Multi-Input Convolutional Neural Networks for Automatic Pollen Classification

Pollen allergies are a cause of much suffering for an increasing number of individuals. Current pollen monitoring techniques are lacking due to their reliance on manual counting and classification of pollen by human technicians. In this study, we present a neural network architecture capable of distinguishing pollen species using data from an automated particle measurement device. This work presents an improvement over the current state of the art in the task of automated pollen classification, using fluorescence spectrum data of aerosol particles. We obtained a relative reduction in the error rate of over 48%, from 27% to 14%, for one of the datasets, with similar improvements for the other analyzed datasets. We also use a novel approach for doing hyperparameter tuning for multiple input networks.

Automation of online particle measurement during the simulated use of catheters and stent systems

The assessment of the coating integrity of cardiovascular implants such as catheters and stent systems is of crucial importance for device approval. Released particles may represent a potential health risk for the patients. Thus, an analysis of the particles released at simulated in-vivo conditions depending on their size and number is required by international standards (ISO, ASTM) as well as national authorities. In this study, an automated test bench for online particle measurement is presented. For software controlled automation, sensor data transmission and solenoid valves were implemented. A user interface was created for setting test parameters and data recording. The setup was validated by investigating standard particles as well as those released during the simulated application of non-industrial coated balloons. The measurement data were compared with results generated using the previous manual test routine. The results show an improvement in the reproducibility of the measurements, which can be attributed to the simplified handling for the user.

Application of an Electrical Low Pressure Impactor (ELPI) for Residual Particle Measurement in an Epitaxial Growth Reactor

The purpose of this study was to determine the feasibility of using an electrical low pressure impactor (ELPI) for analyzing residual particles in a Si epitaxial growth process chamber and establish an application technique. Prior to experimental measurements, some preliminary works were conducted, including an inlet improvement of a cascade impactor, vacuum fitting fastening and flow rate adjustment, and a vacuum leak test. After that, residual particles in the process chamber were measured during N2 gas purge using an ELPI due to its advantages including the real-time measurement of particles and the ability to separate and collect particles by their diameters. In addition, ELPI could be used to obtain particle size distribution and see the distribution trend for both number and mass concentration. The results of the real-time analysis of the total particle count revealed that the concentration at the endpoint compared to that at the beginning of the measurement by decreased 36.9%. Scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM–EDS) analysis of collected particles was performed using two types of substrates: Al foil and a Si wafer. The results showed that most particles were Si particles, while few particles had Si and Cl components. ELPI has the clear advantages of real-time particle concentration measurement and simultaneous collection. Thus, we believe that it can be more actively used for particle measurement and analysis in the semiconductor industry, which has many critical micro/nanoparticle issues.

FORMULATION AND EVALUATION OF SLN BASED TOPICAL GEL OF KETOROLAC TROMETHAMINE

Ketorolac tromethamine is frequently non-steroidal anti-inflammatory drug (NSAIDs) with analgesic, anti-inflammatory and antipyretic properties, is also nice in relieving symptoms of osteoarthritis, rheumatoid arthritis, ankylosing spondylitis, acute sciatica and low back pain. Solid lipid nanoparticles (SLNs) are able to be used for the focused on of anti-inflammatory drugs, thus accomplish most significant advantages such as reduction in total dose and prevention of systemic toxicity and unusual side effects. The objective of the present investigation was to prepare & evaluate solid lipid nanoparticle (SLN) based topical gel of non-steroidal anti-inflammatory drug (NSAID) ketorolac tromethamine for the cure of arthritis which would attenuate the gastrointestinal related toxicities related with oral administration. SLNs had been prepared by means of low temperature solidification technique and characterize by means of particle measurement, analysis, FTIR spectroscopy, drug entrapment efficiency, SEM, in vitro In vitro release research were performed on Franz diffusion cell the usage of dialysis membrane in phosphate buffer solution of pH 7.4. The FTIR study indicates no predominant interaction of ketorolac tromethamine with different component ingredients and the Scanning Electron Microscope study revealed that the drug is molecularly dispersion into the lipid. The particle measurement determination confirms the particle distribution in the nanoparticle range (27% volume to 56% volume). In vitro drug release using the dialysis membrane as of the prepared SLNs is greatly higher than the pure drug. The stability of the formulation shows the stability of the formulation besides changing its performances on storage. Hence formulation of ketorolac tromethamine in SLN, enhances the dissolution price as properly as it will enhance the bioavailability of the drug which ought to the stabilized for the duration of storage.

Particle measurement technology based on RDE testing differentiation studies

In the vehicle emission test, there are many kinds of measurement equipment for particulate matter, and their measurement principles are also different. By using two kinds of equipment with different principle of particle measurement, the difference of measurement results under the same conditions is compared and the reasons are analyzed. The results show that more particles with particle size less than 50 nm are measured by DC principle, and the concentration of particles with small particle size is higher, so that the PN measurement results using DC principle test are higher than those using CPC principle test results.The measurement results of the CPC and DC principle test equipment during the transient process are very similar, but DC is more sensitive to small-particle particle testing and can test small-particle particles up to 10 nm, so the test concentration is higher than that of CPC.