Miracle-dz/UniFAR-FTUs huggingface dataset:
VSim: Simulating multi-server setups at near native hardware speed

Simulating contemporary computer systems is a challenging endeavor, especially when it comes to simulating high-end setups involving multiple servers. The simulation environment needs to run complete software stacks, including operating systems, middleware, and application software, and it needs to simulate network and disk activity next to CPU performance. In addition, it needs the ability to scale out to a large number of server nodes while attaining good accuracy and reasonable simulation speeds. This paper presents VSim, a novel simulation methodology for multi-server systems. VSim leverages virtualization technology for simulating a target system on a host system. VSim controls CPU, network and disk performance on the host, and it gives the illusion to the software stack to run on a target system through time dilation. VSim can simulate multiple targets per host, and it employs a distributed simulation scheme across multiple hosts for simulations at scale. Our experimental results demonstrate VSim's accuracy: typical errors are below 6% for CPU, disk, and network performance. Real-life workloads involving the Lucene search engine and the Olio Web 2.0 benchmark illustrate VSim's utility and accuracy (average error of 3.2%). Our current setup can simulate up to five target servers per host, and we provide a Hadoop workload case study in which we simulate 25 servers. These simulation results are obtained at a simulation slowdown of one order of magnitude compared to native hardware execution.
A Random Membership Sampler Based on Guided Random Walks

It is expensive to maintain up-to-date global membership information in large-scale, dynamic distributed systems. Alternatively, random membership sampling [1, 2, 3, 4] provides each node in the system a small, random partial view of the global membership list. Systems supported by such partial views can achieve performance comparable to those using complete global information, but at a much lower maintenance cost. Consequently, random membership sampling has been widely used as a key building block for large-scale distributed systems. However, existing scalable random membership management techniques cannot achieve arbitrary desired node sampling distributions on arbitrary network topologies. Based on our algorithm proposed in [6], we implemented a random membership sampler using guided random walks. Specifically, each node issues random walkers that travel and gather node information to achieve arbitrary desired sampling distribution, such as uniform sampling, load-biased sampling, or distance-based sampling. The random walkers are configured based on the Metropolis algorithm [5] to ensure guaranteed convergence to targeted node sampling distributions. Each step of the walk is made only with the information about the current residing node and its direct neighbors in the network. The issuing, forwarding, fault tolerance, and corresponding information updates of random walks are handled by an event-driven daemon running at each node. These daemons can be easily incorporated into existing distributed systems to provide the service of random membership sampling at desired distributions. In the demo, we plan to show the working mechanism of our random membership sampler deployed on the Planetlab Internet overlay testbed. We will explain the benefits of building a variety of distributed applications on our membership sampler. For example, randomized network topology construction can be supported by using our maintained random membership subset as a candidate pool of link targets. As another example, dynamic load balancing can also benefit because global hot spots (heavily loaded nodes) are likely to be discovered in load-biased random membership subsets. Furthermore, gossip-based broadcasting applications rely on an underlying mechanism to select nodes with certain distance-based probability distributions. We will perform live demonstration of our random walk samplers converging to desired membership sampling distribution. The convergence rate depends on the underlying topology and the targeted sampling probability distribution. Less regular network topologies and more skewed sampling distributions tend to require longer convergence time. 0% 2% 4% 6% 12.7%
A framework for the delivery of MPEG-4 interactive content over QoS aware IP networks

This paper presents an end-to-end application and network framework for delivering multimedia services over QoS aware IP networks as this is implemented within the IST OPENISE project. Several interactive MPEG-4 applications addressing the fields of tele-learning, conferencing and interactive TV have been classified according to their content and QoS requirements. The profile of the traffic that is generated by this set of applications has been clearly identified by using specially implemented traffic analysis tools. The diverse QoS requirements have been carefully mapped to network parameters. The paper reports on the performance capabilities of several packet-scheduling schemes and demonstrates their merits and applicability in delivering time-critical multimedia content.
Influence of HAART on Alternative Reading Frame Immune Responses over the Course of HIV-1 Infection

