Miracle-dz/UniFAR-FTUs huggingface dataset:
Calpain Inhibition Reduces Axolemmal Leakage in Traumatic Axonal Injury

Calcium-induced, calpain-mediated proteolysis (CMSP) has recently been implicated to the pathogenesis of diffuse (traumatic) axonal injury (TAI). Some studies suggested that subaxolemmal CMSP may contribute to axolemmal permeability (AP) alterations observed in TAI. Seeking direct evidence for this premise we investigated whether subaxolemmal CMSP may contribute to axolemmal permeability alterations (APA) and pre-injury calpain-inhibition could reduce AP in a rat model of TAI. Horseradish peroxidase (HRP, a tracer that accumulates in axons with APA) was administered one hour prior to injury into the lateral ventricle; 30 min preinjury a single tail vein bolus injection of 30 mg/kg MDL-28170 (a calpain inhibitor) or its vehicle was applied in Wistar rats exposed to impact acceleration brain injury. Histological detection of traumatically injured axonal segments accumulating HRP and statistical analysis revealed that pre-injury administration of the calpain inhibitor MDL-28170 significantly reduced the average length of HRP-labeled axonal segments. The axono-protective effect of pre-injury calpain inhibition recently demonstrated with classical immunohistochemical markers of TAI was further corroborated in this experiment; significant reduction of the length of labeled axons in the drug-treated rats implicate CMSP in the progression of altered AP in TAI.
Observation planning for efficient environment information summarization

Mapping is an activity of making a useful description of an environment. Not only geometric information such as free space but also object placements are important if the map is used for human-robot communication. We call such a map making environment information summarization because how to summarize may change depending on the purpose of the map. Environment information summarization usually includes searching for specified objects in the environment. It is, therefore, crucial to make a good observation plan for efficient summarization. We develop an observation planning method which uses object appearance models for appropriately handling a trade-off between visual data quality and vision cost. Experimental results using a vision-based humanoid robot show the effectiveness of the proposed planning method.
MSBVH: an efficient acceleration data structure for ray traced motion blur

When a bounding volume hierarchy is used for accelerating the intersection of rays and scene geometry, one common way to incorporate motion blur is to interpolate node bounding volumes according to the time of the ray. However, such hierarchies typically exhibit large overlap between bounding volumes, which results in an inefficient traversal. This work builds upon the concept of spatially partitioning nodes during tree construction in order to reduce overlap in the presence of moving objects. The resulting hierarchies are often significantly cheaper to traverse than those generated by classic approaches.
The Rise and Fall of Dark Silicon

7 HARDWARE Industry experts predict that transistor counts will continue to grow exponentially for at least another decade. Historically we were able to harness all of these transistors to deliver exponential increases in computational power by capitalizing on both technological improvements and micro-architectural innovation. However , after decades of reaping Moore's bounty, processors eventually hit a power wall. Technological limitations will soon prevent us from powering all transistors simultaneously, leaving a large fraction of the chip powered off ("dark"). Short of a technological miracle, we head toward an era of " dark silicon, " able to build dense devices we cannot afford to power. Without the ability to use more transistors or run them faster, performance improvements are likely to stagnate unless we change course. In this article we (see Acknowledgments) discuss the technological trends that give rise to dark silicon and outline our current efforts to curb them. One of the most important realizations is that instead of wasting the dark silicon, we can harness it to implement specialized cores, where each core is able to perform a narrow set of tasks at significantly lower energy. We envision an architecture that provides a sea of specialized cores, with the executing workload powering up only the most application-specific hardware, while the rest of the chip is switched off to conserve energy. The new architecture shows promise in solving the problem of dark silicon for the foreseeable future, but requires us to overcome several challenges across the entire computing stack to realize it. Computer systems have already become indispensable and ubiquitous in every aspect of our life. Our continuous reliance on computers generates data at exponential rates. For example, during March 2011, over 1 . 6 PB of data was generated and transferred for processing among the Tier-1 sites of CERN's Large Hadron Collider computing grid [1]. Typical business data sets have grown by 29% annually over the last decade, surpassing Moore's Law [2], and personal data has been shown to grow at similar rates. Processing all this data requires unprecedented amounts of computation, with commensurate energy demands. To put the energy demands into perspective, it suffices to note that a 1,000m 2 datacenter is a 1 . 5 MW facility. Gartner estimates that personal computers and servers consumed 408 TWh of energy globally in 2010 [3]. Computer energy consumption in the US alone is estimated at 150 TWh annually, accounting for 3 …
Control systems for robotic gloves

