Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection and Monitoring of Fatigue Cracks in Metallic Structures Using Acoustic Emission: Routes to Quantification of Probability of Detection

The performance and reliability of Structural Health Monitoring (SHM) techniques remain largely unquantified. This is in contrast to the probability of detection (POD) and sensitivity of manual non destructive inspection methods which are well characterised. In this study factors influencing the rates of emission of Acoustic Emission (AE) signals from propagating fatigue cracks were investigated. Fatigue crack growth experiments were performed in 2014 T6 aluminium sheet to observe the effects of changes in crack length, loading spectrum and sample geometry on rates of emission and the probability of detecting and locating the fatigue crack. Significant variation was found in the rates of AE signal generation during crack progression from initiation to final failure. AE signals at any point in the failure process were found to result from different failure mechanisms operating at particular stages in the failure process.
Tailoring the size in colloidal iron oxide magnetic nanoparticles

Colloidal iron oxide magnetic nanoparticles were synthesized from high temperature reaction of Fe(acac)3 solution. The size of particles was easily tunable from 4 to 22 nm in only one step in the synthesis process. From TEM images the particles showed cubic–faceted shape with good homogeneity and narrow size distribution. Preliminary magnetic measurements show the usual superparamagnetic and blocked regimes depending on temperature.
The C2-domain protein QUIRKY and the receptor-like kinase STRUBBELIG localize to plasmodesmata and mediate tissue morphogenesis in Arabidopsis thaliana

Tissue morphogenesis in plants requires communication between cells, a process involving the trafficking of molecules through plasmodesmata (PD). PD conductivity is regulated by endogenous and exogenous signals. However, the underlying signaling mechanisms remain enigmatic. In Arabidopsis, signal transduction mediated by the receptor-like kinase STRUBBELIG (SUB) contributes to inter-cell layer signaling during tissue morphogenesis. Previous analysis has revealed that SUB acts non-cell-autonomously suggesting that SUB controls tissue morphogenesis by participating in the formation or propagation of a downstream mobile signal. A genetic screen identified QUIRKY (QKY), encoding a predicted membrane-anchored C2-domain protein, as a component of SUB signaling. Here, we provide further insight into the role of QKY in this process. We show that like SUB, QKY exhibits non-cell-autonomy when expressed in a tissue-specific manner and that non-autonomy of QKY extends across several cells. In addition, we report on localization studies indicating that QKY and SUB localize to PD but independently of each other. FRET-FLIM analysis suggests that SUB and QKY are in close contact at PD in vivo. We propose a model where SUB and QKY interact at PD to promote tissue morphogenesis, thereby linking RLK-dependent signal transduction and intercellular communication mediated by PD.
Genetic analysis reveals promiscuity among female cheetahs

Cheetahs (Acinonyx jubatus) have a combination of ranging patterns and social system that is unique in mammals, whereby male coalitions occupy small territories less than 10% of the home range of solitary females. This study uses non-invasive genetic sampling of a long-term study population of cheetah in the Serengeti National Park in Tanzania to infer the mating system. Individual cheetah genotypes at up to 13 microsatellite loci were obtained from 171 faecal samples. A statistical method was adapted to partition the cubs within each litter (n=47) into full-sibling clusters and to infer the father of each cluster using these loci. Our data showed a high rate of multiple paternity in the population; 43% of litters with more than one cub were fathered by more than one male. The results also demonstrated that female fidelity was low, and provided some evidence that females chose to mate with unrelated males within an oestrus cycle. The low rate of paternity assignments indicated that males living outside the study area contributed substantially to the reproduction of the cheetah population.
Window materials for 110-GHz and 280-GHz gyrotron

