Miracle-dz/UniFAR-FTUs huggingface dataset:
METHODS FOR ACCELERATING DYNAMIC DURABILITY TESTS

Vibrating components are highly susceptible to fatigue failure. Fatigue occurs through long term exposure to time varying loads which although modest in amplitude give rise to microscopic cracks that steadily propagate to failure. Most components must fulfil some form of durability certification test prior to production. Tests are conducted on real prototype components or use a CAE based simulation of the component. It is seldom possible to use real service loads so engineers require a reduced specification that is still representative of the operational environment. For many years this was addressed through experience; however, it has often led to unnecessary over-design or operational failures. In this paper we pursue a more scientific route and review the topic of Mission Profiling and Test Synthesis. A ‘route map’ is presented to guide the reader towards the optimal test solution.
Positive interpretation bias predicts well-being in medical interns

Cognitive theories of emotion posit that affective responses may be shaped by how individuals interpret emotion-eliciting situations. This study tested whether individual differences in interpretation bias (i.e., interpreting ambiguous scenarios in a more negative or positive manner) independently predict trait resilience and depression in medical interns. Interpretation bias and trait resilience scores were assessed in 47 interns prior to their first internship. Depressive symptoms were assessed twice during internship. Nearly half of the sample (42%) scored above the cut-off for mild depressive symptoms during internship, a significant rise compared to the initial assessment. Those with a more positive interpretation bias had higher trait resilience (β = 0.44, p = 0.004) and a 6-fold decreased depressive symptom risk during internship (OR = 6.41, p = 0.027). The predictive power of a positive interpretation bias for decreased depression symptoms held over and above initial depressive symptoms, demographics and trait reappraisal. Assessing positive interpretation bias may have practical utility for predicting future well-being in at risk-populations.
Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering

This paper provides algorithms to fuse relative and absolute microelectromechanical systems (MEMS) navigation sensors, suitable for micro planetary rovers, to provide a more accurate estimation of navigation information, specifically, attitude and position. Planetary rovers have extremely slow speed (~1 cm/s) and lack conventional navigation sensors/systems, hence the general methods of terrestrial navigation may not be applicable to these applications. While relative attitude and position can be tracked in a way similar to those for ground robots, absolute navigation information is hard to achieve on a remote celestial body, like Moon or Mars, in contrast to terrestrial applications. In this study, two absolute attitude estimation algorithms were developed and compared for accuracy and robustness. The estimated absolute attitude was fused with the relative attitude sensors in a framework of nonlinear filters. The nonlinear Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) were compared in pursuit of better accuracy and reliability in this nonlinear estimation problem, using only on-board low cost MEMS sensors. Experimental results confirmed the viability of the proposed algorithms and the sensor suite, for low cost and low weight micro planetary rovers. It is demonstrated that integrating the relative and absolute navigation MEMS sensors reduces the navigation errors to the desired level.
A Graph-Coarsening Approach for Tag Recommendation

In this paper we propose a new graph-based tag recommendation approach. The approach is structured into an offline step and an online one. Offline, the hypergraph depicting the history of tags assignment by users to resources is abstracted. On online, for a given target user and a resource, we first compute the set of recommended abstract tags (i.e tag clusters) applying a basic graph-based approach to the abstract graph. A new reduced graph is computed by unfolding the abstract subgraph composed of the set of recommended abstract tags and nodes representing the cluster of users (resp. resources) to which the target user (resp. resource) belongs to. Again the same basic graph-based tag recommendation approach is applied to this new reduced graph in order to compute the final set of tags to recommend. Experiments on real dataset show the effectiveness of the proposed approach.
THE IMPACT OF PHORBOL ESTER ON THE REGULATION OF AMILORIDE-SENSITIVE EPITHELIAL SODIUM CHANNEL IN ALVEOLAR TYPE II EPITHELIAL CELLS

Amiloride-sensitive sodium channel (ENaC) plays an important role in recovery from pulmonary edema. Recently, it has been shown that an activation of protein kinase C (PKC) could affect the mRNA expression of ENaC in rat parotid gland cells and A6 distal nephron epithelial cells. To determine whether an activation of PKC would regulate the mRNA expression or the function of ENaC, we stimulated rat alveolar type II epithelial cells with phorbol 12-myristate 13-acetate (PMA), a potent PKC activator, at a concentration of 100 nM. The mRNA expression of α -, β -, and γ -ENaC subunits and amiloride-sensitive current were measured. PMA inhibited the mRNA expression of all 3 ENaC subunits (α -ENaC: 56.0% ± 12.1%; β -ENaC: 62.6% ± 15.9%; γ -ENaC: 68.5% ± 10.6%, respectively) and amiloride-sensitive current (control = 7.0 ± 1.5 μ A/cm 2 ; PMA = 1.7 ± 0.9 μ A/cm 2) significantly at 24 hours. On the other hand, 4 α -phorbol didecanoate 4 α -PDD, inactive form of PMA, had no inhibitory effect on α - and γ -ENaC expression or amiloride-sensitive current. However, no significant difference was seen in β -ENaC expression between PMA and 4 α -PDD. GF 109203X, a wide-range PKC inhibitor, blocked the inhibitory effect of PMA on all ENaC subunits mRNA expression. These results suggest that an activation of PKC may play an important role in the regulation of ENaC mRNA expression and function.
An Optimal Cross-Layer Framework for Cognitive Radio Network Under Interference Temperature Model

