Miracle-dz/UniFAR-FTUs huggingface dataset:
Preserving Consistency Based on Wall-Time Precedence in P2P DVEs

Based on the analysis of the work mode of peer-to-peer (P2P) distributed virtual environments (DVEs), the paper proposes the ideal and relaxed consistency model, and introduces wall-time as the basis of the precedence order. Then the status-retrace algorithm based on wall-time precedence is proposed to realize the synchronization of parallel actions from local and remote sites. Quick-response-wins strategy is introduced to process the wall-time conflict operations and direct precedence, causal precedence based on logical time is also inducted to repair visual confusion caused by status-retrace method. The contrast experiments show the advantages of the newly developed algorithm in highly concurrent environment.
Powertrain control verification benchmark

Industrial control systems are often hybrid systems that are required to satisfy strict performance requirements. Verifying designs against requirements is a difficult task, and there is a lack of suitable open benchmark models to assess, evaluate, and compare tools and techniques. Benchmark models can be valuable for the hybrid systems research community, as they can communicate the nature and complexity of the problems facing industrial practitioners. We present a collection of benchmark problems from the automotive powertrain control domain that are focused on verification for hybrid systems; the problems are intended to challenge the research community while maintaining a manageable scale. We present three models of a fuel control system, each with a unique level of complexity, along with representative requirements in signal temporal logic (STL). We provide results obtained by applying a state of the art analysis tool to these models, and finally, we discuss challenge problems for the research community.
PIM-enabled instructions: A low-overhead, locality-aware processing-in-memory architecture

Processing-in-memory (PIM) is rapidly rising as a viable solution for the memory wall crisis, rebounding from its unsuccessful attempts in 1990s due to practicality concerns, which are alleviated with recent advances in 3D stacking technologies. However, it is still challenging to integrate the PIM architectures with existing systems in a seamless manner due to two common characteristics: unconventional programming models for in-memory computation units and lack of ability to utilize large on-chip caches. In this paper, we propose a new PIM architecture that (I) does not change the existing sequential programming models and (2) automatically decides whether to execute PIM operations in memory or processors depending on the locality of data. The key idea is to implement simple in-memory computation using compute-capable memory commands and use specialized instructions, which we call PIM-enabled instructions, to invoke in-memory computation. This allows PIM operations to be interoperable with existing programming models, cache coherence protocols, and virtual memory mechanisms with no modification. In addition, we introduce a simple hardware structure that monitors the locality of data accessed by a PIM-enabled instruction at runtime to adaptively execute the instruction at the host processor (instead of in memory) when the instruction can benefit from large on-chip caches. Consequently, our architecture provides the illusion that PIM operations are executed as if they were host processor instructions. We provide a case study of how ten emerging data-intensive workloads can benefit from our new PIM abstraction and its hardware implementation. Evaluations show that our architecture significantly improves system performance and, more importantly, combines the best parts of conventional and PlM architectures by adapting to data locality of applications.
The Effect of Cryogenic Treatment on the Fatigue Life of Chrome Silicon Steel Compression Springs

THE EFFECT OF CRYOGENIC TREATMENT ON THE FATIGUE LIFE OF CHROME SILICON STEEL COMPRESSION SPRINGS Debra Lynn Smith, B.S., M.S. Marquette University, 2011 The purpose of this dissertation is to explore the effect of cryogenic treatment on the fatigue life of compression springs. Product manufacturers are constantly searching for ways to make their products last longer. This dissertation addresses three questions: (1) What is the effect of cryogenic treatment on the fatigue life of chrome silicon steel compression springs? Does the life increase, decrease, or remain the same? (2) What is the effect of cryogenic treatment on the Percent Load Loss (Stress Relaxation) of chrome silicon steel compression springs? (3) What are the possible changes in the material that cause these effects? The following tests were carried out; wire tensile test, hardness test, chemical analysis, residual stress, retained austenite, lattice parameter, force vs. deflection, percent load loss (stress relaxation), fatigue, microstructures, and eta carbides. This research produced a number of key findings: (1) The cryogenically treated springs had a longer cycle life and a higher endurance limit than the untreated springs. (2) The percent load loss (stress relaxation) of the cryogenically treated springs was similar to the untreated springs. (3) The cryogenically treated springs had a higher compressive residual stress at the surface than the untreated springs. The conclusions of this research are that the cryogenic treatment of chrome silicon steel compression springs led to an increase in compressive residual stress on the wire surface, which in turn led to an increase in fatigue life and a higher endurance limit. A recommended future study would be to compare cryogenically treated springs to shot peened springs.
Urate Crystal Induced Inflammation and Joint Pain Are Reduced in Transient Receptor Potential Ankyrin 1 Deficient Mice – Potential Role for Transient Receptor Potential Ankyrin 1 in Gout

