A standardised static in vitro digestion method suitable for food – an international consensus

peer-reviewedSimulated gastro-intestinal digestion is widely employed in many fields of food and nutritional sciences, as conducting human trials are often costly, resource intensive, and ethically disputable. As a consequence, in vitro alternatives that determine endpoints such as the bioaccessibility of nutrients and non-nutrients or the digestibility of macronutrients (e.g. lipids, proteins and carbohydrates) are used for screening and building new hypotheses. Various digestion models have been proposed, often impeding the possibility to compare results across research teams. For example, a large variety of enzymes from different sources such as of porcine, rabbit or human origin have been used, differing in their activity and characterization. Differences in pH, mineral type, ionic strength and digestion time, which alter enzyme activity and other phenomena, may also considerably alter results. Other parameters such as the presence of phospholipids, individual enzymes such as gastric lipase and digestive emulsifiers vs. their mixtures (e.g. pancreatin and bile salts), and the ratio of food bolus to digestive fluids, have also been discussed at length. In the present consensus paper, within the COST Infogest network, we propose a general standardised and practical static digestion method based on physiologically relevant conditions that can be applied for various endpoints, which may be amended to accommodate further specific requirements. A frameset of parameters including the oral, gastric and small intestinal digestion are outlined and their relevance discussed in relation to available in vivo data and enzymes. This consensus paper will give a detailed protocol and a line-by-line, guidance, recommendations and justifications but also limitation of the proposed model. This harmonised static, in vitro digestion method for food should aid the production of more comparable data in the future.COST action FA1005 Infogest22 (http://www.cost-infogest.eu/) is acknowledged for providing funding for travel, meetings and conferences

Metabolic Effects of Krill Oil are Essentially Similar to Those of Fish Oil but at Lower Dose of EPA and DHA, in Healthy Volunteers

The purpose of the present study is to investigate the effects of krill oil and fish oil on serum lipids and markers of oxidative stress and inflammation and to evaluate if different molecular forms, triacylglycerol and phospholipids, of omega-3 polyunsaturated fatty acids (PUFAs) influence the plasma level of EPA and DHA differently. One hundred thirteen subjects with normal or slightly elevated total blood cholesterol and/or triglyceride levels were randomized into three groups and given either six capsules of krill oil (N = 36; 3.0 g/day, EPA + DHA = 543 mg) or three capsules of fish oil (N = 40; 1.8 g/day, EPA + DHA = 864 mg) daily for 7 weeks. A third group did not receive any supplementation and served as controls (N = 37). A significant increase in plasma EPA, DHA, and DPA was observed in the subjects supplemented with n-3 PUFAs as compared with the controls, but there were no significant differences in the changes in any of the n-3 PUFAs between the fish oil and the krill oil groups. No statistically significant differences in changes in any of the serum lipids or the markers of oxidative stress and inflammation between the study groups were observed. Krill oil and fish oil thus represent comparable dietary sources of n-3 PUFAs, even if the EPA + DHA dose in the krill oil was 62.8% of that in the fish oil

Modelling and Compensating Measurement Errors Caused by Scattering in Time-Of-Flight Cameras

Recently, Range Imaging (RIM) cameras have become available that capture high resolution range images at video rate. Such cameras measure the distance from the scene for each pixel independently based upon a measured time of flight (TOF). Some cameras, such as the SwissRanger™ SR-3000, measure the TOF based on the phase shift of reflected light from a modulated light source. Such cameras are shown to be susceptible to severe distortions in the measured range due to light scattering within the lens and camera. Earlier work induced using a simplified Gaussian point spread function and inverse filtering to compensate for such distortions. In this work a method is proposed for how to identify and use generally shaped empirical models for the point spread function to get a more accurate compensation. The otherwise difficult inverse problem is solved by using the forward model iteratively, according to well established procedures from image restoration. Each iteration is done as a sequential process, starting with the brightest parts of the image and then moving sequentially to the least bright parts, with each step subtracting the estimated effects from the measurements. This approach gives a faster and more reliable compensation convergence. An average reduction of the error by more than 60% is demonstrated on real images. The computation load corresponds to one or two convolutions of the measured complex image with a real filter of the same size as the image

A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scanning

We present an implementation of a novel foveating 3D sensor concept, inspired by the human eye, which intends to allow future robots to better interact with their surroundings. The sensor is based on a time-of-flight laser scanning technology, where each range distance measurement is performed individually for increased quality. Micro-mirrors enable detailed control on where and when each sample point is acquired in the scene. By finding regions-of-interest (ROIs) and mainly concentrating the data acquisition here, the spatial resolution or frame rate of these ROIs can be significantly increased compared to a non-foveating system.Foveation is enabled through a real-time implementation of a feed-back control loop for the sensor hardware, based on vision algorithms for 3D scene analysis. In this paper, we describe and apply an algorithm for detecting ROIs based on motion detection in range data using background modeling. Heuristics are incorporated to cope with camera motion. We report first results applying this algorithmto scenes with moving objects, and show that the foveation capability allows the frame rate to be increased by up to 8.2 compared to a non-foveating sensor, utilizing up to 99% of the potential frame rate increase. The incorporated heuristics significantly improves the foveation’s performance for moving camera scenes.A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scannin

A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scanning

We present an implementation of a novel foveating 3D sensor concept, inspired by the human eye, which intends to allow future robots to better interact with their surroundings. The sensor is based on a time-of-flight laser scanning technology, where each range distance measurement is performed individually for increased quality. Micro-mirrors enable detailed control on where and when each sample point is acquired in the scene. By finding regions-of-interest (ROIs) and mainly concentrating the data acquisition here, the spatial resolution or frame rate of these ROIs can be significantly increased compared to a non-foveating system. Foveation is enabled through a real-time implementation of a feed-back control loop for the sensor hardware, based on vision algorithms for 3D scene analysis. In this paper, we describe and apply an algorithm for detecting ROIs based on motion detection in range data using background modeling. Heuristics are incorporated to cope with camera motion. We report first results applying this algorithm to scenes with moving objects, and show that the foveation capability allows the frame rate to be increased by up to 8.2 compared to a non-foveating sensor, utilizing up to 99% of the potential frame rate increase. The incorporated heuristics significantly improves the foveation’s performance for moving camera scenes

Modelling and Compensating Measurement Errors Caused by Scattering in Time-Of-Flight Cameras

Recently, Range Imaging (RIM) cameras have become available that capture high resolution range images at video rate. Such cameras measure the distance from the scene for each pixel independently based upon a measured time of flight (TOF). Some cameras, such as the SwissRanger™ SR-3000, measure the TOF based on the phase shift of reflected light from a modulated light source. Such cameras are shown to be susceptible to severe distortions in the measured range due to light scattering within the lens and camera. Earlier work induced using a simplified Gaussian point spread function and inverse filtering to compensate for such distortions. In this work a method is proposed for how to identify and use generally shaped empirical models for the point spread function to get a more accurate compensation. The otherwise difficult inverse problem is solved by using the forward model iteratively, according to well established procedures from image restoration. Each iteration is done as a sequential process, starting with the brightest parts of the image and then moving sequentially to the least bright parts, with each step subtracting the estimated effects from the measurements. This approach gives a faster and more reliable compensation convergence. An average reduction of the error by more than 60% is demonstrated on real images. The computation load corresponds to one or two convolutions of the measured complex image with a real filter of the same size as the image

Adaptive Structured Light with Scatter Correction for High-Precision Underwater 3D Measurements

High-precision underwater 3D cameras are required to automate many of the traditional subsea inspection, maintenance and repair (IMR) operations. In this paper we introduce a novel multi-frequency phase stepping (structured light) method for high-precision 3D estimation even in turbid water. We introduce an adaptive phase-unwrapping procedure which uses the phase-uncertainty to determine the highest frequency that can be reliably unwrapped. Light scattering adversely affects the phase estimate. We propose to remove the effect of forward scatter with an unsharp filter and a model-based method to remove the backscatter effect. Tests in varying turbidity show that the scatter correction removes the adverse effect of scatter on the phase estimates. The adaptive frequency unwrapping with scatter correction results in images with higher accuracy and precision and less phase unwrap errors than the Gray-Code Phase Stepping (GCPS) approach

A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scanning

We present an implementation of a novel foveating 3D sensor concept, inspired by the human eye, which intends to allow future robots to better interact with their surroundings. The sensor is based on a time-of-flight laser scanning technology, where each range distance measurement is performed individually for increased quality. Micro-mirrors enable detailed control on where and when each sample point is acquired in the scene. By finding regions-of-interest (ROIs) and mainly concentrating the data acquisition here, the spatial resolution or frame rate of these ROIs can be significantly increased compared to a non-foveating system.Foveation is enabled through a real-time implementation of a feed-back control loop for the sensor hardware, based on vision algorithms for 3D scene analysis. In this paper, we describe and apply an algorithm for detecting ROIs based on motion detection in range data using background modeling. Heuristics are incorporated to cope with camera motion. We report first results applying this algorithmto scenes with moving objects, and show that the foveation capability allows the frame rate to be increased by up to 8.2 compared to a non-foveating sensor, utilizing up to 99% of the potential frame rate increase. The incorporated heuristics significantly improves the foveation’s performance for moving camera scenes.A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scannin

A Motion based Real-time Foveation Control Loop for Rapid and Relevant 3D Laser Scanning

We present an implementation of a novel foveating 3D sensor concept, inspired by the human eye, which intends to allow future robots to better interact with their surroundings. The sensor is based on a time-of-flight laser scanning technology, where each range distance measurement is performed individually for increased quality. Micro-mirrors enable detailed control on where and when each sample point is acquired in the scene. By finding regions-of-interest (ROIs) and mainly concentrating the data acquisition here, the spatial resolution or frame rate of these ROIs can be significantly increased compared to a non-foveating system. Foveation is enabled through a real-time implementation of a feed-back control loop for the sensor hardware, based on vision algorithms for 3D scene analysis. In this paper, we describe and apply an algorithm for detecting ROIs based on motion detection in range data using background modeling. Heuristics are incorporated to cope with camera motion. We report first results applying this algorithm to scenes with moving objects, and show that the foveation capability allows the frame rate to be increased by up to 8.2 compared to a non-foveating sensor, utilizing up to 99% of the potential frame rate increase. The incorporated heuristics significantly improves the foveation’s performance for moving camera scenes

ROV Navigation in a Fish Cage with Laser-Camera Triangulation

Aquaculture net cage inspection and maintenance is a central issue in fish farming. Inspection using autonomous underwater vehicles is a promising solution. This paper proposes laser-camera triangulation for pose estimation to enable autonomous net following for an autonomous vehicle. The laser triangulation 3D data is experimentally compared to a doppler velocity log (DVL) in an active fish farm. We show that our system is comparable in performance to a DVL for distance and angular pose measurements. Laser triangulation is promising as a short distance ranging sensor for autonomous vehicles at a low cost compared to acoustic sensors