Erratum to "Use of a real-time location system to detect cows in distinct functional areas within a barn" (JDS Commun. 2:217-222).

[This corrects the article DOI: 10.3168/jdsc.2020-0050.].

Use of a real-time location system to detect cows in distinct functional areas within a barn.

Automated sensor-based monitoring of cows has become an important tool in herd management to improve or maintain animal health and welfare. Location systems offer the ability to locate animals within the barn for, for example, artificial insemination. Furthermore, they have the potential to measure the time cows spend in important areas of the barn, which might indicate need for improvement in the management of the herd or individuals. In this study, we tested the sensor-based real-time location system (RTLS) Smartbow (SB, Smartbow GmbH) under field conditions. The objectives of this study were (1) to determine the accuracy of the system to predict the location of the cow and the agreement between visual observations and RTLS observations for the total time spent by cows in relevant areas of the barn and (2) to compare the performance of 2 different algorithms (Alg1 and Alg2) for cow location. The study was conducted on a commercial Austrian dairy farm. In total, 35 lactating cows were video recorded for 3 consecutive days. From these recordings, approximately 1 h was selected randomly each day for every cow (3 d × 35 cows). Simultaneously, location data were collected and classified by the RTLS system as dedicated to the alley, feed bunk, or cubicle on a 1-min resolution. A total of 6,030 paired observations were derived from visual observations (VO) and the RTLS and used for the final data analysis. Substantial agreement of categorical data between VO and SB was obtained by Cohen's kappa for both algorithms (Alg1 = 0.76 and Alg2 = 0.78). Similar results were achieved by both algorithms throughout the study, with a slight improvement for Alg2. The ability of the system to locate the cows in the predefined areas was assessed, and the results from Alg2 showed sensitivity, specificity, and positive predictive value of alley (74.0, 91.2, and 76.9%), feed bunk (93.5, 86.2, and 89.1%), and cubicle (90.5, 83.3, and 95.4%) and an overall accuracy of 87.6%.The correlation coefficient (r) between VO and SB for the total time cows spent (within 1 h) in the predefined areas was good to strong (r = 0.82, 0.98, and 0.92 for alley, feed bunk, and cubicle, respectively). These results show the potential of the system to automatically assess total time spent by cows in important areas of the barn for indoor settings. Future studies should focus on evaluating 24-h periods to assess time budgets and to combine technologies such as accelerometers and location systems to improve the performance of behavior prediction in dairy cows.

Morphometric classification and spatial organization of spiral ganglion neurons in the human cochlea: consequences for single fiber response to electrical stimulation.

The unique, unmyelinated perikarya of spiral ganglion cells (SGCs) in the human cochlea are often arranged in functional units covered by common satellite glial cells. This micro anatomical peculiarity presents a crucial barrier for an action potential (AP) travelling from the sensory receptors to the brain. Confocal microscopy was used to acquire systematically volumetric data on perikarya and corresponding nuclei in their full dimension along the cochlea of two individuals. Four populations of SGCs within the human inner ear of two different specimens were identified using agglomerative hierarchical clustering, contrary to the present distinction of two groups of SGCs. Furthermore, we found evidence of a spatial arrangement of perikarya and their accordant nuclei along the cochlea spiral. In this arrangement, the most uniform sizes of cell bodies are located in the middle turn, which represents the majority of phonational frequencies. Since single-cell recordings from other mammalians may not be representative to humans and human SGCs are not accessible for physiological measurements, computer simulation has been used to quantify the effect of varying soma size on single neuron response to electrical micro stimulation. Results show that temporal parameters of the spiking pattern are affected by the size of the cell body. Cathodic stimulation was found to induce stronger variations of spikes while also leading to the lowest thresholds and longest latencies. Therefore, anodic stimulation leads to a more uniform excitation profile among SGCs with different cell body size.