Introduction In gout, monosodium urate (MSU) crystals deposit intra-articularly and cause painful arthritis. In the present study we tested the hypothesis that Transient Receptor Poten-tial Ankyrin 1 (TRPA1), an ion channel mediating nociceptive signals and neurogenic in-flammation, is involved in MSU crystal-induced responses in gout by utilizing three experi-mental murine models. Methods The effects of selective pharmacological inhibition (by HC-030031) and genetic depletion of TRPA1 were studied in MSU crystal-induced inflammation and pain by using 1) spontaneous weight-bearing test to assess MSU crystal-induced joint pain, 2) subcutaneous air-pouch model resembling joint inflammation to measure MSU crystal-induced cytokine production and inflammatory cell accumulation, and 3) MSU crystal-induced paw edema to assess acute vascular inflammatory responses and swelling. Results Intra-articularly injected MSU crystals provoked spontaneous weight shift off from the affected limb in wild type but not in TRPA1 knock-out mice referring alleviated joint pain in TRPA1 deficient animals. MSU crystal-induced inflammatory cell infiltration and accumulation of cytokines MCP-1, IL-6, IL-1beta, MPO, MIP-1alpha and MIP-2 into subcu-taneous air-pouch (resembling joint cavity) was attenuated in TRPA1 deficient mice and in mice treated with the selective TRPA1 inhibitor HC-030031 as compared to control animals. Further, HC-030031 treated and TRPA1 deficient mice developed tempered inflammatory edema when MSU crystals were injected into the paw. Conclusions TRPA1 mediates MSU crystal-induced inflammation and pain in experimental models supporting the role of TRPA1 as a potential mediator and a drug target in gout flare.
The impact of anesthesia providers on major morbidity following screening colonoscopies

Background and aims Few studies evaluate the impact of anesthesia providers during procedures, such as colonoscopy, on low-risk patients. The objective of this study was to compare the effect of anesthesia providers on several outcome variables, including major morbidity, following screening colonoscopies. Methods A propensity-matched cohort study of 14,006 patients who enrolled with a national insurer offering health maintenance organization (HMO), preferred provider organization (PPO), and Medicare Advantage plans for a screening colonoscopy between July 1, 2005 and June 30, 2007 were studied. Records were evaluated for completion of the colonoscopy, new cancer diagnosis (colon, anal, rectal) within 6 months of the colonoscopy, new primary diagnosis of myocardial infarction (MI), new primary diagnosis of stroke, hospital admission within 7 days of the colonoscopy, and adherence to guidelines for use of anesthesia providers. Results The presence of an anesthesia provider did not affect major morbidity or the percent of completed exams. Overall morbidity within 7 days was very low. When an anesthesia provider was present, a nonsignificant trend toward greater cancer detection within 6 months of the procedure was observed. Adherence to national guidelines regarding the use of anesthesia providers for low-risk patients was poor. Conclusion A difference in outcome associated with the presence or absence of an anesthesia provider during screening colonoscopy in terms of MI, stroke, or hospital admission within 7 days of the procedure was not observed. Adherence to published guidelines for the use of anesthesia providers is low. The incidence of completed exams was unaffected by the presence of an anesthesia provider. However, a nonstatistically significant trend toward increased cancer detection requires further study.
A survey of error-correction methods for next-generation sequencing