At higher frequencies it is not easy to find a suitable material for output window applications in a high power gyrotron. The room temperature application of sapphire as a window material at higher frequencies is not feasible since its absorption coefficient increases almost linearly with increasing frequency in the millimeter wavelength region. At cryogenic temperature the absorption coefficient value decreases only by a few factors (factor of 2 to 3) in the 90-200 GHz region. The earlier reported temperature squared dependence (decrease) in the absorption coefficient of the loss tangent value is totally absent in our broad band continuous wave data we are reporting here (at 6.5 K, 35 K, 77 K, and 300 K). We utilize our precision millimeter wave dispersive Fourier transform spectroscopic techniques at room temperature and at cryogenic temperatures. The extra high resistivity single crystal compensated silicon is no doubt the lowest loss material available at room temperature in the entire millimeter wavelength region. At higher millimeter wave frequencies an extra high resistivity silicon window or a window made with extra high resistivity silicon coated with diamond film would certainly make a better candidate in the future. A single free standing synthetic diamond window seems to have higher absorption coefficient values at millimeter wavelength region at this time although it is claimed that it possesses good mechanical strength and higher thermal conductivity characteristics. It certainly does not rule out the use of diamond film on a single crystal high resistivity silicon to improve its mechanical strength and thermal conductivity.
Sketch-based indexing of n-words

Formulating and processing phrases and other term dependencies to improve query effectiveness is an important problem in information retrieval. However, accessing these types of statistics using standard inverted indexes requires unreasonable processing time or incurs a substantial space overhead. Establishing a balance between these competing space and time trade-offs can dramatically improve system performance. In this paper, we present and analyze a new index structure designed to improve query efficiency in term dependency retrieval models, with bounded space requirements. By adapting a class of (ε,δ)-approximation algorithms originally proposed for sketch summarization in networking applications, we show how to accurately estimate various statistics important in term dependency models with low, probabilistically bounded error rates. The space requirements of the sketch index structure is largely independent of this size and the number of phrase term dependencies. Empirically, we show that the sketch index can reduce the space requirements of the vocabulary component of an index of all n-grams consisting of between 1 and 5 words extracted from the Clueweb-Part-B collection to less than 0.2% of the requirements of an equivalent full index. We show that n-gram queries of 5 words can be processed more efficiently than in current alternatives, such as next-word indexes. We show retrieval using the sketch index to be up to 400 times faster than with positional indexes, and 15 times faster than next-word indexes.
Quantification of ergosterol and 3-hydroxy fatty acids in settled house dust by gas chromatography-mass spectrometry: comparison with fungal culture and determination of endotoxin by a Limulus amebocyte lysate assay

Ergosterol and 3-hydroxy fatty acids, chemical markers for fungal biomass and the endotoxin of gram-negative bacteria, respectively, may be useful in studies of health effects of organic dusts, including domestic house dust. This paper reports a method for the combined determination of ergosterol and 3-hydroxy fatty acids in a single dust sample and a comparison of these chemical biomarkers determined by gas chromatography-mass spectrometry with results from fungal culture and Limulus assay. Analyses of replicate house dust samples resulted in correlations of 0.91 (ergosterol in six replicates; P < 0.01) and 0.94 (3-hydroxy fatty acids in nine replicates; P < 0.001). The amounts of ergosterol (range, 2 to 16.5 ng/mg of dust) correlated with those of total culturable fungi (range, 6 to 1,400 CFU/mg of dust) in 17 samples, (r = 0.65; P < 0.005). The amounts of endotoxin (range, 11 to 243 endotoxin units/mg of dust) measured with a modified chromogenic Limulus assay correlated with those of lipopolysaccharide (LPS) determined from 3-hydroxy fatty acid analysis of 15 samples. The correlation coefficient depended on the chain lengths of 3-hydroxy acids used to compute the LPS content. The correlation was high (r = 0.88 +/- 0.01; P < 0.001) when fatty acid chains of 10 to 14 carbon atoms were included; the correlation was much lower when hydroxy acids of 16- or 18-carbon chains were included. In conclusion, the results of the described extraction and analysis procedure for ergosterol and 3-hydroxy fatty acids are reproducible, and the results can be correlated with fungal culture and endotoxin activity of organic dust samples.
Systems-Level Modeling of Cancer-Fibroblast Interaction

Cancer cells interact with surrounding stromal fibroblasts during tumorigenesis, but the complex molecular rules that govern these interactions remain poorly understood thus hindering the development of therapeutic strategies to target cancer stroma. We have taken a mathematical approach to begin defining these rules by performing the first large-scale quantitative analysis of fibroblast effects on cancer cell proliferation across more than four hundred heterotypic cell line pairings. Systems-level modeling of this complex dataset using singular value decomposition revealed that normal tissue fibroblasts variably express at least two functionally distinct activities, one which reflects transcriptional programs associated with activated mesenchymal cells, that act either coordinately or at cross-purposes to modulate cancer cell proliferation. These findings suggest that quantitative approaches may prove useful for identifying organizational principles that govern complex heterotypic cell-cell interactions in cancer and other contexts.
Summary of Current Work on Active Learning

In this draft, we summarize the approaches that have been proposed and studied for active learning in the past. It was proposed in the late 1980s [2, 4]. The main idea to selectively choose examples for soliciting labels such that the number of examples required labeling can be reduced dramatically. In the following, we will first review the list of theories and algorithms that have been proposed and studied for active learning, followed by the discussion of applications of active learning.
Cloud Computing Model without Resource Management Center

Cloud computing, as an emerging computing model, is attracting more and more attention of industry and academia. Though it is of significant importance to carry out studies on such programming models, so far, there are few programming models for cloud computing. Because various kinds of cloud platforms are developed independently, it is necessary to have the support of cloud platform in making cloud programming model be able to deploy application to the cloud. This paper takes the cloud platform as its center. The cloud computing model in this paper is proposed as the Cloud platform, which is a kind of distributed structure without central management node. Each cloud node has equal status and manages its local resources respectively. In addition, this paper proposes mechanisms for resource management and allocation as well as the organizational structure of the user virtual machine.
Network State Classification Based on the Statistical Properties of RTT for an Adaptive Multi-State Proactive Transport Protocol for Satellite Based Networks

This paper attempts to establish the fact that Multi State Network Classification is essential for performance enhancement of Transport protocols over Satellite based Networks. A model to classify Multi State network condition taking into consideration both congestion and channel error is evolved. In order to arrive at such a model an analysis of the impact of congestion and channel error on RTT values has been carried out using ns2. The analysis results are also reported in the paper. The inference drawn from this analysis is used to develop a novel statistical RTT based model for multi state network classification. An Adaptive Multi State Proactive Transport Protocol consisting of Proactive Slow Start, State based Error Recovery, Timeout Action and Proactive Reduction is proposed which uses the multi state network state classification model. This paper also confirms through detail simulation and analysis that a prior knowledge about the overall characteristics of the network helps in enhancing the performance of the protocol over satellite channel which is significantly affected due to channel noise and congestion. The necessary augmentation of ns2 simulator is done for simulating the multi state network classification logic. This simulation has been used in detail evaluation of the protocol under varied levels of congestion and channel noise. The performance enhancement of this protocol with reference to established protocols namely TCP SACK and Vegas has been discussed. The results as discussed in this paper clearly reveal that the proposed protocol always outperforms its peers and show a significant improvement in very high error conditions as envisaged in the design of the protocol. The protocol is also evaluated to have very good fairness property under different error conditions .
FUZZY BASED PREPROCESSING USING FUSION OF ONLINE AND OFFLINE TRAIT FOR ONLINE URDU SCRIPT BASED LANGUAGES CHARACTER RECOGNITION

Character recognition has been fascinating and intenseeld of pattern recog- nition research since early days of computer. This task becomes more challenging when it involves Urdu script based languages especially written in handwritten Nasta'liq font due to the large variations and complexity of the script. Fuzzy logic is an important tool to deal with vague, incomplete, noisy and contradictory information. In order to make handwritten communication with machine more natural, we propose several preprocessing steps for handwritten online Urdu script character recognition to overcome the issue in raw input. We present fuzzy based several preprocessing operations in order to normalize the handwritten stroke using both online and offline domain. The proposed technique is also the necessary step towards character recognition, person identication, personality determination where input data are processed from all perspectives. Keywords: Preprocessing, Baseline, Slant correction, Character recognition, Smooth- ing, Urdu, Nasta'liq, Naskh
The Failed Posterior Lumbar Interbody Fusion

The problems presented by unsuccessful posterior lumbar interbody fusion (PLIF) have not been addressed. The cases of 12 patients who presented with failed PLIF were reviewed. Five patients were male and seven female (age range, 24-50 years; mean age, 40 years). All patients underwent at least one PLIF; many had undergone other procedures. A total of 37 procedures had been performed on the 12 patients. Chronic radiculopathy was present in all patients, as detected with electromyographic or nerve conduction velocity examination. At the time of reconstructive surgery, in the 11 patients in whom the canal was explored, all had extensive epidural fibrosis. Nine of the 12 patients had pseudarthrosis of the previous PLIF. Four patients had evidence of motion segment dysfunction at nearby levels: two had positive discograms adjacent to the PLIFs; one developed a facet syndrome at L5-S1, caudal to an L4-5 PLIF; and one demonstrated frank segmental instability at L2-3, cranial to a previous PLIF at L3-4. Twelve patients underwent a total of 22 procedures after referral. Eleven patients initially underwent decompression and fusion, and one patient underwent a sympathectomy. Seven patients underwent an additional 10 procedures, including repeat decompression, repair of pseudarthrosis, and implantation of an epidural analgesic pump system. After all surgical treatment, five patients rated their pain as improved. Seven patients were thought to have a solid fusion. The presence of a solid fusion did not correlate with satisfactory relief of pain (chi-square). Continued extremity pain was the predominant complaint of all the patients. Two shortcomings of the PLIF were evident. The first was biomechanical: Adjacent unfused segments became symptomatic in four patients. The second problem was one of chronic radiculopathy, on the basis of extensive epineural and endoneural fibrosis provoked by the more extensive epidural manipulation required by the PLIF. The first problem, mechanical dysfunction, can be addressed by stabilization with rigid internal fixation. However, the clinical utility of this is thus far unclear. For the second and major symptomatic problem, chronic radiculopathy, there is currently no good solution.
The effect of helium–oxygen‐assisted mechanical ventilation on chronic obstructive pulmonary disease exacerbation: A systemic review and meta‐analysis

Chronic obstructive pulmonary disease (COPD) is often accompanied by acute exacerbations. Patients of COPD exacerbation suffering from respiratory failure often need the support of mechanical ventilation. Helium–oxygen can be used to reduce airway resistance during mechanical ventilation. The aim of this study is to evaluate the effect of helium–oxygen‐assisted mechanical ventilation on COPD exacerbation through a meta‐analysis.
Bootstrap feature selection in support vector machines for ventricular fibrillation detection

Support Vector Machines (SVM) for classification are be- ing paid special attention in a number of practical applications. When using nonlinear Mercer kernels, the mapping of the input space to a high- dimensional feature space makes the input feature selection a difficult task to be addressed. In this paper, we propose the use of nonparametric boot- strap resampling technique to provide with a statistical, distribution inde- pendent, criterion for input space feature selection. The confidence interval of the difference of error probability between the complete input space and a reduced-in-one-variable input space, is estimated via bootstrap resam- pling. Hence, a backward variable elimination procedure can be stated, by removing one variable at each step according to its associated confi- dence interval. A practical example application to early stage detection of cardiac Ventricular Fibrillation (VF) is presented. Basing on a previ- ous nonlinear analysis based on temporal and spectral VF parameters, we use the SVM with Gaussian kernel and bootstrap resampling to provide with the minimum input space feature set that still holds the classification performance of the complete data. The use of bootstrap resampling is a powerful input feature selection procedure for SVM classifiers.
Extrinsic self calibration of a camera and a 3D laser range finder from natural scenes

In this paper, we describe a new approach for the extrinsic calibration of a camera with a 3D laser range finder, that can be done on the fly. This approach does not require any calibration object. Only few point correspondences are used, which are manually selected by the user from a scene viewed by the two sensors. The proposed method relies on a novel technique to visualize the range information obtained from a 3D laser scanner. This technique converts the visually ambiguous 3D range information into a 2D map where natural features of a scene are highlighted. We show that by enhancing the features the user can easily find the corresponding points of the camera image points. Therefore, visually identifying laser- camera correspondences becomes as easy as image pairing. Once point correspondences are given, extrinsic calibration is done using the well-known PnP algorithm followed by a noninear refinement process. We show the performance of our approach through experimental results. In these experiments, we will use an omnidirectional camera. The implication of this method is important because it brings 3D computer vision systems out of the laboratory and into practical use.
A P ] 9 O ct 2 01 3 A CONSTRUCTIVE METHOD FROM BOLTZMANN TO INCOMPRESSIBLE NAVIER-STOKES ON THE TORUS

We investigate the Boltzmann Equation, depending on the Knudsen number, in the Navier-Stokes perturbative setting on the torus. Using hypocoercivity, we derive a new proof of existence and exponential decay for the solutions of this perturbed equation, with explicit regularity bounds and rates of convergence. These results are uniform in the Knudsen number and thus allow us to obtain a strong derivation of the incompressible Navier-Stokes equations as the Knudsen number tends to 0. Moreover, our method shows that the smaller the Knudsen number, the less control on the v-derivatives of the initial perturbation is needed to have existence and decay. It is also used to deal with other kinetic models. Finally, we show that the study of this hydrodynamical limit is rather different on the torus than the already proven convergences in the whole space as it requires averaging in time, unless the initial layer conditions are satisfied.
Transforming Neural-Net Output Levels to Probability Distributions

(1) The outputs of a typical multi-output classification network do not satisfy the axioms of probability; probabilities should be positive and sum to one. This problem can be solved by treating the trained network as a preprocessor that produces a feature vector that can be further processed, for instance by classical statistical estimation techniques. (2) We present a method for computing the first two moments of the probability distribution indicating the range of outputs that are consistent with the input and the training data. It is particularly useful to combine these two ideas: we implement the ideas of section 1 using Parzen windows, where the shape and relative size of each window is computed using the ideas of section 2. This allows us to make contact between important theoretical ideas (e.g. the ensemble formalism) and practical techniques (e.g. back-prop). Our results also shed new light on and generalize the well-known "softmax" scheme.
Cell morphology and property relationships of microcellular foamed pvc/wood‐fiber composites

Wood-fiber composites make use of cellulose fibers as a reinforcing filler in the polymer matrix and are known to have a lower material cost and a higher stiffness than neat polymers. However, the lower material cost and enhanced stiffness of wood-fiber composites are achieved at the expense of other properties such as the ductility and impact strength. Since microcellular plastics exhibit a higher impact strength, higher toughness, and increased fatigue life compared to unfoamed plastics, microcellular foaming of wood-fiber composites will improve the mechanical properties of the composites and therefore increase the usefulness of the materials. In this paper, microcellular foamed PVC/wood-fiber composites with unique cell morphology and material composition are characterized. Microcellular structures are produced in PVC/wood-fiber composites by first saturating the composite samples with CO2 under high pressure followed by rapidly decreasing the solubility of gas in the samples. The void fraction of the microcellular foamed PVC/wood-fiber composites is controlled by tailoring the composition of materials and the foaming process parameters. The results indicate that tensile and impact properties of microcellular foamed PVC/wood-fiber composites are most sensitive to changes in the cell morphology and the surface modification of fibers.