estimated parameters are compared against actual values to settle the question of their adequacy.
A Biologically Inspired Filter For Image Restoration

Digital image restoration is a field of engineering that studies methods used to recover original scene from the degraded images and observations. Techniques used for image restoration are oriented towards modeling the degradations, usually blur and noise and applying various filters to obtain an approximation of the original scene. In this paper genetic algorithms based filter which uses the concept of Weighted Order Statistics filter and Darwin's theory of evolution for achieving various generations of restored output is proposed. Once the initial target image is obtained, the GA's can be used to restore the images which are affected by different degradations levels without having any prior information about the blurring model and noise type. The results in this paper also point out that this method can be effectively used in blind restoration problems.
Adaptive Planification in Active 3 D Object Recognition for Many Classes of Objects

This paper focuses on active 3D object recognition by an autonomous visual agent in an unknown environment. In this problem, the central issue concerns the choice of the next viewpoint in the dynamical exploration of the object given the information collected until the present state of the agent. Numerous exploration strategies have been proposed and they were shown to outperform random viewpoint planification. Some are based on the maximization of an entropy measure which accounts for the dissimilarity between objects as in [3, 1], or they attempt to find the viewpoint the most favorable in terms of discrimination ability [4]. An agent-based approach was also proposed in the context of reinforcement learning framework [2]. The latter approach accounts for the interaction between the agent and the environment through the update of a planning function. However, these strategies are not robust with respect to the number of classes objects and they may even turn to be infeasible when there are many distinct classes. In the present paper, we propose to unify both approaches in order to deal with a very large number of classes of objects. We define a planning function based on an entropy measure which is adaptive in two senses: (i) it takes into account the knowledge acquired by the agent until its present state, and (ii) it progressively filters the classes with high confidence. We present simulation results for our adaptive exploration strategy on a car image database. These results illustrate the impact on performance with respect to both the number of classes and the duration of the exploration process.
Visualized Classification of Multiple Sample Types

The goal of the knowledge discovery and data mining is to extract the useful knowledge from the given data. Visualization enables us to find structures, features, patterns, and relationships in a dataset by presenting the data in various graphical forms with possible interactions. Recently, DNA microarray technology provides a board snapshot of the state of the cell by measuring the expression levels of thousands of genes simultaneously. Such information can thus be used to analyze different samples by the gene expression profiles. Last few years saw many cluster analysis and classsification methods extensively be applied to capture the similarity pattern of gene expressions. A novel interactive visualization approach, VizCluster, was presented and applied to classify samples of two types. It combines the merits of both high dimensional projection scatter plot and parallel coordinate plot, taking advantage of graphical visualization methods to reveal the underlining data patterns. In this paper, we expand VizCluster to classify multiple types of samples. First, we identify genes which are differentially expressed across the sample groups. Then we apply VizCluster to build classifiers based on those genes. Finally, classifiers were evaluated by either hold out or cross validation. Five gene expression data sets were used to illustrate the approach. Experimental performance demonstrated the feasibility and usefulness of this approach.
Intercontinental multimodal tele-cooperation using a humanoid robot

In multimodal tele-cooperation as considered in this paper two humans in distant locations jointly perform a task requiring multimodal including haptic feedback. One human operator teleoperates a remotely placed humanoid robot which is collocated with the human cooperator. Time delay in the communication channel as destabilizing factor is one of the multiple challenges associated with such a tele-cooperation setup. In this paper we employ a control architecture with force-position exchange accounting for the admittance type of the haptic input device and the telerobot, which both are position-based admittance controlled. Llewellynpsilas stability criteria are employed for the parameter tuning of the virtual impedances in the presence of time delay. The control strategy is successfully validated in an intercontinental tele-cooperation experiment with the humanoid telerobot HRP-2 located in Japan/Tsukuba and a multimodal human-system-interface located in Germany/Munich, see also the corresponding video submission. The proposed setup gives rise to a large number of exciting new research questions to be addressed in the future.
Design and Effectiveness Analysis of a Personalized Information Resource Service System

According to the user's interest model and the characteristics of information resources, personalized recommendation strategy is used to select the appropriate information resources from the database for users. The system provides feedback to the guiding teacher on the student's learning experiences and learning diary. Also, a customer satisfaction evaluation model of the system has been constructed and the investigation has been made. The results of the investigation demonstrate that most users are satisfied with the use of a personalized information resource services system for assisting their graduation design.
Improving the Peer Assessment Experience on MOOC Platforms

Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.
Analyzing the Logic Behavior of Digital CMOS Circuits in Presence of Simultaneous Switching Noise

This paper analyzes the logic errors in digital circuits due to the presence of Simultaneous Switching Noise (SSN). It is demonstrated that 2 conditions must be fulfilled in order to guarantee the correct logic behaviour of a digital circuits. The first condition called ‘Minimum Switch Condition' is proved to be fulfilled whatever the amount of SSN in the power and ground lines. The second condition called ‘Signal Coherence Condition' is proved to be fulfilled within power coherent logic blocks. However the interface between non-coherent logic blocks may originate logic dysfunction
Performance modeling for power consumption reduction on SCC

As power is becoming one of the biggest challenge in high performance computing, we are proposing a performance model on the Single-chip Cloud Computer in order to predict both power consumption and runtime of regular codes. This model takes into account the frequency at which the cores of the SCC chip operate. Thus, we can predict the execution time and power needed to run the code for each available frequency. This allows to choose the best frequency to optimize several metrics such as power efficiency or minimizing power consumption, based on the needs of the application. Our model only needs some parameters that are code dependent. These parameters can be found through static code analysis. We validated our model by showing that it can predict performance and find the optimal frequency divisor to optimize energy efficiency on several dense linear algebra codes.
ERF 2011-135 GEOMETRIC OPTIMISATION OF A GURNEY FLAP HINGE-LESS DEPLOYMENT SYSTEM FOR A HELICOPTER MODEL BLADE

Following a comparative study on shape morphing and adaptive systems to improve rotorcraft efficiency, the Green Rotorcraft consortium has selected the Gurney flap technology as demonstrator of a smart adaptive rotorblade within the Clean Sky Joint Technology Initiative [1]. The aim of such a system is to actively increase helicopter overall performance by improving lift and alleviating static and dynamic stall on the retreating side of the helicopter [2, 3]. The Gurney flap technology will be subjected to various tests, prior to manufacturing a full-scale demonstrator. Along with wind tunnel and whirl tower tests on full blade sections, a reduced-scale blade is required to be tested on a rotary support in a wind tunnel. The aim is to have a fully operational mechanism in a 1/8th-scale blade. A specific system needs to be designed for this smaller model blade. The specifications for the model blade mechanism are more challenging compared to the full model blade. The blade tip speed must remain the same between the two blades. Therefore, the model blade rotation speed and centrifugal loads greatly increase. Piezoelectric patch actuators combined with flexible beams are chosen to design a fast and robust mechanism, which would fit inside the model blade and support the large centrifugal loads. A mechanism is modeled using Finite Element Analysis tools and its geometry is optimised using a surrogate optimisation to maximise displacement and force. The optimised geometry has a Z-shape profile and maximise displacement and force. The force generated is sufficient to counter directly the force of the airflow on the flap. However, the displacement and the mechanical work are not large enough to deploy directly the Gurney flap as a conventional flap. The deployment time remains insufficient as well. Building on these results, refined geometries are under investigation using the same optimisation process. INTRODUCTION Shape morphing and adaptive systems appear to be promising technologies for improving rotorcraft performances and efficiency [3–6]. The Green Rotorcraft Consortium have reviewed active concepts in the scope of the European Clean Sky Joint Technology Initiative to improve helicopter transportation on the following aspects: fuel consumption and performances, active vibration control and active noise control [7]. The Gurney flap technology was selected as a demonstrator of a smart adaptive rotorblade [1]. The Gurney flap consists in a small flap, which length measures typically 2% of the chord length, placed at of the rotorblade’s trailing edge as shown in Figure 1. It improves the lift of the blade at a small drag penalty. Overall, the lift over drag coefficient increases over a large range of angles of attacks [2, 3, 8]. Moreover, the Gurney flap alleviates the static and dynamic stall of the blade [9]. Gurney flap Chord line Chord length Figure 1: Sketch of a profile with a 2% long gurney flap at the trailing edge.
Pure gauge configurations and tachyon solutions to string field theories equations of motion