UNLABELLED Error Correction is important for most next-generation sequencing applications because highly accurate sequenced reads will likely lead to higher quality results. Many techniques for error correction of sequencing data from next-gen platforms have been developed in the recent years. However, compared with the fast development of sequencing technologies, there is a lack of standardized evaluation procedure for different error-correction methods, making it difficult to assess their relative merits and demerits. In this article, we provide a comprehensive review of many error-correction methods, and establish a common set of benchmark data and evaluation criteria to provide a comparative assessment. We present experimental results on quality, run-time, memory usage and scalability of several error-correction methods. Apart from providing explicit recommendations useful to practitioners, the review serves to identify the current state of the art and promising directions for future research. AVAILABILITY All error-correction programs used in this article are downloaded from hosting websites. The evaluation tool kit is publicly available at: http://aluru-sun.ece. iastate.edu/doku.php? id=ecr.
Neural adaptation to resistance training: changes in evoked V-wave and H-reflex responses.

Combined V-wave and Hoffmann (H) reflex measurements were performed during maximal muscle contraction to examine the neural adaptation mechanisms induced by resistance training. The H-reflex can be used to assess the excitability of spinal alpha-motoneurons, while also reflecting transmission efficiency (i.e., presynaptic inhibition) in Ia afferent synapses. Furthermore, the V-wave reflects the overall magnitude of efferent motor output from the alpha-motoneuron pool because of activation from descending central pathways. Fourteen male subjects participated in 14 wk of resistance training that involved heavy weight-lifting exercises for the muscles of the leg. Evoked V-wave, H-reflex, and maximal M-wave (M(max)) responses were recorded before and after training in the soleus muscle during maximal isometric ramp contractions. Maximal isometric, concentric, and eccentric muscle strength was measured by use of isokinetic dynamometry. V-wave amplitude increased approximately 50% with training (P < 0.01) from 3.19 +/- 0.43 to 4.86 +/- 0.43 mV, or from 0.308 +/- 0.048 to 0.478 +/- 0.034 when expressed relative to M(max) (+/- SE). H-reflex amplitude increased approximately 20% (P < 0.05) from 5.37 +/- 0.41 to 6.24 +/- 0.49 mV, or from 0.514 +/- 0.032 to 0.609 +/- 0.025 when normalized to M(max). In contrast, resting H-reflex amplitude remained unchanged with training (0.503 +/- 0.059 vs. 0.499 +/- 0.063). Likewise, no change occurred in M(max) (10.78 +/- 0.86 vs. 10.21 +/- 0.66 mV). Maximal muscle strength increased 23-30% (P < 0.05). In conclusion, increases in evoked V-wave and H-reflex responses were observed during maximal muscle contraction after resistance training. Collectively, the present data suggest that the increase in motoneuronal output induced by resistance training may comprise both supraspinal and spinal adaptation mechanisms (i.e., increased central motor drive, elevated motoneuron excitability, reduced presynaptic inhibition).
Predicting CPAP Use and Treatment Outcomes Using Composite Indices of Sleep Apnea Severity.

STUDY OBJECTIVES Measures of baseline sleep apnea disease burden (apnea-hypopnea index, Epworth Sleepiness Scale) predict continuous positive airway pressure (CPAP) adherence, but composite indices of sleep apnea severity (Sleep Apnea Severity Index, Modified Sleep Apnea Severity Index) may be more robust measures of disease burden. We tested the relative prognostic ability of each measure of sleep apnea disease burden to predict subsequent CPAP adherence and subjective sleep outcomes. METHODS Prospective cohort study at a tertiary academic sleep center. Patients (n = 323) underwent initial diagnostic polysomnography for suspected obstructive sleep apnea and 6 mo of subsequent CPAP therapy. RESULTS Baseline apnea-hypopnea index and both composite indices predicted adherence to CPAP therapy at 6 mo in multivariate analyses (all p ≤ 0.001). Baseline Epworth Sleepiness Scale did not predict CPAP adherence (p = 0.22). Both composite indices were statistically stronger predictors of CPAP adherence at 6 mo than apnea-hypopnea index (p < 0.001). In multivariate analyses, baseline apnea-hypopnea index (p < 0.05) and both composite indices (both p < 0.04) predicted change in Pittsburgh Sleep Quality Index, whereas only the composite indices predicted changes in Sleep Apnea Quality of Life Index (both p < 0.001). Adjustment for treatment adherence did not affect the relationship of the composite indices with change in Sleep Apnea Quality of Life Index (both p ≤ 0.005). CONCLUSIONS Composite indices of baseline sleep apnea severity better predict objective CPAP adherence and subjective treatment outcomes than baseline apnea-hypopnea index and baseline Epworth Sleepiness Scale.
A two‐part model for censored medical cost data

