Rotating Machinery Predictive Maintenance Through Expert System

Modern rotating machines such as turbomachines, either produce or absorb huge amount of power. Some of the common applications are: steam turbine-generator and gas turbine-compressor-generator trains produce power and machines, such as pumps, centrifugal compressors, motors, generators, machine tool spindles, etc., are being used in industrial applications. Condition-based maintenance of rotating machinery is a common practice where the machine's condition is monitored constantly, so that timely maintenance can be done. Since modern machines are complex and the amount of data to be interpreted is huge, we need precise and fast methods in order to arrive at the best recommendations to prevent catastrophic failure and to prolong the life of the equipment. In the present work using vibration characteristics of a rotor-bearing system, the condition of a rotating machinery (electrical rotor) is predicted using an off-line expert system. The analysis of the problem is carried out in an Object Oriented Programming (OOP) framework using the finite element method. The expert system which is also developed in an OOP paradigm gives the type of the malfunctions, suggestions and recommendations. The system is implemented in C++

Jamming modulates coalescence dynamics of shear-thickening colloidal droplets

Recent investigations into coalescence dynamics of complex fluid droplets revealed the existence of sub-Newtonian behaviour for polymeric fluids (elastic and shear thinning). We hypothesize that such delayed coalescence or sub-Newtonian coalescence dynamics may be extended to the general class of shear thickening fluids. To investigate this droplets of aqueous corn-starch suspensions were chosen and its coalescence in sessile pendant configuration was probed by high-speed real time imaging. Temporal evolution of the neck (growth) during coalescence was quantified as a function of suspended particle weight fraction \phi_w. The necking behaviour was found to evolve as the power-law relation $R=at^b$ where R is neck radius with exponent \b\le0.5 implying it is a subset of the generic sub-Newtonian coalescence. Second significant delay in the coalescence dynamics is observed for particle fractions beyond the jamming fraction {\ \phi}_w>\ \phi_J\geq0.35}. Our proposed theoretical model captures this delay implicitly through altered suspension viscosity stemming from increased particle content

COMBINATORIAL EFFECT OF D-AMINOACIDS AND TETRACYCLINE AGAINST PSEUDOMONAS AERUGINOSA BIOFILM

Objective: The present study attempted to evaluate the anti-biofilm activity of D-amino acids (D-AAs) on Pseudomonas aeruginosa and determine if the combination of D-AAs with tetracycline enhances the anti-biofilm activity in vitro and ex vivo.Methods: Different D-AAs were tested for antibiofilm activity against wild type P. aeruginosa PAO1 and two multidrug resistant P. aeruginosa clinical strains in the presence of sub inhibitory concentrations of tetracycline using crystal violet microtitre plate assay. Results were further validated using in vitro wound dressing and ex vivo porcine skin models followed by cytotoxicity and hemocompatibility studies.Results: D-tryptophan (5 mmol) showed 61 % reduction in biofilm formation of P. aeruginosa. Interestingly combinatorial effect of 5 mmol D-tryptophan and 0.5 minimum inhibitory concentration (MIC) (7.5µg/ml) tetracycline showed 90% reduction in biofilm formation. 5 mmol D-methionine shows 28 % reduction and combination with tetracycline shows 41% reduction in biofilm formation of P. aeruginosa. D-leucine and D-tyrosine alone or in combination with tetracycline did not show significant anti-biofilm activity. D tryptophan-tetracycline combination could reduce 80 % and 77 % reduction in biofilm formation in two multi drug resistant P. aeruginosa clinical strains. D-tryptophan-tetracycline-combination could also reduce 76% and 66% reduction in biofilm formation in wound dressing model and porcine skin explant respectively. The cytotoxicity and hemocompatibility studies did not show significant toxicity when this combination was used.Conclusion: The results established the potential therapeutic application of D-tryptophan alone or in combination with tetracycline for treating biofilm associated clinical problems caused by P. aeruginosa

Critical weather limits for paddy rice under diverse ecosystems of India

Rice yields are largely influenced by variability in weather. Here, we demonstrate the effect of weather variables viz., maximum and minimum temperatures, rainfall, morning and evening relative humidity, bright sunshine hours on the yield of rice cv. Swarna, grown across five rice ecologies of India through field experiments during kharif (wet) season (Jun-Sept.). Critical thresholds of weather elements were identified for achieving above average, average and below average yield for each ecology. The investigation could determine how different weather elements individually and collectively affect rice yield in different rice ecosystems of India. While a sudden increase in minimum temperature by 8-10 °C (> 30 °C) during reproductive period resulted in 40-50 per cent yield reduction at Mohanpur, a sudden decrease (< 20 °C) caused yield decline at Dapoli. The higher yields may be attributed to a significant difference in bright sunshine hours between reproductive phases of above-average and below-average yield years (ranging from 2.8 to 7.8 hours during P5 stages and 1.7 to 5.1 during P4 stages). Rice cultivar Swarna performed differently at various sowing dates in a location as well as across locations (6650 kg ha-1 at Dapoli to 1101 kg ha-1 at Samastipur). It was also found that across all locations, the above average yield could be associated with higher range of maximum temperature compared to that of below average yield. Principal component analysis explained 77 per cent of cumulative variance among the variables at first growth stage, whereas 70 per cent at second growth stage followed by 74 per cent and 66 per cent at subsequent growth stages. We found that coastal locations, in contrast to inland ones, could maximize the yield potential of the cultivar Swarna, due to the longer duration of days between panicle initiation to physiological maturity. We anticipate that the location-specific thresholds of weather factors will encourage rice production techniques that are climate resilient

Plasma chemokines as immune biomarkers for diagnosis of pediatric tuberculosis

Abstract Background Diagnosing tuberculosis (TB) in children is challenging due to paucibacillary disease, and lack of ability for microbiologic confirmation. Hence, we measured the plasma chemokines as biomarkers for diagnosis of pediatric tuberculosis. Methods We conducted a prospective case control study using children with confirmed, unconfirmed and unlikely TB. Multiplex assay was performed to examine the plasma CC and CXC levels of chemokines. Results Baseline levels of CCL1, CCL3, CXCL1, CXCL2 and CXCL10 were significantly higher in active TB (confirmed TB and unconfirmed TB) in comparison to unlikely TB children. Receiver operating characteristics curve analysis revealed that CCL1, CXCL1 and CXCL10 could act as biomarkers distinguishing confirmed or unconfirmed TB from unlikely TB with the sensitivity and specificity of more than 80%. In addition, combiROC exhibited more than 90% sensitivity and specificity in distinguishing confirmed and unconfirmed TB from unlikely TB. Finally, classification and regression tree models also offered more than 90% sensitivity and specificity for CCL1 with a cutoff value of 28 pg/ml, which clearly classify active TB from unlikely TB. The levels of CCL1, CXCL1, CXCL2 and CXCL10 exhibited a significant reduction following anti-TB treatment. Conclusion Thus, a baseline chemokine signature of CCL1/CXCL1/CXCL10 could serve as an accurate biomarker for the diagnosis of pediatric tuberculosis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe