Use of open-top chambers to study the effect of climate change in aquatic ecosystems

The aim of this research was to explore the possibility to use inexpensive open-top chambers (OTCs) as passive artificial warming devices in experimental aquatic studies. Our results show that OTCs give a significant temperature increase compared with the control. The measured increase (up to an average of 2.3°C) corresponds with predicted climatic warming. Due to their open top, the light quantity and quality is only minimally reduced. We found that OTCs are especially suited for studying the effect of climate change in small waters as the vertical temperature gradients remain unchanged. They can also easily be transported to remote environments. We discuss other advantages and disadvantages of these devices for aquatic studies and compare them with other warming devices

Source location encoding in the fish lateral line canal

The position of a hydrodynamic dipole source, as encoded in a linear array of mechano-detecting neuromasts in the fish lateral line canal, was electrophysiologically investigated. Measured excitation patterns along the lateral line were compared to theoretical predictions and were found to be in good agreement. The results demonstrate that information on the position of a vibrating source from a fish is linearly coded in the spatial characteristics of the excitation pattern of pressure gradients distributed along the lateral line canal. Several algorithms are discussed that could potentially be used by a fish to decode lateral line excitation patterns, in order to localise a source and its axis of vibration. Specifically, a wavelet transform of a 1-D excitation pattern is shown to reconstruct a 2-D image of dipole sources located within a distance comparable to the body length of a fish and with a close range spatial accuracy twice the inter-neuromast distance

Use and usability of custom-made orthopedic shoes

The goal of this study was to investigate the use of custom-made orthopedic shoes (OS) and the association between the use of OS and the most relevant aspects of their usability. Over a 6-month period, patients meeting the inclusion criteria were recruited by 12 orthopedic shoe companies scattered throughout the Netherlands and asked to complete a questionnaire composed of a pre- and post-OS section. Patients with different pathologies were included in the study (n = 339; response 67%). Mean age of the patients was 63 +/- 15 years, and 38% were male. Three months after delivery, 81% of the patients used their OS frequently (4-7 days/week), 13% occasionally (1-3 days/week), and 6% did not use their OS. Associations were found between use and all measured aspects of usability (p-values varied from <0.001 to 0.028). Patients who used their OS more often had a more positive opinion regarding all the aspects of usability. We conclude that all aspects of the usability of OS are relevant in relation to their use and should be taken into account when prescribing and evaluating OS

Performance of Neural Networks in Source Localization using Artificial Lateral Line Sensor Configurations

Artificial lateral lines (ALL) are used to detect the movement and locations of sources underwater, and are based on the lateral line organ found in fish and amphibians. Experiments have been performed to evaluate if the localization performance of neural networks, trained on simulated ALL sensor data, can be improved through adjustments of the internal ALL sensor positions. A Cramér-Rao lower bound analysis was performed on a subset of handpicked sensor configurations to estimate the likely performance of various configurations. The best and worst configurations were used to generate simulated datasets with which extreme learning machines (ELMs) and convolutional neural networks (CNNs) were trained and tested on their location accuracy. Simulated datasets consisted of two sources in a three-dimensional basin and the sensor readings of 16 ALL sensors. Results show that the best performing configuration consists of improved ELM and CNN localization performances, while also demonstrating that ELMs are capable of localizing multiple sources in three-dimensional aquatic environments, with comparable if not better results than CNNs