A robotic glove designed to help stroke patients regain movement of their hands has been developed as part of a collaborative project in Romania. The robotic glove has been designed to facilitate repetitive movement and exercise of the hand of patients within the chronic stage of illness and after they have been released from hospital. A method for the analysis of flexion-extension movement of both human and anthropomorphic robotic finger is presented. Two types of control systems developed for robotic gloves and two implemented methods of recuperative actions are presented, too.
When separation logic met Java ( by example )

Separation logic is a promising new approach to modular reasoning, but so far it has primarily been applied to low-level C-like languages. To extend separation logic to allow modular reasoning about object-oriented languages like Java, we must add behavioural subtyping to the logic. However, a na ı̈ve integration of behavioural subtyping and separation logic is too restrictive. In this paper we demonstrate how abstract predicate families provide an abstraction mechanism that addresses these restrictions, by mirroring dynamic dispatch in the logic. We demonstrate the utility of our approach with a series of examples, including the Visitor pattern.
Jumping robot based on the kinematics performance of locust

The geometrical configurations of the locust, Oedaleus infernalis, were obtained by using the stereomicroscope. The jumping movements of the locust were analyzed from the sequences of the images captured by the high-speed camera. The characteristics of the locust during jumping were discussed, and the jumping parameters of the locusts were gained. The jump of the locust was propelled by the simultaneous extension of the two hind legs powered by the rapid depression movements about the coxa-trochanteral joints. Kinematic analysis of the locust jumping provided critical 3D space point data for modeling and simulation. The model of the locust-like robot was established by the technology of virtual prototype. The velocity, acceleration and force of the hind leg of the locust-like robot during jumping were analyzed. This work may provide the basic theory in developing locust-like robot in structural design. Besides, it provides an important reference to study the other bionic robots.
Tensor-Factor Analysis

A nonparametric factor analysis framework is developed for tensor-variate data. The dictionary elements (factor loadings) are inferred as tensors, as opposed to vectors. Our tensor-factor analysis (TFA) framework is developed in the context of the beta-process factor analysis (BPFA) using a nonparametric tensor decomposition for each dictionary element. We extend the multiplicative gamma prior to allow inference of the shape parameter, which can help control model complexity during learning. Moreover, we extend the TFA model to include translation invariance and a multi-layer structure—a deep convolutional TFA. We test our approach on 2D & 3D image denoising, inpainting, and image classiﬁ-cation. Our TFA models provide more diverse dictionaries. In particular, TFA provides state of the art results for simultaneous image inpainting & denoising and on the Caltech 101 benchmark.
Dynamic path planning method for anchor node in three-dimensional wireless sensor networks

Localization constitutes one of the key technologies in wireless sensor networks. In the localization method based on anchor node assistance, the motion path of anchor node exerts huge influence on location performance. With the motion path of anchor node pre-determined, the static path planning fails to make full use of the real-time information during the localization, due to which it can not be applied to the area with unknown deployment and abnormal topology. Resorting to artificial potential field theory, this paper raises a three-dimensional dynamic path planning algorithm of mobile anchor node based on virtual force (3D-VFDPP). By the virtue of real-time calculation of the magnitude of virtual force exerted upon anchor nodes by unknown ones in different areas, this algorithm offers online decision of motion direction to instruct the motion of anchor node. The simulation results show that compared with the typical static planning method, it enjoys a far better effectiveness and universality.
Precise, Scalable, and Online Request Tracing for Multitier Services of Black Boxes

As more and more multitier services are developed from commercial off-the-shelf components or heterogeneous middleware without source code available, both developers and administrators need a request tracing tool to (1) exactly know how a user request of interest travels through services of black boxes and (2) obtain macrolevel user request behaviors of services without manually analyzing massive logs. This need is further exacerbated by IT system “agility,” which mandates the tracing tool to provide online performance data since offline approaches cannot reflect system changes in real time. Moreover, considering the large scale of deployed services, a pragmatic tracing approach should be scalable in terms of the cost in collecting and analyzing logs. In this paper, we introduce a precise, scalable, and online request tracing tool for multitier services of black boxes. Our contributions are threefold. First, we propose a precise request tracing algorithm for multitier services of black boxes, which only uses application-independent knowledge. Second, we present a microlevel abstraction, component activity graph, to represent causal paths of each request. On the basis of this abstraction, we use dominated causal path patterns to represent repeatedly executed causal paths that account for significant fractions, and we further present a derived performance metric of causal path patterns, latency percentages of components, to enable debugging performance-in-the-large. Third, we develop two mechanisms, tracing on demand and sampling, to significantly increase the system scalability. We implement a prototype of the proposed system, called PreciseTracer, and release it as open source code. In comparison with WAP5-a black-box tracing approach, PreciseTracer achieves higher tracing accuracy and faster response time. Our experimental results also show that PreciseTracer has low overhead, and still achieves high tracing accuracy even if an aggressive sampling policy is adopted, indicating that PreciseTracer is a promising tracing tool for large-scale production systems.
Formal Network Testing

