An Evaluation of Multi-Component Weft-Knitted Twill Structures for Sensing Tensile Force

We present multi-component knitted resistive sensors for tracking tensile force. The knits were fabricated using a Twill structure, which is a simple pattern featuring anisotropic elastic behavior, providing high stability along course-direction. Our sensors are made of two commercially available conductive yarn types, with highly different linear resistance. We present a variety of integration methods using the proposed Twill structure, all of which can be easily replicated on a two-bed weft-knitting machine. We evaluate the performance of the resulting sensor variations, with respect to consistency, hysteresis, short-term and long-term relaxation and drift, among other metrics. We found that particulars of the knit's loop composition have a crucial effect on the consistency of the sensor readings. Furthermore, we show that knitting resistive yarn more tightly than the substrate material gives superior results and that improving elastic recoil by adding Lycra to the supporting substrate can considerably improve performance

Machine Learning Based Compensation for Inconsistencies in Knitted Force Sensors

Knitted sensors frequently suffer from inconsistencies due to innate effects such as offset, relaxation, and drift. These properties, in combination, make it challenging to reliably map from sensor data to physical actuation. In this paper, we demonstrate a method for counteracting this by applying processing using a minimal artificial neural network (ANN) in combination with straightforward pre-processing. We apply a number of exponential smoothing filters on a re-sampled sensor signal, to produce features that preserve different levels of historical sensor data and, in combination, represent an adequate state of previous sensor actuation. By training a three-layer ANN with a total of 8 neurons, we manage to significantly improve the mapping between sensor reading and actuation force. Our findings also show that our technique translates to sensors of reasonably different composition in terms of material and structure, and it can furthermore be applied to related physical features such as strain

Debris-flow activity and sediment dynamics in the landslide-influenced Lattenbach catchment, Austria

Deep seated landslides are common phenomena in Alpine areas. In case of a direct connectivity with the channel system, the catchment’s sediment yield and the probability of other forms of mass wasting processes such as debris flows may be increased significantly. Up to now, sediment dynamics related to deep-seated landslides and debris flows have not been quantified. The Lattenbach catchment (basin area 5,3 km², relief 2134 m) in Grins (Tyrol, Austria), is an example for an active DF-site, where there is geomorphological evidence of deep-seated landslide activity. In this study we shed light (1) on the location and size of active landslides in the catchment, that may deliver sediment to the channel system. Furthermore, we want to (2) quantify the contributed sediment volumes by these landslides (3) and estimate the exported sediment by debris flow. We apply an image correlation algorithm to high resolution ALS and TLS terrain models of derived over a period of 14 years to calculate surface movement rates within the catchment and locate deep seated landslide activity. We further assess the sediment yield of these landslides to the channel system and relate that with DF-volumes measured by a monitoring station at the catchment outlet. We find that there are five deep-seated landslide bodies directly connected to the channel system in the catchment. These are the largest source of sediment and significantly increases the overall sediment yield of the catchment. Our study shall contribute to the limited knowledge about the importance of deep-seated landslides for sediment dynamics and debris-flow activity, as their presence is predicted to be more frequent in the wake of global warming

Supplementary data from: Adrenal venous sampling (AVS) in Primary Bilateral Macronodular Adrenocortical Hyperplasia (PBMAH): A study of 16 patients

Adrenal venous sampling in primary bilateral macronodular adrenocortical hyperplasi

A versatile optode system for oxygen, carbon dioxide, and pH measurements in seawater with integrated battery and logger

Herein, we present a small and versatile optode system with integrated battery and logger for monitoring of O-2, pH, and pCO(2) in seawater. Three sensing materials designed for seawater measurements are optimized with respect to dynamic measurement range and long-term stability. The spectral properties of the sensing materials were tailored to be compatible with a commercially available laboratory oxygen logger that was fitted into a pressure housing. Interchangeable sensor caps with appropriate "sensing chemistry" are conveniently attached to the end of the optical fiber. This approach allows using the same instrument for multiple analytes, which offers great flexibility and minimizes hardware costs. Applications of the new optode system were demonstrated by recording depth profiles for the three parameters during a research cruise in the Baltic Sea and by measuring surface water transects of pH. The optode was furthermore used to monitor the concentration of dissolved oxygen in a seagrass meadow in the Limfjord, Denmark, and sensor packages consisting of pO(2), pH, and pCO(2) were deployed in the harbors of Kiel, Germany, and Southampton, England, for 6 d. The measurements revealed that the system can resolve typical patterns in seawater chemistry related to spatial heterogeneities as well as temporal changes caused by biological and tidal activity

Efficiency of Ontario primary care physicians across payment models : a stochastic frontier analysis

Objective The study examines the relationship between the primary care model that a physician belongs to and the efficiency of the primary care physician in Ontario, Canada. Methods Survey data were collected from 183 self-selected physicians and linked to administrative databases to capture the provision of services to the patients served for the 12 month period ending June 30, 2013, and the characteristics of the patients at the beginning of the study period. Two stochastic frontier regression models were used to estimate efficiency scores and parameters for two separate outputs: the number of distinct patients seen and the number of visits. Results Because of missing data, only 165 physicians were included in the analyses. The average efficiency was 0.72 for both outputs with scores varying from 4 % to 93 % for the visits and 5 % to 94 % for the number of patients seen. We observed that there were both very low and very high efficiency scores within each model. These variations were larger than variations in average scores across models

Interplay between phosphorylation and palmitoylation mediates plasma membrane targeting and sorting of GAP43.

Phosphorylation and lipidation provide posttranslational mechanisms that contribute to the distribution of cytosolic proteins in growing nerve cells. The growth-associated protein GAP43 is susceptible to both phosphorylation and S-palmitoylation and is enriched in the tips of extending neurites. However, how phosphorylation and lipidation interplay to mediate sorting of GAP43 is unclear. Using a combination of biochemical, genetic, and imaging approaches, we show that palmitoylation is required for membrane association and that phosphorylation at Ser-41 directs palmitoylated GAP43 to the plasma membrane. Plasma membrane association decreased the diffusion constant fourfold in neuritic shafts. Sorting to the neuritic tip required palmitoylation and active transport and was increased by phosphorylation-mediated plasma membrane interaction. Vesicle tracking revealed transient association of a fraction of GAP43 with exocytic vesicles and motion at a fast axonal transport rate. Simulations confirmed that a combination of diffusion, dynamic plasma membrane interaction and active transport of a small fraction of GAP43 suffices for efficient sorting to growth cones. Our data demonstrate a complex interplay between phosphorylation and lipidation in mediating the localization of GAP43 in neuronal cells. Palmitoylation tags GAP43 for global sorting by piggybacking on exocytic vesicles, whereas phosphorylation locally regulates protein mobility and plasma membrane targeting of palmitoylated GAP43