511 research outputs found
Performance and Total PM Emission Factor Evaluation of Expendable Abrasives
Dry abrasive blasting is one of the most widely used methods of surface preparation. Air emissions from this process include particulate matter (PM) and metals. Spent abrasive generated from this process may be hazardous in nature. With increasing concern on health effects due to silica emissions from sand, use of alternative materials is suggested by health and regulatory agencies. The objective of this research was to evaluate performance of expendable abrasives and determine PM emission factors. Dry abrasive blasting was performed in an enclosed chamber and total PM samples were collected. Three commonly used expendable abrasives, coal slag, copper slag and specialty sand, were used to evaluate cleaner alternatives. Blast pressure and abrasive feed rate, two important process conditions were varied to study their effect on performance of an abrasive. Productivity, consumption and emission factors (performance parameters) were calculated and their variation with pressure and feed rate was evaluated. Two dimensional and three dimensional predicted models were developed to estimate the performance at intermediate blast pressure and feed rate conditions. Performance of the three abrasives was compared with respect to emission potential, productivity and consumption. Emission factors developed in this research will help in accurate estimation of total PM emissions and to select cleaner abrasives and optimum process conditions that will results in minimum emissions and reduced health risk. The productivity and consumption models will help is estimating life cycle costs including material cost, equipment cost, energy cost, labor costs, waste disposal cost, and compliance costs. Consumption models will also help in determining the quantity of spent abrasive generated, identify abrasives with lower material consumption, and identify process conditions that generate minimum spent abrasives. In addition, these models will help industries in making environmentally preferable purchasing (EPP), which results in pollution prevention and cost reduction
Performance and Total PM Emission Factor Evaluation of Expendable Abrasives
Dry abrasive blasting is one of the most widely used methods of surface preparation. Air emissions from this process include particulate matter (PM) and metals. Spent abrasive generated from this process may be hazardous in nature. With increasing concern on health effects due to silica emissions from sand, use of alternative materials is suggested by health and regulatory agencies. The objective of this research was to evaluate performance of expendable abrasives and determine PM emission factors. Dry abrasive blasting was performed in an enclosed chamber and total PM samples were collected. Three commonly used expendable abrasives, coal slag, copper slag and specialty sand, were used to evaluate cleaner alternatives. Blast pressure and abrasive feed rate, two important process conditions were varied to study their effect on performance of an abrasive. Productivity, consumption and emission factors (performance parameters) were calculated and their variation with pressure and feed rate was evaluated. Two dimensional and three dimensional predicted models were developed to estimate the performance at intermediate blast pressure and feed rate conditions. Performance of the three abrasives was compared with respect to emission potential, productivity and consumption. Emission factors developed in this research will help in accurate estimation of total PM emissions and to select cleaner abrasives and optimum process conditions that will results in minimum emissions and reduced health risk. The productivity and consumption models will help is estimating life cycle costs including material cost, equipment cost, energy cost, labor costs, waste disposal cost, and compliance costs. Consumption models will also help in determining the quantity of spent abrasive generated, identify abrasives with lower material consumption, and identify process conditions that generate minimum spent abrasives. In addition, these models will help industries in making environmentally preferable purchasing (EPP), which results in pollution prevention and cost reduction
Predicting Personality Traits Using Smartphone Sensor Data and App Usage Data
Human behavior is complex -- often defying explanation using traditional mathematical models. To simplify modeling, researchers often create intermediate psychological models to capture aspects of human behavior. These intermediate forms, such as those gleaned from personality inventories, are typically validated using standard survey instruments, and often correlate with behavior. Typically these constructs are used to predict stylized aspects of behavior. Novel sensing systems have made tracking behavior possible with unprecedented fidelity, posing the question as to whether the inverse process is possible: that is, inferring psychological constructs for individuals from behavioral data. Modern smartphones contain an array of sensors which can be filtered, combined, and analyzed to provide abstract measures of human behavior. Being able to extract a personal profile or personality type from data directly obtainable from a mobile phone without participant interaction could have applications for marketing or for initiating social or health interventions. In this work, we attempt to model a particularly salient and well-established personality inventory, the Big Five framework. Daily routines of participants were measured from parameters readily available from smartphones and supervised machine learning was used to create a model from that data. Cross validation-based evaluation demonstrated that the root mean squared error was sufficiently small to make actionable predictions about a person's personality from smartphone logs, but the model performed poorly for personality outliers
Perinatal outcome in pregnancies complicated with oligohydramnios at term