This paper investigates the optimal scheduling of cognitive radio network links under an interference temperature (IT) model. A link layer model based on the IT model has been developed. A mathematical cross-layered model for the cognitive radio network link scheduling problem under the IT model is presented. The proposed cross-layered model optimizes the performance of the cognitive radio network across several network layers. The objective is to activate as many simultaneous primary/secondary links while the IT constraints are satisfied. The IT-based link layer scheduling can potentially increase the network performance. The proposed model advocates the potential benefits of adopting a location-aware and IT-based MAC protocol in modern wireless networks.
Genetic consequences of population expansions and contractions in the common hippopotamus (Hippopotamus amphibius) since the Late Pleistocene

Over the past two decades, an increasing amount of phylogeographic work has substantially improved our understanding of African biogeography, in particular the role played by Pleistocene pluvial–drought cycles on terrestrial vertebrates. However, still little is known on the evolutionary history of semi‐aquatic animals, which faced tremendous challenges imposed by unpredictable availability of water resources. In this study, we investigate the Late Pleistocene history of the common hippopotamus (Hippopotamus amphibius), using mitochondrial and nuclear DNA sequence variation and range‐wide sampling. We documented a global demographic and spatial expansion approximately 0.1–0.3 Myr ago, most likely associated with an episode of massive drainage overflow. These events presumably enabled a historical continent‐wide gene flow among hippopotamus populations, and hence, no clear continental‐scale genetic structuring remains. Nevertheless, present‐day hippopotamus populations are genetically disconnected, probably as a result of the mid‐Holocene aridification and contemporary anthropogenic pressures. This unique pattern contrasts with the biogeographic paradigms established for savannah‐adapted ungulate mammals and should be further investigated in other water‐associated taxa. Our study has important consequences for the conservation of the hippo, an emblematic but threatened species that requires specific protection to curtail its long‐term decline.
Local and global sparse Gaussian process approximations

Gaussian process (GP) models are flexible probabilistic nonparametric models for regression, classification and other tasks. Unfortunately they suffer from computational intractability for large data sets. Over the past decade there have been many different approximations developed to reduce this cost. Most of these can be termed global approximations, in that they try to summarize all the training data via a small set of support points. A different approach is that of local regression, where many local experts account for their own part of space. In this paper we start by investigating the regimes in which these different approaches work well or fail. We then proceed to develop a new sparse GP approximation which is a combination of both the global and local approaches. Theoretically we show that it is derived as a natural extension of the framework developed by Quinonero Candela and Rasmussen [2005] for sparse GP approximations. We demonstrate the benefits of the combined approximation on some 1D examples for illustration, and on some large real-world data sets.
Statistical Identification of English Loanwords in Korean Using Automatically Generated Training Data

This paper describes an accurate, extensible method for automatically classifying unknown foreign words that requires minimal monolingual resources and no bilingual training data (which is often difficult to obtain for an arbitrary language pair). We use a small set of phonologically-based transliteration rules to generate a potentially unlimited amount of pseudo-data that can be used to train a classifier to distinguish etymological classes of actual words. We ran a series of experiments on identifying English loanwords in Korean, in order to explore the consequences of using pseudo-data in place of the original training data. Results show that a sufficient quantity of automatically generated training data, even produced by fairly low precision transliteration rules, can be used to train a classifier that performs within 0.3% of one trained on actual English loanwords (96% accuracy).
Memory system connectivity exploration

In programmable embedded systems, the memory subsystem represents a major cost, performance and power bottleneck. To optimize the system for such different goals, the designer would like to perform Design Space Exploration, evaluating different memory modules from a memory IP library, and selecting the most promising designs. However while the memory modules are important, the rate at which the memory system can produce the data for the CPU is significantly impacted by the connectivity architecture between the memory subsystem and the CPU. Thus, it is critical go consider the connectivity architecture early in the design flow, in conjunction with the memory architecture. We present a connectivity architecture exploration approach, evaluating a wide range of cost, performance, and energy connectivity architectures. When coupled with our memory modules exploration approach, we can significantly improve the system behavior We present experiments on a set of large real-life benchmarks, showing significant performance improvements for varied cost and power characteristics, allowing the designer to tailor the performance, cost and power of the programmable embedded system.
On modeling software architecture recovery as graph matching

