Detection of bearing failure in mechanical devices using neural networks

We present a novel time-domain method for the detection of faulty bearings that has direct applicability to monitoring the health of the turbo pumps on the Space Shuttle Main Engine. A feed-forward neural network was trained to detect modelled roller bearing faults on the basis of the periodicity of impact pulse trains. The network's performance was dependent upon the number of pulses in the network's input window and the signal-to-noise ratio of the input signal. To test the model's validity, we fit the model's parameters to an actual vibration signal generated by a faulty roller element bearing and applied the network trained on this model to detect faults in actual vibration data. When this network was tested on the actual vibration data, it correctly identified the vibration signal as a fault condition 76 percent of the time

Evaluation of parasitism and predation of Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae) by Diglyphus isaea (Walker, 1838) (Hymenoptera: Eulophidae)

To evaluate an eventual parasitism and/or predation behaviour of the eulophid parasitoid Diglyphus isaea (Walker, 1838) on Tuta absoluta (Meyrick, 1917) larvae two assays were performed releasing adult parasitoids. The first assay was conducted in Petri dishes using tomato leaflets havig mines with T. absoluta larvae inside. The second, was performed on previously infested potted tomato plants. In both assays no parasitism but only predation was found. Predation was observed, mainly on L2 and L3 larvae which had moulted. Proportion of clearly preyed larvae reached 17% in Petri dishes and 38% in potted plants. Predation was attested by the presence of punctures done by the oviscapt of the female parasitoid. A significant higher proportion of dead larvae where it was not possible to see punctures occurred in the presence of the parasitoid females. Some of them probably were also preyed on by D. isaea femalesinfo:eu-repo/semantics/publishedVersio

Relationship of Alexithymia Ratings to Dopamine D2-type Receptors in Anterior Cingulate and Insula of Healthy Control Subjects but Not Methamphetamine-Dependent Individuals.

BackgroundIndividuals with substance-use disorders exhibit emotional problems, including deficits in emotion recognition and processing, and this class of disorders also has been linked to deficits in dopaminergic markers in the brain. Because associations between these phenomena have not been explored, we compared a group of recently abstinent methamphetamine-dependent individuals (n=23) with a healthy-control group (n=17) on dopamine D2-type receptor availability, measured using positron emission tomography with [(18)F]fallypride.MethodsThe anterior cingulate and anterior insular cortices were selected as the brain regions of interest, because they receive dopaminergic innervation and are thought to be involved in emotion awareness and processing. The Toronto Alexithymia Scale, which includes items that assess difficulty in identifying and describing feelings as well as externally oriented thinking, was administered, and the scores were tested for association with D2-type receptor availability.ResultsRelative to controls, methamphetamine-dependent individuals showed higher alexithymia scores, reporting difficulty in identifying feelings. The groups did not differ in D2-type receptor availability in the anterior cingulate or anterior insular cortices, but a significant interaction between group and D2-type receptor availability in both regions, on self-report score, reflected significant positive correlations in the control group (higher receptor availability linked to higher alexithymia) but nonsignificant, negative correlations (lower receptor availability linked to higher alexithymia) in methamphetamine-dependent subjects.ConclusionsThe results suggest that neurotransmission through D2-type receptors in the anterior cingulate and anterior insular cortices influences capacity of emotion processing in healthy people but that this association is absent in individuals with methamphetamine dependence

IST Austria Technical Report

In order to guarantee that each method of a data structure updates the logical state exactly once, al-most all non-blocking implementations employ Compare-And-Swap (CAS) based synchronization. For FIFO queue implementations this translates into concurrent enqueue or dequeue methods competing among themselves to update the same variable, the tail or the head, respectively, leading to high contention and poor scalability. Recent non-blocking queue implementations try to alleviate high contentionby increasing the number of contention points, all the while using CAS-based synchronization. Furthermore, obtaining a wait-free implementation with competition is achieved by additional synchronization which leads to further degradation of performance.In this paper we formalize the notion of competitiveness of a synchronizing statement which can beused as a measure for the scalability of concurrent implementations. We present a new queue implementation, the Speculative Pairing (SP) queue, which, as we show, decreases competitiveness by using Fetch-And-Increment (FAI) instead of CAS. We prove that the SP queue is linearizable and lock-free.We also show that replacing CAS with FAI leads to wait-freedom for dequeue methods without an adverse effect on performance. In fact, our experiments suggest that the SP queue can perform and scale better than the state-of-the-art queue implementations

In Vivo Time-Lapse Imaging of Cell Divisions during Neurogenesis in the Developing Zebrafish Retina

AbstractTwo-photon excitation microscopy was used to reconstruct cell divisions in living zebrafish embryonic retinas. Contrary to proposed models for vertebrate asymmetric divisions, no apico-basal cell divisions take place in the zebrafish retina during the generation of postmitotic neurons. However, a surprising shift in the orientation of cell division from central-peripheral to circumferential occurs within the plane of the ventricular surface. In the sonic you (syu) and lakritz (lak) mutants, the shift from central-peripheral to circumferential divisions is absent or delayed, correlating with the delay in neuronal differentiation and neurogenesis in these mutants. The reconstructions here show that mitotic cells always remain in contact with the opposite basal surface by means of a thin basal process that can be inherited asymmetrically

Quantitative relaxation of concurrent data structures

There is a trade-off between performance and correctness in implementing concurrent data structures. Better performance may be achieved at the expense of relaxing correctness, by redefining the semantics of data structures. We address such a redefinition of data structure semantics and present a systematic and formal framework for obtaining new data structures by quantitatively relaxing existing ones. We view a data structure as a sequential specification S containing all "legal" sequences over an alphabet of method calls. Relaxing the data structure corresponds to defining a distance from any sequence over the alphabet to the sequential specification: the k-relaxed sequential specification contains all sequences over the alphabet within distance k from the original specification. In contrast to other existing work, our relaxations are semantic (distance in terms of data structure states). As an instantiation of our framework, we present two simple yet generic relaxation schemes, called out-of-order and stuttering relaxation, along with several ways of computing distances. We show that the out-of-order relaxation, when further instantiated to stacks, queues, and priority queues, amounts to tolerating bounded out-of-order behavior, which cannot be captured by a purely syntactic relaxation (distance in terms of sequence manipulation, e.g. edit distance). We give concurrent implementations of relaxed data structures and demonstrate that bounded relaxations provide the means for trading correctness for performance in a controlled way. The relaxations are monotonic which further highlights the trade-off: increasing k increases the number of permitted sequences, which as we demonstrate can lead to better performance. Finally, since a relaxed stack or queue also implements a pool, we actually have new concurrent pool implementations that outperform the state-of-the-art ones

The effectiveness of decompression as initial treatment for jaw cysts : a 10-year retrospective study

Decompression is an approved alternative to cystectomy in the treatment of jaw cysts. This study aimed to evaluate its effectiveness as an initial procedure, as well as factors with potential to influence outcome. The frequency of decompression was analysed, whether completed in one session or followed by enucleation at the Division of Oral Surgery and Orthodontics, Department of Dental Medicine and Oral Health, Medical University of Graz, from 2005 to 2015. Further analysis focussed on factors potentially influencing outcome: cyst location, histopathology, means of preserving the cyst opening, cyst size, patient age. In all, 53 patients with 55 jaw cysts (mean age of 35.1) were treated by initial decompression in the ten-year period. In the majority of cases, histopathological analysis revealed a follicular cyst (43.6%), followed by odontogenic keratocysts (23.7%), radicular cysts (21.8%), residual cysts (7.3%) and nasopalatine cysts (3.6%) Treatment was completed with a single decompression in 45.5% of the cases. Among those, 72.0% were follicular cysts and 8.0% odontogenic keratocysts. Subsequent enucleation was needed in 54.5% of all cases, with a majority in the keratocystic group (36.7%). Histological findings, means of keeping the cyst open, and patient age were found to influence the effectiveness of decompression. Decompression could be performed as a procedure completed in one session or combined with subsequent enucleation, mainly dependent on histopathological findings. Subsequent enucleation of odontogenic keratocysts is highly recommended

An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms

Cephalometric tracing method is usually used in orthodontic diagnosis and treatment planning. In this paper, we propose a deep learning based framework to automatically detect anatomical landmarks in cephalometric X-ray images. We train the deep encoder-decoder for landmark detection, and combine global landmark configuration with local high-resolution feature responses. The proposed frame-work is based on 2-stage u-net, regressing the multi-channel heatmaps for land-mark detection. In this framework, we embed attention mechanism with global stage heatmaps, guiding the local stage inferring, to regress the local heatmap patches in a high resolution. Besides, the Expansive Exploration strategy improves robustness while inferring, expanding the searching scope without increasing model complexity. We have evaluated our framework in the most widely-used public dataset of landmark detection in cephalometric X-ray images. With less computation and manually tuning, our framework achieves state-of-the-art results