Background: AFI of less than or equal to five cm is considered oligohydramnios. Various approaches, such as NST, acoustic stimulation, and foetal Doppler velocimetry, are useful in assessing foetal well-being and identifying pregnancies at risk of postnatal complications. The goal of this study was to learn about the negative perinatal outcomes in pregnant women who had oligohydramnios at term and to assess the efficacy of AFI in predicting foetal distress and caesarean delivery.Methods: A retrospective and comparative study of singleton pregnancies outcomes in 60 women diagnosed with oligohydramnios by USG after 37 weeks of pregnancy, compared to 60 women who did not have oligohydramnios and were matched for other factors. Some criteria for inclusion and exclusion were utilised. The data was analysed using statistical criteria such as mean, standard deviation, and chi square test sensitivity, specificity, PPV, and NPV.Results: The occurrence of non-reactive and re-active NST patterns differed significantly between the two groups. In comparison to women with AFI >5 cm, women with AFI 5cm have a higher rate of labour induction. LBW (2.5 kg) was more common in women with oligohydramnios, and LSCS rates were higher in oligohydramnios-complicated pregnancies.Conclusions: After 37 weeks of pregnancy, an AFI of less than 5 cm is a sign of poor perinatal outcome. AFI can be used in conjunction with other foetal monitoring techniques. AFI is a useful screening test for predicting foetal distress during labour that necessitates a caesarean section
FORMULATION AND IN VITRO EVALUATION OF ORLISTAT ORODISPERSIBLE TABLETS FOR ENHANCEMENT OF DISSOLUTION RATE
Objective: The aim of the present study was to formulate the oro dispersible tablets (ODTs) of Orlistat (OST) by direct compression technique using melt granulation method.Methods: Super disintegrants were used for the preparation of ODTs namely Crospovidone (CP), Croscarmellose sodium (CCS), Sodium starch glycolate (SSG). The powder mixture was subjected to pre compression evaluation like FTIR, Micromeritic, solubility studies and post-compression evaluation like friability, hardness, wetting time, dispersion time, disintegration time and in vitro dissolution rate.Results: FTIR studies confirmed that there was no chemical interaction between the drug and excipients. Micromeritic studies revealed that the powder blend has good flow ability. The results of hardness and friability complied with the official standards. The solid dispersions (SDs) prepared in OST to PEG 6000 ratio of 1:2 were showed good solubility than other SDs and it was selected for formulation development. It was evident from the results that the increase in super disintegrants concentration decreases the wetting, dispersion and disintegration times and CP showed the best results than other super disintegrating agents.Conclusion: The F4 formulation showed optimum drug release of 98.99 % at the end of 15 min when compared to the other formulations; it might be due to the presence of CP.Keywords: Direct compression, Melt granulation method, Orlistat, Orodispersible tablets, Polyethylene glycol.Â
A Matrix Framework Factorization on a Sentiment Based Rating Prediction Method tackles Cyber bullying Detection
It displays a great chance to share our perspectives for different items we buy. In any case, we confront the data over-overloading issue. Instructions to mine profitable data from audits to comprehend a client's inclinations and make an exact proposal is critical. Customary recommender systems (RS) think of some as variables, for example, client's buy records, item classification, and geographic area. In this work, we propose a supposition based rating prediction technique (RPS) to enhance expectation exactness in recommender systems. In this paper, we extricate item highlights from literary audits utilizing LDA. We for the most part need to get the item highlights including some named elements and some item/thing/benefit characteristics. LDA is a Bayesian model, which is used to show the relationship of audits, points and words.
DESIGN AND LOAD ANALYSIS OF AND OPTIMIZATION OF COMPOUND EPICYCLIC GEAR TRAINS
A Planetary or Epicyclical Gear Trains comprises of one or more planet gears revolving around a sun gear. Usually, an epicyclical gearing systems are employed to achieve high reduction ratio in a small and power dense package. It is examined that load sharing capability is not equal in the planetary gear train. These Gear Trains are extensively used for the transmission and are the most critical component in a mechanical power transmission system. They play a very vital role in all the industrial areas, any failure in the gear train leads to a total system failure, thus identifying the causes and optimizing to get the best performance is very necessary. The advantages of epicycle gear trains are higher torque capacity, lower weight, small size and improved efficiency of the planetary design. Planetary gear transmissions are compact, high power transmitting speed reductions technology. Structural analysis of three stage coupled planetary gear train is reviewed. This analysis depicts the fast and easy determination of the speed ratio, torques, and efficiency and power flow directions of coupled planetary gear trains. Three stage efficiency determined. 3D modeling done in CREO parametric software and analysis is done in ANSYS
Preclinical evaluation of nephroprotective potential of a probiotic formulation LOBUN on Cyclosporine-A induced renal dysfunction in Wistar rats
The aim of present study was to evaluate the nephroprotective effect of probiotic formulation LOBUN on Cyclosporine A (CsA) induced renal dysfunction in Wistar rats. CsA (20 mg/kg body weight s.c) was administered for 15 days to cause renal dysfunction in Wistar rats. The probiotic formulation LOBUN was administered with the dose of 500 mg/kg body weight (p.o) for twice (TGI) and thrice a day (TGII). The samples were analyzed for the parameters like blood urine nitrogen (BUN), serum creatinine, serum uric acid, total serum protein and urine proteins, urine potassium, urine sodium. The renal functional and histopathological studies revealed that the oral administration of probiotic formulation LOBUN has provided appreciable renoprotection and possibly alleviated the symptoms of Chronic Kidney Disease (CKD) at the dose of 500 mg/kg body weight administered thrice a day and also the results were supported by histopathological findings
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