Background Translational errors can result in bypassing of the main viral protein reading frames and the production of alternate reading frame (ARF) or cryptic peptides. Within HIV, there are many such ARFs in both sense and the antisense directions of transcription. These ARFs have the potential to generate immunogenic peptides called cryptic epitopes (CE). Both antiretroviral drug therapy and the immune system exert a mutational pressure on HIV-1. Immune pressure exerted by ARF CD8+ T cells on the virus has already been observed in vitro. HAART has also been described to select HIV-1 variants for drug escape mutations. Since the mutational pressure exerted on one location of the HIV-1 genome can potentially affect the 3 reading frames, we hypothesized that ARF responses would be affected by this drug pressure in vivo. Methodology/Principal findings In this study we identified new ARFs derived from sense and antisense transcription of HIV-1. Many of these ARFs are detectable in circulating viral proteins. They are predominantly found in the HIV-1 env nucleotide region. We measured T cell responses to 199 HIV-1 CE encoded within 13 sense and 34 antisense HIV-1 ARFs. We were able to observe that these ARF responses are more frequent and of greater magnitude in chronically infected individuals compared to acutely infected patients, and in patients on HAART, the breadth of ARF responses increased. Conclusions/Significance These results have implications for vaccine design and unveil the existence of potential new epitopes that could be included as vaccine targets.
CHAOS AND SPIKE PATTERNS IN NEOCORTICAL COMPUTATION

From simulations relying on detailed physiological data, cortical layer IV recurrent network topology and small thalamic input currents, a novel synchronization paradigm emerges. Coarse synchronization, where small temporal variations due to individual characteristics of neurons are still allowed, is mediated by the bursting of intrinsically non-bursting spiny stellate and basket neurons. Using advanced methods of noise removal, we concluded that the collective behavior is of low-dimensional chaotic nature. The model observations are compared with data from anesthetized cats, where three fundamental groups of neuronal firing are distinguished. Using variable thalamic input currents, the characteristic in vivo behaviors and statistical properties are reproduced. Model and experimental data lead us to the conclusion that a large group of neurons fire in terms of patterns which may have a significance in information transfer in the brain.
Two-band amplitude scale estimation for quantization-based watermarking

Quantization-based watermarking schemes comprise a class of watermarking schemes that achieves channel capacity in terms of additive noise attacks. Unfortunately, quantization-based watermarking schemes are not robust against linear time invariant (LTI) filtering attacks. In this paper we concentrate on amplitude scaling of a multi-band system. First we derive the probability density function (PDF) of the attacked data. Second, using a simplified approximation of the PDF model, we derive a maximum likelihood (ML) procedure for estimating two-band amplitude scaling factor. Finally, experiments are performed with real audio signals showing the good performance of the proposed estimation technique under realistic conditions.
Sequential and compartmentalized action of Rabs, SNAREs, and MAL in the apical delivery of fusiform vesicles in urothelial umbrella cells

As major urothelial differentiation products, uroplakins are targeted to the apical surface of umbrella cells. Via the sequential actions of Rabs 11, 8, and 27b and their effectors, uroplakin vesicles are transported to a subapical zone above a K20 network and fuse, via a SNARE-mediated and MAL-facilitated step, with the urothelial apical membrane.
Passivity Analysis for Discrete-Time Stochastic Markovian Jump Neural Networks With Mixed Time Delays

In this paper, passivity analysis is conducted for discrete-time stochastic neural networks with both Markovian jumping parameters and mixed time delays. The mixed time delays consist of both discrete and distributed delays. The Markov chain in the underlying neural networks is finite piecewise homogeneous. By introducing a Lyapunov functional that accounts for the mixed time delays, a delay-dependent passivity condition is derived in terms of the linear matrix inequality approach. The case of Markov chain with partially unknown transition probabilities is also considered. All the results presented depend upon not only discrete delay but also distributed delay. A numerical example is included to demonstrate the effectiveness of the proposed methods.
Upper Body Pose Estimation with Temporal Sequential Forests

Our objective is to efficiently and accurately estimate human upper body pose in gesture videos. To this end, we build on the recent successful applications of random forests (RF) classifiers and regressors, and develop a pose estimation model with the following novelties: (i) the joints are estimated sequentially, taking account of the human kinematic chain. This means that we don't have to make the simplifying assumption of most previous RF methods - that the joints are estimated independently; (ii) by combining both classifiers (as a mixture of experts) and regressors, we show that the learning problem is tractable and that more context can be taken into account; and (iii) dense optical flow is used to align multiple expert joint position proposals from nearby frames, and thereby improve the robustness of the estimates. The resulting method is computationally efficient and can overcome a number of the errors (e.g. confusing left/right hands) made by RF pose estimators that infer their locations independently. We show that we improve over the state of the art on upper body pose estimation for two public datasets: the BBC TV Signing dataset and the ChaLearn Gesture Recognition dataset.
Intelligent robotics in 3D simulation - An eRobotics approach

