Miracle-dz/UniFAR-FTUs huggingface dataset:
Automating Failure Testing Research at Internet Scale

Large-scale distributed systems must be built to anticipate and mitigate a variety of hardware and software failures. In order to build confidence that fault-tolerant systems are correctly implemented, Netflix (and similar enterprises) regularly run failure drills in which faults are deliberately injected in their production system. The combinatorial space of failure scenarios is too large to explore exhaustively. Existing failure testing approaches either randomly explore the space of potential failures randomly or exploit the "hunches" of domain experts to guide the search. Random strategies waste resources testing "uninteresting" faults, while programmer-guided approaches are only as good as human intuition and only scale with human effort. In this paper, we describe how we adapted and implemented a research prototype called lineage-driven fault injection (LDFI) to automate failure testing at Netflix. Along the way, we describe the challenges that arose adapting the LDFI model to the complex and dynamic realities of the Netflix architecture. We show how we implemented the adapted algorithm as a service atop the existing tracing and fault injection infrastructure, and present early results.
A Parallel Algorithms on Nearest Neighbor Search

The (k-)nearest neighbor searching has very high computational costs. The algorithms presented for nearest neighbor search in high dimensional spaces have have suffered from curse of dimensionality, which affects either runtime or storage requirements of the algorithms terribly. Parallelization of nearest neighbor search is a suitable solution for decreasing the workload caused by nearest neighbor searching in high dimensions. In this paper, we have surveyed notable advancements in the parallelization efforts on nearest neighbor searching algorithms. The algorithms covered are ordered chronologically for exhibiting the evolution throughout the years. Recent improvements on GPU based nearest neighbor search algorithms are covered. Additionally, we address the open problems in the area of parallel nearest neighbor algorithms.
Correlation of Cerebrospinal Fluid (CSF) Cell Counts and Elevated CSF Protein Levels with Enterovirus Reverse Transcription-PCR Results in Pediatric and Adult Patients

ABSTRACT During the 2001, 2002, and 2003 enterovirus seasons, we investigated the correlations between cerebrospinal fluid (CSF) nucleated cell counts and elevated CSF protein levels and the detection of enteroviral RNA by reverse transcription (RT)-PCR. Our objective was to determine if pleocytosis and/or elevated protein levels were predictive of positive RT-PCR results for enterovirus. We were also interested in determining if the presence of West Nile virus during the 2002 enteroviral season contributed to a change in these correlations. We found that in the group of patients aged >2 months, the absence of pleocytosis was highly predictive of a negative RT-PCR result. Elevated CSF protein level was not a good predictor of RT-PCR positivity for enterovirus and did not add to the diagnostic sensitivity or specificity of pleocytosis.
Memory test experiment: industrial results and data

The results of 12 well-known and three fault-primitive-based memory test algorithms applied to 0.13 micron technology 512 kB single-port SRAMs are presented. Each test algorithm is used with up to 16 different stress combinations (SCs) (i.e. different address sequences, data backgrounds and voltages) resulting in 122 tests. The results show that SCs influence the fault coverage (FC) of the test algorithms, that the highest FC is obtained at a low voltage level and that the highest detected number of unique faults is obtained at a high voltage level. They also show that the tests with the most promising FC, based on the theory, also tend to have the highest FC in practice. Moreover, the test results show that some algorithms detect faults that cannot be explained with the existing fault models, indicating that the existing fault models still leave much to be explained; for example, no theoretical basis exists to model the stresses and the predicted FC for a given test.
Overlapping Non-dedicated Clusters Architecture

Non-dedicated computer clusters promise more efficient resource utilization than conventional dedicated clusters. Existing non-dedicated clustering solutions either expect trust among participating users, or they do not take into account a possibility of running multiple independent clusters on a same set of computers.In this paper, we argue how an ability to run multiple independent clusters without requiring trust among participating users can be capitalized to increase user experience and thus attract more users to participate in the cluster. A generic extension of non-dedicated clusters that satisfies these requirements is defined and a feasibility of one particular extension is demonstrated on our implementation.
Generalization of Shannon-Khinchin axioms to nonextensive systems and the uniqueness theorem for the nonextensive entropy

Tsallis entropy, one-parameter generalization of Shannon entropy, has been often discussed in statistical physics as a new information measure. This new information measure has provided many satisfactory physical interpretations in nonextensive systems exhibiting chaos or fractal. We present the generalized Shannon-Khinchin axioms to nonextensive systems and prove the uniqueness theorem rigorously. Our results show that Tsallis entropy is the simplest among all nonextensive entropies. By the detailed comparisons of our axioms with the previously presented two sets of axioms, we reveal the peculiarity of pseudoadditivity as an axiom. In this correspondence, the most fundamental basis for Tsallis entropy as information measure is established in the information-theoretic framework.
S2SI: A Practical Pseudonym Changing Strategy for Location Privacy in VANETs

Location privacy remains an open issue in VANETs. Although, frequently pseudonym changing is commonly accepted as solution to protect privacy in VANETs, many studies have been shown its weakness to provide the required level of privacy protection. In this paper, we propose a practical pseudonym changing strategy, called Silence & Swap at Signalized Intersection (S2SI). S2SI consists of two protocols, one for creating of safe silent mix zones and another for exchanging pseudonyms between vehicles under the control of RSUs within these zones. We evaluate the provided privacy protection of our strategy by developing anonymity set analytic model and by performing a simulative study of the strategy using the entropy of vehicles' anonymity set as the primary metric.
On the interaction between cosmic rays and dark matter molecular clouds in the Milky Way – I. Basic considerations

ABSTRA C T We explore some basic observational consequences of assuming that the dark matter in the Milky Way consists mainly of molecular clouds, and that cosmic rays can penetrate these clouds. In a favoured model of the clouds, this penetration would have the following consequences, all of which agree with observation. (i) Cosmic ray nuclei would be fragmented when they enter a cloud, giving them a lifetime in the Galaxy of ,10 15 s (for relativistic nuclei). (ii) Pionic g-rays emitted by the clouds, after proton‐proton (pp) collisions, would have a diffuse flux in the Galactic plane comparable to the flux from known sources for photon energies *1 GeV. (iii) The heat input into the clouds from cosmic rays would be re-radiated mainly in the far-infrared. The resulting radiation background agrees, in both intensity and spectrum in different directions, with a known excess in the far-infrared background of the galaxy over emission by warm dust.
Design Considerations for Traveling-Wave Single-Pole Multithrow MMIC Switch Using Fully Distributed FET

The circuit design considerations for the traveling-wave switch (TWSW) single-pole double-throw (SPDT) monolithic microwave integrated circuit (MMIC) utilizing a fully distributed FET (FD-FET) are presented here for the first time. The normalized length of the impedance transformer for a single-pole multithrow TWSW using the FD-FET is found to be less than a quarter-wavelength at the operating frequency. Unlike the TWSW using lumped FETs, the TWSW with the FD-FET offers the advantage of no design limits regarding such frequency characteristics as bandwidth and group delay. The newly developed SPDT TWSW MMIC using the 400-mum-gate finger FD-FET delivers broadband characteristics over more than an octave frequency range with highly reliable MMIC technology. The newly developed SPDT MMIC switch provides low insertion loss of less than 2.1 dB and high isolation of over 25.5 dB from 38 to 80 GHz, coupled with the benefit of very small size
Institute of Physics Publishing Journal of Micromechanics and Microengineering the Nonlinear Response of Resonant Microbeam Systems with Purely-parametric Electrostatic Actuation

Electrostatically-actuated resonant microbeam devices have garnered significant attention due to their geometric simplicity and broad applicability. Recently, some of this focus has turned to comb-driven microresonators with purely-parametric excitation, as such systems not only exhibit the inherent benefits of MEMS devices, but also a general improvement in sensitivity, stopband attenuation and noise rejection. This work attempts to combine each of these areas by proposing a microbeam device which couples the inherent benefits of a resonator with purely-parametric excitation with the simple geometry of a microbeam. Theoretical analysis reveals that the proposed device exhibits desirable response characteristics, but also quite complex dynamics. Of particular note is the fact that the device's nonlinear frequency response is found to be qualitatively dependent on the system's ac excitation amplitude. While this flexibility can be desirable in certain contexts, it introduces additional design and operating limitations. While the principal focus of this work is the proposed system's nonlinear response, the work also contains details pertaining to model development and device design.
A scalable graph pattern matching engine on top of Apache Giraph Master Thesis in Parallel and Distributed Computer Systems

Many applications are switching to a graph representation of their data in order to take advantage of the connections that exist between entities. Consequently, graph databases are becoming increasingly popular. A query in such a graph database can be expressed as a graph pattern matching problem, which is NP complete, a problem especially relevant in the presence of largedata. To overcome the need of fast and scalable graph processing, this project leverages the open source project Apache Giraph, a system based on the Bulk Synchronous Parallel model of distributed computation. We built on top of Giraph a scalable graph pattern matching engine that accepts queries equivalent with the ones that can be expressed with a subset of Cypher. Unlike existing graph databases which were designed to provide interactive queries and thus strive for low-latency, we focused on offline graph analytics queries. These types of queries operate with large amounts of data and are better suited for distributed environments. As such the evaluation of our system showed that it scales and supports queries for data sets of 16 million entities.
QUARK MATTER IN MASSIVE COMPACT STARS

The recent observation of the pulsar PSR J1614-2230 with a mass of 1.97 ± 0.04 M☉ gives a strong constraint on the quark and nuclear matter equations of state (EoS). We explore the parameter ranges for a parameterized EoS for quark stars. We find that strange stars, made of absolutely stable strange quark matter, comply with the new constraint only if effects from the strong coupling constant and color-superconductivity are taken into account. Hybrid stars, compact stars with a quark matter core and a hadronic outer layer, can be as massive as 2 M☉, but only for a significantly limited range of parameters. We demonstrate that the appearance of quark matter in massive stars crucially depends on the stiffness of the nuclear matter EoS. We show that the masses of hybrid stars stay below the ones of hadronic and pure quark stars, due to the softening of the EoS at the quark–hadron phase transition.
Target Prediction For Indirect Jumps

As the issue rate and pipeline depth of high performance superscalar processors increase, the amount of speculative work issued also increases. Because speculative work must be thrown away in the event of a branch misprediction, wide-issue, deeply pipelined processors must employ accurate branch predictors to effectively exploit their performance potential. Many existing branch prediction schemes are capable of accurately predicting the direction of conditional branches. However, these schemes are ineffective in predicting the targets of indirect jumps achieving, on average, a prediction accuracy rate of 51.8% for the SPECint95 benchmarks. In this paper, we propose a new prediction mechanism, the target cache, for predicting indirect jump targets. For the perl and gcc benchmarks, this mechanism reduces the indirect jump misprediction rate by 93.4% and 63.35% and the overall execution time by 14% and 5%.
Auditory Brainstem Response Latency in Noise as a Marker of Cochlear Synaptopathy

Evidence from animal and human studies suggests that moderate acoustic exposure, causing only transient threshold elevation, can nonetheless cause “hidden hearing loss” that interferes with coding of suprathreshold sound. Such noise exposure destroys synaptic connections between cochlear hair cells and auditory nerve fibers; however, there is no clinical test of this synaptopathy in humans. In animals, synaptopathy reduces the amplitude of auditory brainstem response (ABR) wave-I. Unfortunately, ABR wave-I is difficult to measure in humans, limiting its clinical use. Here, using analogous measurements in humans and mice, we show that the effect of masking noise on the latency of the more robust ABR wave-V mirrors changes in ABR wave-I amplitude. Furthermore, in our human cohort, the effect of noise on wave-V latency predicts perceptual temporal sensitivity. Our results suggest that measures of the effects of noise on ABR wave-V latency can be used to diagnose cochlear synaptopathy in humans. SIGNIFICANCE STATEMENT Although there are suspicions that cochlear synaptopathy affects humans with normal hearing thresholds, no one has yet reported a clinical measure that is a reliable marker of such loss. By combining human and animal data, we demonstrate that the latency of auditory brainstem response wave-V in noise reflects auditory nerve loss. This is the first study of human listeners with normal hearing thresholds that links individual differences observed in behavior and auditory brainstem response timing to cochlear synaptopathy. These results can guide development of a clinical test to reveal this previously unknown form of noise-induced hearing loss in humans.
Preconditioning Techniques for Constrained Vector Potential Integral Equations, with Application to 3-d Magnetoquasistatic Analysis of Electronic Packages

In this paper techniques are presented for preconditioning equations generated by discretizing constrained vector integral equations associated with magnetoquasistatic analysis. Standard preconditioning approaches often fail on these problems. We present a specialized preconditioning technique and prove convergence bounds independent of the constraint equations and electromagnetic excitation frequency. Computational results from analyzing several electronic packaging examples are given to demonstrate that the new preconditioning approach can sometimes reduce the number of GMRES iterations by more than an order of magnitude.
Path Planning to Optimize Wind Observability in a Planar Uniform Flow Field

This paper is concerned with path planning for under-sensed vehicles, where the vehicle has insufficient sensors to estimate its state without active control. One such system is an autonomous underwater vehicle, which typically does not have complete inertial position information. Using the condition number of the observability gramian as a cost functional, we develop an observability optimal control problem for a general nonlinear system and discuss solution methods. Two planar navigation problems for a nonholonomic vehicle in uniform currents are presented, and we derive trajectories that maximize system and currents observability using limited inertial sensors. Simulation results show that the optimal trajectories yield faster estimator convergence and lower steady-state covariances.
Unexpected Inflation , Real Wages , and Employment Determination in Union Contracts

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Email Surveys in Educational Research: Ethical and Net-Cultural Concerns.

