Delayed maintenance modelling considering speed restriction for a railway section

The deterioration of track geometry depends on several factors of which the speed of the train is one. Imposing a speed restriction can slow down the track deterioration and allows a longer survival time before a serious condition is achieved. Preventive maintenance delays can be authorized during the survival time. However, speed restrictions also reduce the system throughput. On the other hand, a longer interval between preventive maintenance activities has a lower maintenance action cost and it also enables grouping the maintenance activities to save set-up costs as well as system down time. If the repair delay is too long, it may cause unacceptable conditions on the track and lead to higher maintenance costs and accidents. Therefore, it is interesting to assess the effect of a speed restriction on the delayed maintenance strategies for a railway track section. We want to solve a maintenance optimization problem to find the optimal tuning of the maintenance delay time and imposition of a speed restriction. To this aim, a delayed maintenance model is developed, in which track deterioration depends on the train speed and the number of passing trains. The model is used to determine an optimal speed restriction strategy and a preventive repair delay for the optimization of the system benefit and unavailability. Coloured Petri Nets (CPN) are adopted to model the maintenance and operation of the railway track section. The CPN model describes the gradual track deterioration as a stochastic process. Different speed restriction policies and maintenance delay strategies are modelled and activated by the observed component states. Monte Carlo simulations are carried out to estimate the maintenance cost, the system benefit and the system downtime under different policies. Numerical results show the maintenance decision variable trade-off

What Are You Looking At? Team Fight Prediction Through Player Camera

Esport is a large and still growing industry with vast audiences. Multiplayer Online Battle Arenas (MOBAs), a sub-genre of esports, possess a very complex environment, which often leads to experts missing important coverage while broadcasting live competitions. One common game event that holds significant importance for broadcasting is referred to as a team fight engagement. Professional player's own knowledge and understanding of the game may provide a solution to this problem. This paper suggests a model that predicts and detects ongoing team fights in a live scenario. This approach outlines a novel technique of deriving representations of a complex game environment by relying on player knowledge. This is done by analysing the positions of the in-game characters and their associated cameras, utilising this data to train a neural network. The proposed model is able to both assist in the production of live esport coverage as well as provide a live, expert-derived, analysis of the game without the need of relying on outside sources

Cordyceps spp.: A Review on Its Immune-Stimulatory and Other Biological Potentials

In recent decades, interest in the Cordyceps genus has amplified due to its immunostimulatory potential. Cordyceps species, its extracts, and bioactive constituents have been related with cytokine production such as interleukin (IL)-1ß, IL-2, IL-6, IL-8, IL-10, IL-12, and tumor necrosis factor (TNF)-a, phagocytosis stimulation of immune cells, nitric oxide production by increasing inducible nitric oxide synthase activity, and stimulation of inflammatory response via mitogen-activated protein kinase pathway. Other pharmacological activities like antioxidant, anti-cancer, antihyperlipidemic, anti-diabetic, anti-fatigue, anti-aging, hypocholesterolemic, hypotensive, vasorelaxation, anti-depressant, aphrodisiac, and kidney protection, has been reported in pre-clinical studies. These biological activities are correlated with the bioactive compounds present in Cordyceps including nucleosides, sterols, flavonoids, cyclic peptides, phenolic, bioxanthracenes, polyketides, and alkaloids, being the cyclic peptides compounds the most studied. An organized review of the existing literature was executed by surveying several databanks like PubMed, Scopus, etc. using keywords like Cordyceps, cordycepin, immune system, immunostimulation, immunomodulatory, pharmacology, anti-cancer, anti-viral, clinical trials, ethnomedicine, pharmacology, phytochemical analysis, and different species names. This review collects and analyzes state-of-the-art about the properties of Cordyceps species along with ethnopharmacological properties, application in food, chemical compounds, extraction of bioactive compounds, and various pharmacological properties with a special focus on the stimulatory properties of immunity.This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1G1A1004667), Republic of Korea

A threshold level of NFATc1 activity facilitates thymocyte differentiation and opposes notch-driven leukaemia development.

International audienceNFATc1 plays a critical role in double-negative thymocyte survival and differentiation. However, the signals that regulate Nfatc1 expression are incompletely characterized. Here we show a developmental stage-specific differential expression pattern of Nfatc1 driven by the distal (P1) or proximal (P2) promoters in thymocytes. Whereas, preTCR-negative thymocytes exhibit only P2 promoter-derived Nfatc1beta expression, preTCR-positive thymocytes express both Nfatc1beta and P1 promoter-derived Nfatc1alpha transcripts. Inducing NFATc1alpha activity from P1 promoter in preTCR-negative thymocytes, in addition to the NFATc1beta from P2 promoter impairs thymocyte development resulting in severe T-cell lymphopenia. In addition, we show that NFATc1 activity suppresses the B-lineage potential of immature thymocytes, and consolidates their differentiation to T cells. Further, in the pTCR-positive DN3 cells, a threshold level of NFATc1 activity is vital in facilitating T-cell differentiation and to prevent Notch3-induced T-acute lymphoblastic leukaemia. Altogether, our results show NFATc1 activity is crucial in determining the T-cell fate of thymocytes

Use of Ionic Liquid in Fabrication, Characterization, and Processing of Anodic Porous Alumina

Two different ionic liquids have been tested in the electrochemical fabrication of anodic porous alumina in an aqueous solution of oxalic acid. It was found that during galvanostatic anodization of the aluminum at a current density of 200 mA/cm2, addition of 0.5% relative volume concentration of 1-butyl-3-methylimidazolium tetrafluoborate resulted in a three-fold increase of the growth rate, as compared to the bare acidic solution with the same acid concentration. This ionic liquid was also used successfully for an assessment of the wettability of the outer surface of the alumina, by means of liquid contact angle measurements. The results have been discussed and interpreted with the aid of atomic force microscopy. The observed wetting property allowed to use the ionic liquid for protection of the pores during a test removal of the oxide barrier layer

High Resolution Detection and Analysis of CpG Dinucleotides Methylation Using MBD-Seq Technology

Methyl-CpG binding domain protein sequencing (MBD-seq) is widely used to survey DNA methylation patterns. However, the optimal experimental parameters for MBD-seq remain unclear and the data analysis remains challenging. In this study, we generated high depth MBD-seq data in MCF-7 cell and developed a bi-asymmetric-Laplace model (BALM) to perform data analysis. We found that optimal efficiency of MBD-seq experiments was achieved by sequencing ∼100 million unique mapped tags from a combination of 500 mM and 1000 mM salt concentration elution in MCF-7 cells. Clonal bisulfite sequencing results showed that the methylation status of each CpG dinucleotides in the tested regions was accurately detected with high resolution using the proposed model. These results demonstrated the combination of MBD-seq and BALM could serve as a useful tool to investigate DNA methylome due to its low cost, high specificity, efficiency and resolution

Molecular marks for epigenetic identification of developmental and cancer stem cells

Epigenetic regulations of genes by reversible methylation of DNA (at the carbon-5 of cytosine) and numerous reversible modifications of histones play important roles in normal physiology and development, and epigenetic deregulations are associated with developmental disorders and various disease states, including cancer. Stem cells have the capacity to self-renew indefinitely. Similar to stem cells, some malignant cells have the capacity to divide indefinitely and are referred to as cancer stem cells. In recent times, direct correlation between epigenetic modifications and reprogramming of stem cell and cancer stem cell is emerging. Major discoveries were made with investigations on reprogramming gene products, also known as master regulators of totipotency and inducer of pluoripotency, namely, OCT4, NANOG, cMYC, SOX2, Klf4, and LIN28. The challenge to induce pluripotency is the insertion of four reprogramming genes (Oct4, Sox2, Klf4, and c-Myc) into the genome. There are always risks of silencing of these genes by epigenetic modifications in the host cells, particularly, when introduced through retroviral techniques. In this contribution, we will discuss some of the major discoveries on epigenetic modifications within the chromatin of various genes associated with cancer progression and cancer stem cells in comparison to normal development of stem cell. These modifications may be considered as molecular signatures for predicting disorders of development and for identifying disease states

Refolding by High Pressure of a Toxin Containing Seven Disulfide Bonds: Bothropstoxin-1 from Bothrops jararacussu

Aggregation is a serious obstacle for recovery of biologically active heterologous proteins from inclusion bodies (IBs) produced by recombinant bacteria. E. coli transformed with a vector containing the cDNA for Bothropstoxin-1 (BthTx-1) expressed the recombinant product as IBs. In order to obtain the native toxin, insoluble and aggregated protein was refolded using high hydrostatic pressure (HHP). IBs were dissolved and refolded (2 kbar, 16 h), and the effects of protein concentration, as well as changes in ratio and concentration of oxido-shuffling reagents, guanidine hydrochloride (GdnHCl), and pH in the refolding buffer, were assayed. A 32% yield (7.6 mg per liter of bacterial culture) in refolding of the native BthTx-1 was obtained using optimal conditions of the refolding buffer (Tris–HCl buffer, pH 7.5, containing 3 mM of a 2:3 ratio of GSH/GSSG, and 1 M GdnHCl). Scanning electron microscopy (SEM) showed that that disaggregation of part of IBs particles occurred upon compression and that the morphology of the remaining IBs, spherical particles, was not substantially altered. Dose-dependent cytotoxic activity of high-pressure refolded BthTx-1 was shown in C2C12 muscle cells

Sex Differences in the Brain: A Whole Body Perspective

Most writing on sexual differentiation of the mammalian brain (including our own) considers just two organs: the gonads and the brain. This perspective, which leaves out all other body parts, misleads us in several ways. First, there is accumulating evidence that all organs are sexually differentiated, and that sex differences in peripheral organs affect the brain. We demonstrate this by reviewing examples involving sex differences in muscles, adipose tissue, the liver, immune system, gut, kidneys, bladder, and placenta that affect the nervous system and behavior. The second consequence of ignoring other organs when considering neural sex differences is that we are likely to miss the fact that some brain sex differences develop to compensate for differences in the internal environment (i.e., because male and female brains operate in different bodies, sex differences are required to make output/function more similar in the two sexes). We also consider evidence that sex differences in sensory systems cause male and female brains to perceive different information about the world; the two sexes are also perceived by the world differently and therefore exposed to differences in experience via treatment by others. Although the topic of sex differences in the brain is often seen as much more emotionally charged than studies of sex differences in other organs, the dichotomy is largely false. By putting the brain firmly back in the body, sex differences in the brain are predictable and can be more completely understood

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation