scholarly journals Development of a Controlled Continuous Low-Dose Feeding Process

2021 ◽  
Vol 22 (7) ◽  
Author(s):  
Sara Fathollahi ◽  
Julia Kruisz ◽  
Stephan Sacher ◽  
Jakob Rehrl ◽  
M. Sebastian Escotet-Espinoza ◽  
...  
Keyword(s):  
Control Strategy ◽  
Small Particle ◽  
Feed Rate ◽  
Low Dose ◽  
Particle System ◽  
High Density ◽  
Displacement Rate ◽  
Set Point ◽  
Relative Standard ◽  
Feeding Process

AbstractThis paper proposes a feed rate control strategy for a novel volumetric micro-feeder, which can accomplish low-dose feeding of pharmaceutical raw materials with significantly different powder properties. The developed feed-forward control strategy enables a constant feed rate with a minimum deviation from the set-point, even for materials that are typically difficult to accurately feed (e.g., due to high cohesion or low density) using conventional continuous feeders. Density variations observed during the feeding process were characterized via a displacement feed factor profile for each powder. The characterized effective displacement density profile was applied in the micro-feeder system to proactively control the feed rate by manipulating the powder displacement rate (i.e., computing the feed rate from the powder displacement rate). Based on the displacement feed factor profile, the feed rate can be predicted during the feeding process and at any feed rate set-point. Three pharmaceutically relevant materials were used for the micro-feeder evaluation: di-calcium phosphate (large-particle system, high density), croscarmellose sodium (small-particle system, medium density), and barium sulfate (very small-particle <10 μm, high density). A significant improvement in the feeding performance was achieved for all investigated materials. The feed rate deviation from the set-point and its relative standard deviation were minimal compared to operations without the control strategy.

scholarly journals Performance Evaluation of a High-Precision Low-Dose Powder Feeder

2020 ◽  
Vol 21 (8) ◽  
Author(s):  
Sara Fathollahi ◽  
Stephan Sacher ◽  
M. Sebastian Escotet-Espinoza ◽  
James DiNunzio ◽  
Johannes G. Khinast
Keyword(s):  
Test Performance ◽  
Feed Rate ◽  
Low Dose ◽  
Elastic Recovery ◽  
Density Variation ◽  
Feeding Performance ◽  
Dose Rates ◽  
Pharmaceutical Ingredients ◽  
Feeding Process ◽  
Bed Expansion

Abstract Highly potent active pharmaceutical ingredients (APIs) and low-dose excipients, or excipients with very low density, are notoriously hard to feed with currently available commercial technology. The micro-feeder system presented in this work is capable of feeding low-dose rates of powders with different particle sizes and flow properties. Two different grades of lactose, di-calcium phosphate, croscarmellose sodium, silicon dioxide, a spray-dried intermediate, and an active ingredient were studied to vary material properties to test performance of the system. The current micro-feeder system is a volumetric feeder combined with a weighing balance at the outlet that measures feeder output rates. Feeding results are shown as a so-called “displacement-feed factor” curve for each material. Since the powder mass and volume are known in the micro-feeder system, in this work, we characterized an observed density variation during processing via a “displacement-feed factor” profile for each of the fed powders. This curve can be later used for calibrating the system to ensure an accurate, constant feed rate and in addition predicting feeding performance for that material at any feed rate. There is a relation between powder properties and feeding performance. Powders with finer particles and higher compressibility show densification during their feeding process. However, powders with larger particles and lower compressibility show both “densification” and “powder bed expansion,” which is the manifestation of dilation and elastic recovery of particles during the micro-feeding process. Through the application of the displacement-feed factor, it is possible to provide precise feeding accuracy of low-dose materials. Graphical abstract

scholarly journals Intuitive real-time control strategy for high-density myoelectric hand prosthesis using deep and transfer learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Simon Tam ◽  
Mounir Boukadoum ◽  
Alexandre Campeau-Lecours ◽  
Benoit Gosselin
Keyword(s):  
Real Time ◽  
Transfer Learning ◽  
Control Strategy ◽  
High Density ◽  
Fine Tuning ◽  
Mode Switching ◽  
Correct Prediction ◽  
Learning Approach ◽  
Predictive Values ◽  
Hand Prosthesis

AbstractMyoelectric hand prostheses offer a way for upper-limb amputees to recover gesture and prehensile abilities to ease rehabilitation and daily life activities. However, studies with prosthesis users found that a lack of intuitiveness and ease-of-use in the human-machine control interface are among the main driving factors in the low user acceptance of these devices. This paper proposes a highly intuitive, responsive and reliable real-time myoelectric hand prosthesis control strategy with an emphasis on the demonstration and report of real-time evaluation metrics. The presented solution leverages surface high-density electromyography (HD-EMG) and a convolutional neural network (CNN) to adapt itself to each unique user and his/her specific voluntary muscle contraction patterns. Furthermore, a transfer learning approach is presented to drastically reduce the training time and allow for easy installation and calibration processes. The CNN-based gesture recognition system was evaluated in real-time with a group of 12 able-bodied users. A real-time test for 6 classes/grip modes resulted in mean and median positive predictive values (PPV) of 93.43% and 100%, respectively. Each gesture state is instantly accessible from any other state, with no mode switching required for increased responsiveness and natural seamless control. The system is able to output a correct prediction within less than 116 ms latency. 100% PPV has been attained in many trials and is realistically achievable consistently with user practice and/or employing a thresholded majority vote inference. Using transfer learning, these results are achievable after a sensor installation, data recording and network training/fine-tuning routine taking less than 10 min to complete, a reduction of 89.4% in the setup time of the traditional, non-transfer learning approach.

Automated Deburring with a Filamentary Brush: Prescribed Burr Geometry

1999 ◽  
Vol 121 (3) ◽  
pp. 385-392 ◽  
Author(s):  
Robert J. Stango ◽  
Lienjing Chen ◽  
Vikram Cariapa
Keyword(s):  
Penetration Depth ◽  
Dynamic Model ◽  
Control Strategy ◽  
Feed Rate ◽  
Material Removal ◽  
Vision System ◽  
Closed Form Solution ◽  
Straight Edge ◽  
Finite Width ◽  
Production Environment

In this paper, a dynamic model for removal of edge burrs with a compliant brushing tool is reported. Description of the burr geometry is assumed to be known through on-line measurement methods such as a computer vision system in the flexible manufacturing cell. Dynamic response of the brush/workpiece system is evaluated on the basis of experimentally obtained data. Master Curves are introduced as machining descriptors which characterize the incremental burr removal performance of the brush/workpiece system, leading to the development of an analytical dynamic model for orthogonal burr removal using a finite-width brushing tool. Based upon the dynamic model for material removal, a control strategy for automatic deburring is presented for burr configurations having constant height as well as variable height. A closed-form solution for transverse brush feed rate is obtained which is applicable for removal of burrs having variable height, as described by suitable geometry functions. For illustrative purposes, simulations are carried out for a straight-edge burr profile and sinusoidal burr geometry. Results are reported which identify important relationships among brush feed rate, brush penetration depth, and brush rotational speed. In order to help assess the validity of the proposed analytical model and control strategy, experimental results are reported for a combination ramp/straight-edge burr configuration. The results demonstrate generally good correlation between the predicted and actual profile for the edge burr that has been machined. In addition, some important observations include; (1) burr removal is most rapidly carried out by using the highest brush speed and deepest brush/workpiece penetration depth, subject to the condition that the brush fiber is not damaged, (2) Currently available polymer abrasive brushing tools exhibit very slow machining characteristics and must be improved in order to be used in a production environment where burr size is appreciable, (3) Material removal characteristics of the leading and trailing edge of brushes may be a source of error which merits further investigation.

scholarly journals Efficacy of low-dose rosuvastatin in patients with type 2 diabetes and hypo high-density lipoprotein cholesterolaemia

2014 ◽  
Vol 42 (2) ◽  
pp. 457-467 ◽  
Author(s):  
Takuyuki Katabami ◽  
Mariko Murakami ◽  
Suzuko Kobayashi ◽  
Tomoya Matsui ◽  
Makoto Ujihara ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
High Density Lipoprotein ◽  
Low Dose ◽  
Density Lipoprotein ◽  
High Density

Long-Term Low-Dose Treatment With Reserpine of Cholesterol-Fed Rabbits Reduces Cholesterol in Plasma, Non-High Density Lipoproteins and Arterial Walls

2002 ◽  
Vol 40 (1) ◽  
pp. 67-79 ◽  
Author(s):  
Shahida Shafi ◽  
Irina P. Stepanova ◽  
Colin Fitzsimmons ◽  
David E. Bowyer ◽  
Gustav V. R. Born
Keyword(s):  
Low Dose ◽  
High Density ◽  
High Density Lipoproteins ◽  
Dose Treatment ◽  
Arterial Walls

scholarly journals Quasi-3D Plasmonic Nanowell Array for Molecular Enrichment and SERS-Based Detection

Nanomaterials ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 939
Author(s):  
Sunho Kim ◽  
Chaewon Mun ◽  
Dae-Geun Choi ◽  
Ho Sang Jung ◽  
Dong-Ho Kim ◽  
...  
Keyword(s):  
Nanoimprint Lithography ◽  
Molecular Detection ◽  
Near Field ◽  
Field Enhancement ◽  
Triple Line ◽  
Surface Enhanced Raman Spectroscopy ◽  
High Density ◽  
Localized Surface Plasmon ◽  
Au Nps ◽  
Relative Standard

We report on a quasi-three-dimensional (3D) plasmonic nanowell array with high structural uniformity for molecular detection. The quasi-3D plasmonic nanowell array was composed of periodic hexagonal Au nanowells whose surface is densely covered with gold nanoparticles (Au NPs), separated by an ultrathin dielectric interlayer. The uniform array of the Au nanowells was fabricated by nanoimprint lithography and deposition of Au thin film. A self-assembled monolayer (SAM) of perfluorodecanethiol (PFDT) was coated on the Au surface, on which Au was further deposited. Interestingly, the PFDT-coated Au nanowells were fully covered with Au NPs with an ultra-high density of 375 μm−2 rather than a smooth film due to the anti-wetting property of the low-energy surface. The plasmonic nanogaps formed among the high-density Au NPs led to a strong near-field enhancement via coupled localized surface plasmon resonance and produced a uniform surface-enhanced Raman spectroscopy (SERS) response with a small relative standard deviation of 5.3%. Importantly, the highly uniform nanostructure, featured by the nanoimprint lithography and 3D growth of densely-packed Au NPs, minimizes the spatial variation of Raman intensity, potentially providing quantitative analysis. Moreover, analyte molecules were highly concentrated and selectively deposited in nanowells when a water droplet containing the analyte was evaporated on the plasmonic substrate. The analyte formed a relatively thick overcoat in the nanowells near the triple line due to the coffee-ring effects. Combining 3D plasmonic nanowell substrates with molecular enrichments, highly sensitive detection of lactic acid was demonstrated. Given its combination of high sensitivity and signal uniformity, the quasi-3D plasmonic nanowell substrate is expected to provide a superior molecular detection platform for biosensing applications.

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