Robot manipulators are increasingly employed in dynamic and uncertain environments. Therefore, weak and strong physical interactions with the surrounding operational environment can occur. Managing the complexity related to this trend requires simulation capabilities going far beyond traditional off-line motion planning of robots in free-space. This paper presents a dynamic simulation that addresses this issue. The simulator conveys insight into the accommodation of external forces during physical interaction, since the simulated robots are endowed with force-sensitive and compliance control capabilities. Further, a symbiotic simulation of compliance control enables physical interaction between a human operator and a real position-controlled robot. Our approach builds upon a comprehensive, holistic and versatile coupling of modeling paradigms. It leverages the significance of simulation outcomes by enriching the simulator with realistic robot control techniques. It deepens the understanding of ongoing processes by allowing an overall and customizable view on the robot down to actuators. The results highlight the effectiveness of the eRobotics methodology, which represents the foundation this work is built upon.
Intravenous administration of piceatannol, an arginase inhibitor, improves endothelial dysfunction in aged mice

Advanced age is one of the risk factors for vascular diseases that are mainly caused by impaired nitric oxide (NO) production. It has been demonstrated that endothelial arginase constrains the activity of endothelial nitric oxide synthase (eNOS) and limits NO generation. Hence, arginase inhibition is suggested to be vasoprotective in aging. In this study, we examined the effects of intravenous injection of Piceatannol, an arginase inhibitor, on aged mice. Our results show that Piceatannol administration reduced the blood pressure in aged mice by inhibiting arginase activity, which was associated with NO production and reactive oxygen species generation. In addition, Piceatannol administration recovered Ca2+/calmodulin-dependent protein kinase II phosphorylation, eNOS phosphorylation and eNOS dimer stability in the aged mice. The improved NO signaling was shown to be effective in attenuating the phenylephrine-dependent contractile response and in enhancing the acetylcholine-dependent vasorelaxation response in aortic rings from the aged mice. These data suggest Piceatannol as a potential treatment for vascular disease.
Nationwide Investigation of the Pyrethroid Susceptibility of Mosquito Larvae Collected from Used Tires in Vietnam

Pyrethroid resistance is envisioned to be a major problem for the vector control program since, at present, there are no suitable chemical substitutes for pyrethroids. Cross-resistance to knockdown agents, which are mainly used in mosquito coils and related products as spatial repellents, is the most serious concern. Since cross-resistance is a global phenomenon, we have started to monitor the distribution of mosquito resistance to pyrethroids. The first pilot study was carried out in Vietnam. We periodically drove along the national road from the north end to the Mekong Delta in Vietnam and collected mosquito larvae from used tires. Simplified susceptibility tests were performed using the fourth instar larvae of Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus. Compared with the other species, Ae. aegypti demonstrated the most prominent reduction in susceptibility. For Ae. aegypti, significant increases in the susceptibility indices with a decrease in the latitude of collection points were observed, indicating that the susceptibility of Ae. aegypti against d-allethrin was lower in the southern part, including mountainous areas, as compared to that in the northern part of Vietnam. There was a significant correlation between the susceptibility indices in Ae. aegypti and the sum of annual pyrethroid use for malaria control (1998–2002). This might explain that the use of pyrethroids as residual treatment inside houses and pyrethroid-impregnated bed nets for malaria control is attributable to low pyrethroid susceptibility in Ae. aegypti. Such insecticide treatment appeared to have been intensively administered in the interior and along the periphery of human habitation areas where, incidentally, the breeding and resting sites of Ae. aegypti are located. This might account for the strong selection pressure toward Ae. aegypti and not Ae. albopictus.
MR imaging methods for assessing fetal brain development

Fetal magnetic resonance imaging provides an ideal tool for investigating growth and development of the brain in vivo. Current imaging methods have been hampered by fetal motion but recent advances in image acquisition can produce high signal to noise, high resolution 3‐dimensional datasets suitable for objective quantification by state of the art post acquisition computer programs. Continuing development of imaging techniques will allow a unique insight into the developing brain, more specifically process of cell migration, axonal pathway formation, and cortical maturation. Accurate quantification of these developmental processes in the normal fetus will allow us to identify subtle deviations from normal during the second and third trimester of pregnancy either in the compromised fetus or in infants born prematurely. © 2008 Wiley Periodicals, Inc. Develop Neurobiol, 2008
Digital Games as a Context for Children's Cognitive Development: Research Recommendations and Policy Considerations