This paper presents a graph matching model for the software architecture recovery problem. Because of their expressiveness, the graphs have been widely used for representing both the software system and its high-level view, known as the conceptual architecture. Modeling the recovery process as graph matching is an attempt to identify a sub-optimal transformation from a pattern graph, representing the high-level view of the system, onto a subgraph of the software system graph. A successful match yields a restructured system that conforms to the given pattern graph. A failed match indicates the points where the system violates specific constraints. The pattern graph generation and the incrementality of the recovery process are the important issues to be addressed. The approach is evaluated through case studies using a prototype toolkit that implements the proposed interactive recovery environment.
Ship Heading Control with Speed Keeping via a Nonlinear Disturbance Observer

The control problem for a ship steering system with speed loss is discussed in this paper. Two methods are proposed to deal with the unknown bounded disturbance for a sliding mode controller applied to a nonlinear surface vessel heading control system. The system uncertainties caused by speed changes are taken as internal disturbances, while the wave moments are considered as external disturbances. A feedback linearization method is adopted to simplify the nonlinear system. An adaptive method and a Nonlinear Disturbance Observer (NDO) are proposed for course keeping manoeuvres and speed keeping in vessel steering and provide robust performance for time varying wave disturbance and actuator dynamics. Furthermore, the overall stability conditions of the proposed controllers are analysed by Lyapunov's direct method. Finally, simulation results using the characteristics of a naval vessel illustrate the effectiveness of the presented control algorithms.
Transdermal Influenza Immunization with Vaccine-Coated Microneedle Arrays

Background Influenza is a contagious disease caused by a pathogenic virus, with outbreaks all over the world and thousands of hospitalizations and deaths every year. Due to virus antigenic drift and short-lived immune responses, annual vaccination is required. However, vaccine coverage is incomplete, and improvement in immunization is needed. The objective of this study is to investigate a novel method for transdermal delivery using metal microneedle arrays (MN) coated with inactivated influenza virus to determine whether this route is a simpler and safer approach than the conventional immunization, capable to induce robust immune responses and confer protection against lethal virus challenge. Methodology/Principal Findings Inactivated A/Aichi/2/68 (H3N2) influenza virus was coated on metal microneedle arrays and applied to mice as a vaccine in the caudal dorsal skin area. Substantial antibody titers with hemagglutination inhibition activity were detected in sera collected two and four weeks after a single vaccine dose. Challenge studies in mice with 5×LD50 of mouse adapted Aichi virus demonstrated complete protection. Microneedle vaccination induced a broad spectrum of immune responses including CD4+ and CD8+ responses in the spleen and draining lymph node, a high frequency of antigen-secreting cells in the lung and induction of virus-specific memory B-cells. In addition, the use of MN showed a dose-sparing effect and a strong Th2 bias when compared to an intramuscular (IM) reference immunization. Conclusions/Significance The present results show that delivery of inactivated influenza virus through the skin using metal microneedle arrays induced strong humoral and cellular immune responses capable of conferring protection against virus challenge as efficiently as intramuscular immunization, which is the standard vaccination route. In view of the convenience of delivery and the potential for self-administration, vaccine-coated metal microneedles may provide a novel and highly effective immunization method.
Dissociation of centrosome replication events from cycles of DNA synthesis and mitotic division in hydroxyurea-arrested Chinese hamster ovary cells

Relatively little is known about the mechanisms used by somatic cells to regulate the replication of the centrosome complex. Centrosome doubling was studied in CHO cells by electron microscopy and immunofluorescence microscopy using human autoimmune anticentrosome antiserum, and by Northern blotting using the cDNA encoding portion of the centrosome autoantigen pericentriolar material (PCM)-1. Centrosome doubling could be dissociated from cycles of DNA synthesis and mitotic division by arresting cells at the G1/S boundary of the cell cycle using either hydroxyurea or aphidicolin. Immunofluorescence micros-copy using SPJ human autoimmune anticentrosome antiserum demonstrated that arrested cells were able to undergo numerous rounds of centrosome replication in the absence of cycles of DNA synthesis and mitosis. Northern blot analysis demonstrated that the synthesis and degradation of the mRNA encoding PCM-1 occurred in a cell cycle-dependent fashion in CHO cells with peak levels of PCM-1 mRNA being present in G1 and S phase cells before mRNA amounts dropped to undetectable levels in G2 and M phases. Conversely, cells arrested at the G1/S boundary of the cell cycle maintained PCM-1 mRNA at artificially elevated levels, providing a possible molecular mechanism for explaining the multiple rounds of centrosome replication that occurred in CHO cells during prolonged hydroxyurea-induced arrest. The capacity to replicate centrosomes could be abolished in hydroxyurea-arrested CHO cells by culturing the cells in dialyzed serum. However, the ability to replicate centrosomes and to synthesize PCM-1 mRNA could be re- initiated by adding EGF to the dialyzed serum. This experimental system should be useful for investigating the positive and negative molecular mechanisms used by somatic cells to regulate the replication of centrosomes and for studying and the methods used by somatic cells for coordinating centrosome duplication with other cell cycle progression events.
Dietary Calcium Intake, Vitamin D Status, and Bone Health in Postmenopausal Women in Rural Pakistan

The high prevalence of osteoporosis in Pakistan is of public-health concern. However, there is a paucity of information regarding nutrition and bone density in rural communities. The purpose of this study was to evaluate the dietary and lifestyle factors that impact bone health in Nahaqi. Data were collected from 140 postmenopausal women using an interviewer-administered 24-hour dietary recall questionnaire. Bone mineral density was estimated using the quantitative ultrasound index (QUI). Serum 25(OH)D was measured in fasting blood samples. The QUI scores revealed that 42% and 29% of the women had T-scores, indicative of osteopaenia and osteoporosis respectively. The mean calcium intake was 346 mg/d, which is less than 50% of the recommended daily intake. The QUI correlated with 25(OH)D after controlling for age (p=0.021, r=0.41, r2=0.168). Vitamin D deficiency and low intake of dietary calcium are two key factors contributing to poor bone health in this population.
Late reionizations of the Universe and their manifestation in the WMAP and future Planck data

We investigate two sets of two-epoched reionization models and their manifestation in the CMB anisotropy and polarization data of the recent WMAP project and make some predictions for the future Planck missions. In the first set of models, the universe was reionized twice, first at z ≃ 15 by population III stars and then at z ≃ 6 by stars in large galaxies. In the second set of models, the extra peak-like reionization at high redshifts z > 100 is induced by the decay of unstable particles, followed by the standard picture of reionization at z ≃ 6. We examine the general properties of these two-epoched reionization models and their implication in the WMAP CMB temperature anisotropy-polarization cross-correlation. We have shown that these models have comparable likelihood values for the WMAP data and distinct characters which can be tested with the Planck high sensitivities.
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo

We present a novel approach for fully non-stationary Gaussian process regression (GPR), where all three key parameters -- noise variance, signal variance and lengthscale -- can be simultaneously input-dependent. We develop gradient-based inference methods to learn the unknown function and the non-stationary model parameters, without requiring any model approximations. We propose to infer full parameter posterior with Hamiltonian Monte Carlo (HMC), which conveniently extends the analytical gradient-based GPR learning by guiding the sampling with model gradients. We also learn the MAP solution from the posterior by gradient ascent. In experiments on several synthetic datasets and in modelling of temporal gene expression, the nonstationary GPR is shown to be necessary for modeling realistic input-dependent dynamics, while it performs comparably to conventional stationary or previous non-stationary GPR models otherwise.
Electrical Network Frequency as a Tool for Audio Concealment Process

We live in a digital era. Digital contents may be produced by digital equipments or by converting old analog recordings. With the rapid growth of digital contents, digital archiving technology is demanded. Different types of contents require different processing techniques. In this paper, we focus on digital audio contents. The related techniques, such as forensics, authentication, and error concealment, were studied. When converting audio tapes to digital files, sometimes a certain automatic error detection and concealment is needed. However, traditional audio tapes were recorded without any error recovery information. Based on the restriction, we proposed a scheme that incorporates the electrical network frequency (ENF) as a tool for detecting damaged audio segments. The goal is to help people identifying candidate concealment segments. When using in an archiving application, it reduces the manpower as well as increases the accuracy of the generated meta-data.
Asia–Latin America as Method: The Global South Project and the Dislocation of the West

Abstract:By approaching Asian and Latin American relations not only as a research object but as an epistemic framework, this article sheds light on the ways in which the figure of the “West,” even in its apparent absence, continues to govern and structure periphery-to-periphery encounters. It contends that in order to forge the project of the Global South, the unequal power relations, cacophonies, and contradictions that characterize Asian and Latin American relations must be examined. The article's use of Asia–Latin America as method enables new perspectives on epistemic violence and the politics of knowledge as well as a fundamental reassessment of the workings of culture, race, economy, globality, geopolitics, and biopolitics.
Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons: a Review

Dynamics of the membrane potential in a single neuron can be studied by estimating biophysical parameters from intracellular recordings. Diffusion processes, given as continuous solutions to stochastic differential equations, are widely applied as models for the neuronal membrane potential evolution. One-dimensional models are the stochastic integrate-and-fire neuronal diffusion models. Biophysical neuronal models take into account the dynamics of ion channels or synaptic activity, leading to multidimensional diffusion models. Since only the membrane potential can be measured, this complicates the statistical inference and parameter estimation from these partially observed detailed models. This paper reviews parameter estimation techniques from intracellular recordings in these diffusion models.