The two‐part model is often used to analyse medical cost data which contain a large proportion of zero cost and are highly skewed with some large costs. The total medical costs over a period of time are often censored due to incomplete follow‐up, making the analysis difficult as the censoring can be informative. We propose to apply the inverse probability weighting method on a two‐part model to analyse right‐censored cumulative medical costs with informative censoring. We also introduce a set of simple functionals based on the intermediate cost history to be applied with the efficiency augmentation technique. In addition, we propose a practical model‐checking technique based on the cumulative residuals. Simulation studies are conducted to evaluate the finite sample performance of the proposed method. We use a data set on the cardiovascular disease (CVD)‐related Medicare costs to illustrate our proposed method. Copyright © 2007 John Wiley & Sons, Ltd.
Contradictory antecedent debugging in bounded model checking

In the context of formal verification Bounded Model Checking (BMC) has shown to be very powerful for large industrial designs. BMC is used to check whether a circuit satisfies a temporal property or not. Typically, such a property is formulated as an implication. In the antecedent of the property the verification engineer specifies the assumptions about the design environment and joins the respective expressions by logical AND. However, the overall conjunction may have no solution, i.e. the antecedent is contradictory. Since in this case a property trivially holds this situation has to be avoided. Furthermore, the root cause of a contradictory antecedent has to be identified which is a manual and very time-consuming process. In this paper we propose a fully automatic approach for presenting all reasons of a contradictory antecedent to the verification engineer, i.e. the approach pinpoints to the sub-expressions in the antecedent that form a contradiction. Hence, our approach reduces the debugging time of a contradictory antecedent significantly.
General Regression Neural Network Optimization for Handwritten Persian Digits recognition Using Particle Swarm Optimization

In this paper an optimization algorithm based on Particle Swarm Optimization algorithm is used for handwritten Persian digits recognition with General Regression Neural Network . The system uses image zoning for the digit recognition. General Regression Neural Network accuracy depends on the centers and widths of the hidden layer neuron basis functions (neuron spread). In this paper we use Particle Swarm Optimization algorithm to determine General Regression Neural Network hidden layer spread. Results show that the optimized General Regression Neural Network provides higher recognition ability compared with that of unoptimized General Regression Neural Network.
Where is ...? Learning and Utilizing Motion Patterns of Persons with Mobile Robots

Whenever people move through their environments they do not move randomly. Instead, they usually follow specific trajectories or motion patterns corresponding to their intentions. Knowledge about such patterns may enable a mobile robot to robustly keep track of persons in its environment or to improve its obstacle avoidance behavior. This paper proposes a technique for learning collections of trajectories that characterize typical motion patterns of persons. Data recorded with laser-range finders is clustered using the expectation maximization algorithm. Based on the result of the clustering process we derive a Hidden Markov Model (HMM). This HMM is able to estimate the current and future positions of multiple persons given knowledge about their intentions. Experimental results obtained with a mobile robot using laser and vision data collected in a typical office building with several persons illustrate the reliability and robustness of the approach. We also demonstrate that our model provides better estimates than an HMM directly learned from the data.
Exploiting the Wikipedia structure in local and global classification of taxonomic relations*