We document the need to examine digital game play and app use as a context for cognitive development, particularly during middle childhood. We highlight this developmental period as 6through 12year olds comprise a large swath of the preadult population that plays and uses these media forms. Surprisingly, this age range remains understudied with regard to the impact of their interactive media use as compared to young children and adolescents. This gap in knowledge about middle childhood may reflect strong and widely held concerns about the effects of digital games and apps before and after this period. These concerns include concurrent and subsequent influences of game use on very young children’s and adolescents’ cognitive and socioemotional functioning. We highlight here what is currently known about the impact of media on young children and adolescents and what is not known about this impact in middle childhood. We then offer recommendations for the types of research that developmental scientists can undertake to examine the efficacy of digital games within the rapidly changing media ecology in which children live. We conclude with a discussion of media policies that we believe can help children benefit from their media use. Our hope is that this review will foster greater investigation of the cognitive socialization, as raised over 20 years ago by developmental psychologist and early games researcher Patricia Greenfield, that digital games serve during the middle childhood period, and childhood more generally.
AProbing: Estimating available bandwidth using ACK pair probing

Available bandwidth estimation is an effective way to understand the situations of networks and applications. The packet pair technique analyzes the inter-arrival time of packet pair for the available bandwidth estimation in an end-to-end path. The inter-arrival time of packet pair is mostly caused by the queuing delay of narrow link which is sensitive to cross traffic. This paper proposes a new method using ACK pair probing (AProbing) to estimate end-to-end available bandwidth. It improves the packet pair technique with the probe gap model (PGM) which reduces the influences of cross traffic, and reconstructs the acknowledgements (ACKs) of Transmission Control Protocol (TCP) which reduces the overhead of measurement. AProbing has been implemented and verified in NS-3. The simulation results show that the accuracy of AProbing is similar with that of Pathload and 10% higher than the accuracies of Pathchirp and Cprobe. Moreover, AProbing significantly decreases the overhead of bandwidth estimation compared with these existed methods.
Evaluating the Use of Empirically Constructed Lexical Resources for Named Entity Recognition

– Because of privacy concerns and the expense involved in creating an annotated corpus, the existing small annotated corpora might not have sufficient number of examples for statistically learning to extract all the named-entities precisely. In this work, we evaluate what value may lie in automatically generated features based on distributional semantics when using machine-learning named entity recognition (NER).
M2-branes on Orbifolds of the Cone over Q**1,1,1

We study the = 2 supersymmetric Chern-Simons quiver gauge theory recently introduced in arXiv:0809.3237 to describe M2-branes on a cone over the well-known Sasaki-Einstein manifold Q1,1,1. For Chern-Simons levels (k,k,−k,−k) we argue that this theory is dual to AdS4 × Q1,1,1/k. We derive the k orbifold action and show that it preserves geometrical symmetry U(1)R × SU(2) × U(1), in agreement with the symmetry of the gauge theory. We analyze the simplest gauge invariant chiral operators, and show that they match Kaluza-Klein harmonics on AdS4 × Q1,1,1/k. This provides a test of the gauge theory, and in particular of its sextic superpotential which plays an important role in restricting the spectrum of chiral operators. We proceed to study other quiver gauge theories corresponding to more complicated orbifolds of Q1,1,1. In particular, we propose two U(N)4 Chern-Simons gauge theories whose quiver diagrams are the same as in the 4d theories describing D3-branes on a complex cone over F0, a 2 orbifold of the conifold (in 4d the two quivers are related by the Seiberg duality). The manifest symmetry of these gauge theories is U(1)R × SU(2) × SU(2). We argue that these gauge theories at levels (k,k,−k,−k) are dual to AdS4 × Q2,2,2/k. We exhibit calculations of the moduli space and of the chiral operator spectrum which provide support for this conjecture. We also briefly discuss a similar correspondence for AdS4 × M3,2/k. Finally, we discuss resolutions of the cones and their dual gauge theories.
Integrating the Trusted Computing Platform into the Security of Cloud Computing System

Cloud computing has become one of the fastest growing fields in computer science. As the new computing service pattern of cloud computing develops rapidly, the security problem of cloud computing has become a hot research topic. Before the user passes important data or computing task to the cloud, the user of the cloud may want to verify the trusted status of the platform which actually carries out the computing task in the cloud. And the remote attestation mechanism in Trusted Computing is suited for the cloud user's verification need. Cloud computing basically provides people the way to share heterogeneous distributed resources and various services that belong to various organizations or sites. Since cloud computing share heterogeneous distributed resources via the network through in the open Internet Technology environment, thus it makes security problems necessary for us to develop the cloud computing application environment. In this paper, we pay attention to the security requirements in cloud computing environment system. We proposed a method to build a trusted computing environment for cloud computing system by integrating the trusted computing platform into the security of cloud computing system. We propose a model system in which cloud computing system is combined with trusted computing platform with trusted platform module. In this model, some important security services, including authentication, confidentiality and integrity, are provided in cloud computing system. Keyword: - Distributed system, Cloud Computing, trusted service, trusted computing platform, trusted platform module.