Impact of calcium on salivary α-amylase activity, starch paste apparent viscosity and thickness perception

Thickness perception of starch-thickened products during eating has been linked to starch viscosity and salivary amylase activity. Calcium is an essential cofactor for α-amylase and there is anecdotal evidence that adding extra calcium affects amylase activity in processes like mashing of beer. The aims of this paper were to (1) investigate the role of salivary calcium on α-amylase activity and (2) to measure the effect of calcium concentration on apparent viscosity and thickness perception when interacting with salivary α-amylase in starch-based samples. α-Amylase activity in saliva samples from 28 people was assessed using a typical starch pasting cycle (up to 95 °C). The activity of the enzyme (as measured by the change in starch apparent viscosity) was maintained by the presence of calcium, probably by protecting the enzyme from heat denaturation. Enhancement of α-amylase activity by calcium at 37 °C was also observed although to a smaller extent. Sensory analysis showed a general trend of decreased thickness perception in the presence of calcium, but the result was only significant for one pair of samples, suggesting a limited impact of calcium enhanced enzyme activity on perceived thickness

A Model that Predicts the Material Recognition Performance of Thermal Tactile Sensing

Tactile sensing can enable a robot to infer properties of its surroundings, such as the material of an object. Heat transfer based sensing can be used for material recognition due to differences in the thermal properties of materials. While data-driven methods have shown promise for this recognition problem, many factors can influence performance, including sensor noise, the initial temperatures of the sensor and the object, the thermal effusivities of the materials, and the duration of contact. We present a physics-based mathematical model that predicts material recognition performance given these factors. Our model uses semi-infinite solids and a statistical method to calculate an F1 score for the binary material recognition. We evaluated our method using simulated contact with 69 materials and data collected by a real robot with 12 materials. Our model predicted the material recognition performance of support vector machine (SVM) with 96% accuracy for the simulated data, with 92% accuracy for real-world data with constant initial sensor temperatures, and with 91% accuracy for real-world data with varied initial sensor temperatures. Using our model, we also provide insight into the roles of various factors on recognition performance, such as the temperature difference between the sensor and the object. Overall, our results suggest that our model could be used to help design better thermal sensors for robots and enable robots to use them more effectively.Comment: This article is currently under review for possible publicatio

A Review of Smart Materials in Tactile Actuators for Information Delivery

As the largest organ in the human body, the skin provides the important sensory channel for humans to receive external stimulations based on touch. By the information perceived through touch, people can feel and guess the properties of objects, like weight, temperature, textures, and motion, etc. In fact, those properties are nerve stimuli to our brain received by different kinds of receptors in the skin. Mechanical, electrical, and thermal stimuli can stimulate these receptors and cause different information to be conveyed through the nerves. Technologies for actuators to provide mechanical, electrical or thermal stimuli have been developed. These include static or vibrational actuation, electrostatic stimulation, focused ultrasound, and more. Smart materials, such as piezoelectric materials, carbon nanotubes, and shape memory alloys, play important roles in providing actuation for tactile sensation. This paper aims to review the background biological knowledge of human tactile sensing, to give an understanding of how we sense and interact with the world through the sense of touch, as well as the conventional and state-of-the-art technologies of tactile actuators for tactile feedback delivery

Evaluation or perfusion and thermal parameters of skiin tissue using cold provocation and thermographic measurements

Measurement of the perfusion coefficient and thermal parameters of skin tissue using dynamic thermography is presented in this paper. A novel approach based on cold provocation and thermal modelling of skin tissue is presented. The measurement was performed on a person’s forearm using a special cooling device equipped with the Peltier module. The proposed method first cools the skin, and then measures the changes of its temperature matching the measurement results with a heat transfer model to estimate the skin perfusion and other thermal parameters. In order to assess correctness of the proposed approach, the uncertainty analysis was performed

Reactive control and reasoning assistance for scientific laboratory instruments

Scientific laboratory instruments that are involved in chemical or physical sample identification frequently require substantial human preparation, attention, and interactive control during their operation. Successful real-time analysis of incoming data that supports such interactive control requires: (1) a clear recognition of variance of the data from expected results; and (2) rapid diagnosis of possible alternative hypotheses which might explain the variance. Such analysis then aids in decisions about modifying the experiment protocol, as well as being a goal itself. This paper reports on a collaborative project at the NASA Ames Research Center between artificial intelligence researchers and planetary microbial ecologists. Our team is currently engaged in developing software that autonomously controls science laboratory instruments and that provides data analysis of the real-time data in support of dynamic refinement of the experiment control. the first two instruments to which this technology has been applied are a differential thermal analyzer (DTA) and a gas chromatograph (GC). coupled together, they form a new geochemicstry and microbial analysis tool that is capable of rapid identification of the organiz and mineralogical constituents in soils. The thermal decomposition of the minerals and organics, and the attendance release of evolved gases, provides data about the structural and molecular chemistry of the soil samples

The Faculty Notebook, April 2010

The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost

A supramodal representation of the body surface

The ability to accurately localize both tactile and painful sensations on the body is one of the most important functions of the somatosensory system. Most accounts of localization refer to the systematic spatial relation between skin receptors and cortical neurons. The topographic organization of somatosensory neurons in the brain provides a map of the sensory surface. However, systematic distortions in perceptual localization tasks suggest that localizing a somatosensory stimulus involves more than simply identifying specific active neural populations within a somatotopic map. Thus, perceptual localization may depend on both afferent inputs and other unknown factors. In four experiments, we investigated whether localization biases vary according to the specific skin regions and subset of afferent fibers stimulated. We represented localization errors as a ‘perceptual map’ of skin locations. We compared the perceptual maps of stimuli that activate Aβ (innocuous touch), Aδ (pinprick pain), and C fibers (non-painful heat) on both the hairy and glabrous skin of the left hand. Perceptual maps exhibited systematic distortions that strongly depended on the skin region stimulated. We found systematic distal and radial (i.e., towards the thumb) biases in localization of touch, pain, and heat on the hand dorsum. A less consistent proximal bias was found on the palm. These distortions were independent of the population of afferent fibers stimulated, and also independent of the response modality used to report localization. We argue that these biases are likely to have a central origin, and result from a supramodal representation of the body surface

Touch uses frictional cues to discriminate flat materials

In a forced-choice task, we asked human participants to discriminate by touch alone glass plates from transparent polymethyl methacrylate (PMMA) plastic plates. While the surfaces were flat and did not exhibit geometric features beyond a few tens of nanometres, the materials differed by their molecular structures. They produced similar coefficients of friction and thermal effects were controlled. Most participants performed well above chance and participants with dry fingers discriminated the materials especially well. Current models of tactile surface perception appeal to surface topography and cannot explain our results. A correlation analysis between detailed measurements of the interfacial forces and discrimination performance suggested that the perceptual task depended on the transitory contact phase leading to full slip. This result demonstrates that differences in interfacial mechanics between the finger and a material can be sensed by touch and that the evanescent mechanics that take place before the onset of steady slip have perceptual value