The growth of the Internet and the increasing application of electronic mail in many aspects of business and educational research have urged researchers to reach different individuals across geographical borders with an obvious reduction of costs and time. While the use of email surveys in educational research, as this paper mainly argues, offers significant benefits to researchers in collecting data, more awareness of ethical codes of conduct and culture of net-users should be insisted throughout the research process to enhance validity and to minimize physical or mental harm that may cause to the researched participants of different ethnic and socioeconomic backgrounds. This essay is not going to greatly discuss technological methods or concerns in the design of an email survey.
A multi-hop localization algorithm in underwater wireless sensor networks

In mobile underwater environment, underwater wireless sensor networks (UWSNs) keep moving and dispersing due to water flowing and aquatic creatures touching, and thus some isolated nodes appear. This type of isolated nodes cannot obtain enough anchor nodes in their communication range, which makes self-localizations disabled. In order to solve this problem, a multi-hop localization scheme is proposed in this paper. Firstly, ordinary nodes between anchors and unknown nodes are set as routers to find the shortest paths by a greedy approach; secondly, the shortest paths are approximately fitted into a straight distance between two nodes; finally, the positions of unknown nodes can be calculated by trilateration. The proposed algorithm is simulated and is compared with other algorithms in terms of localization error, and the results are proven preferable.
Predictors of hospital mortality in the global registry of acute coronary events.

BACKGROUND Management of acute coronary syndromes (ACS) should be guided by an estimate of patient risk. OBJECTIVE To develop a simple model to assess the risk for in-hospital mortality for the entire spectrum of ACS treated in general clinical practice. METHODS A multivariable logistic regression model was developed using 11 389 patients (including 509 in-hospital deaths) with ACS with and without ST-segment elevation enrolled in the Global Registry of Acute Coronary Events (GRACE) from April 1, 1999, through March 31, 2001. Validation data sets included a subsequent cohort of 3972 patients enrolled in GRACE and 12 142 in the Global Use of Strategies to Open Occluded Coronary Arteries IIb (GUSTO-IIb) trial. RESULTS The following 8 independent risk factors accounted for 89.9% of the prognostic information: age (odds ratio [OR], 1.7 per 10 years), Killip class (OR, 2.0 per class), systolic blood pressure (OR, 1.4 per 20-mm Hg decrease), ST-segment deviation (OR, 2.4), cardiac arrest during presentation (OR, 4.3), serum creatinine level (OR, 1.2 per 1-mg/dL [88.4- micro mol/L] increase), positive initial cardiac enzyme findings (OR, 1.6), and heart rate (OR, 1.3 per 30-beat/min increase). The discrimination ability of the simplified model was excellent with c statistics of 0.83 in the derived database, 0.84 in the confirmation GRACE data set, and 0.79 in the GUSTO-IIb database. CONCLUSIONS Across the entire spectrum of ACS and in general clinical practice, this model provides excellent ability to assess the risk for death and can be used as a simple nomogram to estimate risk in individual patients.
Selective Impairments of Resting-State Networks in Minimal Hepatic Encephalopathy

Background Minimal hepatic encephalopathy (MHE) is a neuro-cognitive dysfunction characterized by impairment in attention, vigilance and integrative functions, while the sensorimotor function was often unaffected. Little is known, so far, about the exact neuro-pathophysiological mechanisms of aberrant cognition function in this disease. Methodology/Principal Findings To investigate how the brain function is changed in MHE, we applied a resting-state fMRI approach with independent component analysis (ICA) to assess the differences of resting-state networks (RSNs) between MHE patients and healthy controls. Fourteen MHE patients and 14 age-and sex-matched healthy subjects underwent resting-state fMRI scans. ICA was used to identify six RSNs [dorsal attention network (DAN), default mode network (DMN), visual network (VN), auditory network (AN), sensorimotor network (SMN), self-referential network (SRN)] in each subject. Group maps of each RSN were compared between the MHE and healthy control groups. Pearson correlation analysis was performed between the RSNs functional connectivity (FC) and venous blood ammonia levels, and neuropsychological tests scores for all patients. Compared with the healthy controls, MHE patients showed significantly decreased FC in DAN, both decreased and increased FC in DMN, AN and VN. No significant differences were found in SRN and SMN between two groups. A relationship between FC and blood ammonia levels/neuropsychological tests scores were found in specific regions of RSNs, including middle and medial frontal gyrus, inferior parietal lobule, as well as anterior and posterior cingulate cortex/precuneus. Conclusions/Significance MHE patients have selective impairments of RSNs intrinsic functional connectivity, with aberrant functional connectivity in DAN, DMN, VN, AN, and spared SMN and SRN. Our fMRI study might supply a novel way to understand the neuropathophysiological mechanism of cognition function changes in MHE.
Optimum stacked layout for analog CMOS ICs

A rigorous and efficient technique is presented for module generation in a maximally stacked layout paradigm for CMOS analog integrated circuits. Analog constraints on symmetry and matching provide a key for heuristics, substantially reducing the computational complexity of robust graph algorithms. The solution found minimizes a cost function accounting for parasitic control and routability considerations. Combined with sensitivity analysis and automatic constraint generation, this algorithm provides a suitable performance-driven approach to analog layout module generation. Examples are reported showing the effectiveness of this approach.