In construction of analytical solutions to open string field theories pure gauge configurations parameterized by wedge states play an essential role. These pure gauge configurations are constructed as perturbation expansions and to guaranty that these configurations are asymptotical solutions to equations of motion one needs to study convergence of the perturbation expansions. We demonstrate that for the large parameter of the perturbation expansion these pure gauge truncated configurations give divergent contributions to the equation of motion on the subspace of the wedge states. We perform this demonstration numerically for the pure gauge configurations related to tachyon solutions for the bosonic and NS fermionic SFT. By the numerical calculations we also show that the perturbation expansions are cured by adding extra terms. These terms are nothing but the terms necessary to make valued the Sen conjectures.
Comparative Study of Sign Language Recognition Systems

- Sign Language (SL) is the communication method for deaf people. But these sign languages are not standard & universal. The grammar differs from country to country. As the sign language is the only method for deaf community to communicate with normal people, we need Sign Language Translators (SLT). The basic automatic SLT uses two approaches. First one is using the electronic data gloves. These gloves have inbuilt sensors & it is worn by the signer to detect hand posture. But these gloves are having high cost. So, visual approach is most suitable & widely used. Here a camera is used to capture images of signer & then image processing is carried out to perform recognition. For the vision based Sign Language Recognition (SLR), various methods are available. Three such methods are discussed & compared in this paper.
Efficient complex matrix multiplication on the Synergistic Processing Element of the Cell processor

In order to implement a complete Fast Multipole Method on the Cell processor, we need an efficient complex matrix multiplication on each Synergistic Processing Element (SPE) of the Cell processor. Since the last IBM SDK does not provide such routine, we build our own one in single precision with C programming. We show that the complex matrix multiplication requires a specific computation scheme for the micro-kernel running on the SPE, and that a 32×32 tile is appropriate for close to peak performance computation as well as for communication overlapping. Our micro-kernel delivers 23.74 Gflop/s, which is 92.7% of the SPE peak performance, and we obtain up to 23.65 Gflop/s for one complete complex matrix product on one SPE, and up to 378.36 Gflop/s for 16 products on 16 SPEs.
From Paragraphs to Vectors and Back Again

I investigate some methods of encoding text into vectors and decoding these vector representations. The purpose of decoding vector representations is two fold. Firstly, I could apply unsupervised learning algorithms to the paragraph vectors to find significant ”new” vectors and decode them into paragraphs of text. Effectively, I could process text and generate ”new” ideas. Secondly, I could decipher the purpose of each component of a paragraph vector by modifying its value and examining the effect on the underlying text.
Targeting your audience: wildlife value orientations and the relevance of messages about bear safety

ABSTRACT While there is an assumption that wildlife value orientations can be useful in strategic communication, few studies have empirically explored this topic. This article used the concept of wildlife value orientations to understand how to increase the motivation of people to process information about wildlife in the context of persuasive communication. A confirmatory factor analysis was used to identify mutualism and domination wildlife value orientations. From the wildlife value orientations, crosstabs were used to create a typology with four discreet segments: mutualists, pluralists, traditionalists, and distanced. A series of ANOVAs examined how important different messages about bear safety were to the typology segments. Results indicated that message relevancy differs among wildlife value orientations. Managers can use this information to help frame their communications about wildlife-related issues. Future research should continue to explore the impact of this value-framing approach to other persuasive communication concepts, like attitudes and behaviors.
Detecting Common Interest Kernels in Large Social Networks

In general, users may influence each other by their activities in social networks. It is interesting to explore hidden relationships of users based on their social activities. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a dataset from Epinions, which demonstrates that our method achieves 4\%-11.8\% accuracy improvement over the state of the art method.
Uniform Random Number Generation From Markov Chains: Non-Asymptotic and Asymptotic Analyses

In this paper, we derive non-asymptotic achievability and converse bounds on the random number generation with/without side-information. Our bounds are efficiently computable in the sense that the computational complexity does not depend on the block length. We also characterize the asymptotic behaviors of the large deviation regime and the moderate deviation regime by using our bounds, which implies that our bounds are asymptotically tight in those regimes. We also show the second-order rates of those problems, and derive single letter forms of the variances characterizing the second-order rates. Furthermore, we address the relative entropy rate and the modified mutual information rate for these problems.