Abstract Determining whether two terms have an ancestor relation (e.g. Toyota Camry and car) or a sibling relation (e.g. Toyota and Honda) is an essential component of textual inference in Natural Language Processing applications such as Question Answering, Summarization, and Textual Entailment. Significant work has been done on developing knowledge sources that could support these tasks, but these resources usually suffer from low coverage, noise, and are inflexible when dealing with ambiguous and general terms that may not appear in any stationary resource, making their use as general purpose background knowledge resources difficult. In this paper, rather than building a hierarchical structure of concepts and relations, we describe an algorithmic approach that, given two terms, determines the taxonomic relation between them using a machine learning-based approach that makes use of existing resources. Moreover, we develop a global constraint-based inference process that leverages an existing knowledge base to enforce relational constraints among terms and thus improves the classifier predictions. Our experimental evaluation shows that our approach significantly outperforms other systems built upon the existing well-known knowledge sources.
Telecare, Remote Monitoring and Care

Telecare is often regarded as a win/win solution to the growing problem of meeting the care needs of an ageing population. In this paper we call attention to some of the ways in which telecare is not a win/win solution but rather aggravates many of the long-standing ethical tensions that surround the care of the elderly. It may reduce the call on carers' time and energy by automating some aspects of care, particularly daily monitoring. This can release carers for other caring activities. On the other hand, remote and impersonal monitoring seems to fall short of providing care. Monitoring may be used to help elderly users retain independence. But it may also increase the amount of information which flows from users to carers, which can result in a form of function-creep that actually undermines independence.
Nano-Indentation of Copper – Nickel thin films -A Molecular Dynamics Simulation Study

Nanostructured materials have attracted many attentions and have been the subject of intensive research in recent years because they possess novel and/or enhanced mechanical properties compared with coarse grained materials. These enhanced mechanical properties of nanomaterial are an important subject of Nano-mechanics research. When brought into a bulk scale, nanoparticles can strongly affect the mechanical properties of the material, like stiffness or elasticity. The mechanical behaviour of very small volumes differs from what is typically observed on the macro level. In particular, thin metal films with nanometer-sized coatings possess interesting mechanical properties. Here, we have used molecular dynamics simulations to elucidate effect of Ni-thickness, effect of loading rate, effect of temperature on load-displacement behaviour during nanoindentation of thin copper films with nickel coatings. After simulation is being performed several deformation mechanisms, such as pile-up of dislocation at the interface, edge dislocation slip lines are observed. Most interestingly, the underlying copper films or substrates are significantly strengthened by thin nickel coatings. The strengthening effect is more pronounced at a low temperature.
Effects of Rapamycin Treatment on Neurogenesis and Synaptic Reorganization in the Dentate Gyrus after Controlled Cortical Impact Injury in Mice

Post-traumatic epilepsy (PTE) is one consequence of traumatic brain injury (TBI). A prominent cell signaling pathway activated in animal models of both TBI and epilepsy is the mammalian target of rapamycin (mTOR). Inhibition of mTOR with rapamycin has shown promise as a potential modulator of epileptogenesis in several animal models of epilepsy, but cellular mechanisms linking mTOR expression and epileptogenesis are unclear. In this study, the role of mTOR in modifying functional hippocampal circuit reorganization after focal TBI induced by controlled cortical impact (CCI) was investigated. Rapamycin (3 or 10 mg/kg), an inhibitor of mTOR signaling, was administered by intraperitoneal injection beginning on the day of injury and continued daily until tissue collection. Relative to controls, rapamycin treatment reduced dentate granule cell area in the hemisphere ipsilateral to the injury two weeks post-injury. Brain injury resulted in a significant increase in doublecortin immunolabeling in the dentate gyrus ipsilateral to the injury, indicating increased neurogenesis shortly after TBI. Rapamycin treatment prevented the increase in doublecortin labeling, with no overall effect on Fluoro-Jade B staining in the ipsilateral hemisphere, suggesting that rapamycin treatment reduced posttraumatic neurogenesis but did not prevent cell loss after injury. At later times post-injury (8–13 weeks), evidence of mossy fiber sprouting and increased recurrent excitation of dentate granule cells was detected, which were attenuated by rapamycin treatment. Rapamycin treatment also diminished seizure prevalence relative to vehicle-treated controls after TBI. Collectively, these results support a role for adult neurogenesis in PTE development and suggest that suppression of epileptogenesis by mTOR inhibition includes effects on post-injury neurogenesis.