Certain types of errors, such as hardware failure, link failure or congestion can only be detected at runtime of network as these are failures that happen when the network is in operation. Today, there exist only preliminary tools to detect and pinpoint such kind of errors, typified by ping and trace rout. In this paper we introduce a formal and comprehensive way to fully test networks at runtime which enables us to pinpoint the exact rule that is causing the problem. Our test packet generation algorithm first picks a relatively small number of test packets and corresponding input ports so that these packets exercise all the rules in network. By periodically sending these packets through the network, we can constantly monitor the health of the network. Whenever an error happens, the fault localization algorithm uses the result of all test packets to find out the exact rule that is in fault.
Material Handling Resource Utilization Simulation Study for Stamping Plant

This paper describes the application of dynamic simulation to evaluate material handling resource utilization for a stamping plant in the automotive industry. The other objective of this study was evaluation of throughput relative to press schedules, shift patterns, the number of material handling resources (i.e. fork truck and tugger train drivers), and storage inventory levels. This dynamic simulation study enabled plant managers to balance the driver utilization with respect to time and to accommodate typical press schedules to achieve desired throughput levels
Geometrical expression of the angular resolution of a network of gravitational-wave detectors and improved localization methods

We report for the first time a method-independent geometrical expression for the angular resolution of an arbitrary network of interferometric gravitational wave (GW) detectors when the arrival-time of a GW is unknown. We discuss the implications of our results on how to improve angular resolutions of a GW network and on improvements of localization methods. An example of an improvement to the null-stream localization method for GWs of unknown waveforms is demonstrated.
The Past is Not a Foreign Country: Detecting Semantically Similar Terms across Time

Numerous archives and collections of past documents have become available recently thanks to mass scale digitization and preservation efforts. Libraries, national archives, and other memory institutions have started opening up their collections to interested users. Yet, searching within such collections usually requires knowledge of appropriate keywords due to different context and language of the past. Thus, non-professional users may have difficulties with conceptualizing suitable queries, as, typically, their knowledge of the past is limited. In this paper, we propose a novel approach for the temporal correspondence detection task that requires finding terms in the past which are semantically closest to a given input present term. The approach we propose is based on vector space transformation that maps the distributed word representation in the present to the one in the past. The key problem in this approach is obtaining correct training set that could be used for a variety of diverse document collections and arbitrary time periods. To solve this problem, we propose an effective technique for automatically constructing seed pairs of terms to be used for finding the transformation. We test the performance of proposed approaches over short as well as long time frames such as 100 years. Our experiments demonstrate that the proposed methods outperform the best-performing baseline by 113 percent for the New York Times Annotated Corpus and by 28 percent for the Times Archive in MRR on average, when the query has a different literal form from its temporal counterpart.
Improving the performance of the UCA when using LTE codebook feedback

In Release 8 (R8) LTE a 4 antenna codebook was designed primarily with a uniform linear array (ULA) in mind. The consequence is that when using an array at the base other than a ULA (for example a uniform circular array (UCA)) the performance with codebook feedback will be degraded relative to a codebook optimized for that array structure. In this paper methods for improving the performance of LTE codebook feedback for non-ULAs (and in particular the UCA) are presented. All of methods have no impact on how the user equipment (UE) operates (i.e., the methods are transparent to the UE) and hence have no impact on the standard. Using these methods improvements of up to 1.2 dB are obtained when using a UCA with the 4 antenna LTE codebook.
Current-Account Reversals in Developing Countries: A Perspective on the East-Asian Crisis

This paper studies episodes of current-account reversal in developing countries (DCs) in the period 1965-1994. First, a number of persistent shifts ("reversals") in the current-account balance dynamics are identified by structural break and segmented trend tests; then, the relationship between these reversals and a set of fundamentals suggested by the intertemporal approach to the current account is investigated in a panel-data set-up. We find that fundamentals play a different role in episodes of persistent deterioration or improvement of the current-account balance in DCs, and focus on the countries involved in the recent external crises in East Asian.
Dynamic Request Splitting for Interactive Cloud Applications

Deploying interactive applications in the cloud is a challenge due to the high variability in performance of cloud services. In this paper, we present Dealer - a system that helps geo-distributed, interactive and multi-tier applications meet their stringent requirements on response time despite such variability. Our approach is motivated by the fact that, at any time, only a small number of application components of large multi-tier applications experience poor performance. Dealer continually monitors the performance of individual components and communication latencies between them to build a global view of the application. In serving any given request, Dealer seeks to minimize user response times by picking the best combination of replicas (potentially located across different data centers). While Dealer requires modifications to application code, we show the changes required are modest. Our evaluations on two multi-tier applications using real cloud deployments indicate the 90%ile of response times could be reduced by more than a factor of 6 under natural cloud dynamics. Our results indicate the cost of inter-data-center traffic with Dealer is minor, and that Dealer can in fact be used to reduce the overall operational costs of applications by up to 15% by leveraging the difference in billing plans of cloud instances.
End-to-end delay analysis for networked systems

End-to-end delay measurement has been an essential element in the deployment of real-time services in networked systems. Traditional methods of delay measurement based on time domain analysis, however, are not efficient as the network scale and the complexity increase. We propose a novel theoretical framework to analyze the end-to-end delay distributions of networked systems from the frequency domain. We use a signal flow graph to model the delay distribution of a networked system and prove that the end-to-end delay distribution is indeed the inverse Laplace transform of the transfer function of the signal flow graph. Two efficient methods, Cramer’s rule-based method and the Mason gain rule-based method, are adopted to obtain the transfer function. By analyzing the time responses of the transfer function, we obtain the end-to-end delay distribution. Based on our framework, we propose an efficient method using the dominant poles of the transfer function to work out the bottleneck links of the network. Moreover, we use the framework to study the network protocol performance. Theoretical analysis and extensive evaluations show the effectiveness of the proposed approach.
Comparison between spatial and temporal independent component analysis for blind source separation in fMRI data

Independent component analysis (ICA) is an exploratory method for analyzing spatial and temporal properties of fMRI data and requires no explicit temporal model, necessary for conventional fMRI analysis. Two varieties of ICA are employed to achieve maximal independence component in space or time yields for functional MRI (fMRI) analysis: spatial ICA (sICA) and temporal ICA (tICA). sICA is widely studied and used in signal separation of fMRI data. In this study, we compared the performance of sica and tICA to extract and separate signals with spatial and temporal independence based on simulated data. Our results reveal that sICA is able to extract and separate relatively highly independent signals. tICA can fulfill the separation of mutually independent component signal in time course and classify the temporally corresponding signal as one group in spite of having a spatially independent component. The results suggest that tICA can be applied to detect a special signal overlapping with the physiological signals by evoking other activations using the special signal.
LTL Satisfiability Checking Revisited

We propose a novel algorithm for the satisfiability problem for Linear Temporal Logic (LTL). Existing approaches first transform the LTL formula into a B"uchi automaton and then perform an emptiness checking of the resulting automaton. Instead, our approach works on-the-fly by inspecting the formula directly, thus enabling finding a satisfying model quickly without constructing the full automaton. This makes our algorithm particularly fast for satisfiable formulas. We report on a prototype implementation, showing that our approach significantly outperforms state-of-the-art tools.
1-15-2013 On Exceptions , Events and Observer Chains

Modular understanding of behaviors and flows of exceptions may help in their better use and handling. Such reasoning tasks about exceptions face unique challenges in event-based implicit invocation (II) languages that allow subjects to implicitly invoke observers, and run the observers in a chain. In this work, we illustrate these challenge in Ptolemy and propose Ptolemyχ that enables modular reasoning about behaviors and flows of exceptions for event announcement and handling. Ptolemyχ’s exception-aware specification expressions and boundary exceptions limit the set of (un)checked exceptions of subjects and observers of an event. Exceptional postconditions specify the behaviors of these exceptions. Greybox specifications specify the flows of these exceptions among the observers in the chain. Ptolemyχ’s type system and refinement rules enforce these specifications and thus enable its modular reasoning. We evaluate the utility of Ptolemyχ’s exception flow reasoning by applying it to understand a set of aspect-oriented (AO) bug patterns. We also present Ptolemyχ’s semantics including its sound static semantics.
Dynamic phase transition for decoding algorithms.

The state-of-the-art error correcting codes are based on large random constructions (random graphs, random permutations, etc.) and are decoded by linear-time iterative algorithms. Because of these features, they are remarkable examples of diluted mean-field spin glasses, both from the static and dynamic points of view. We analyze the behavior of decoding algorithms by mapping them onto statistical-physics models. This allows us to understand the intrinsic (i.e., algorithm independent) features of this behavior.