Development of Fuses for Protection of Geiger-Mode Avalanche Photodiode Arrays

Current-limiting fuses composed of Ti/Al/Ni were developed for use in Geiger-mode avalanche photodiode arrays for each individual pixel in the array. The fuses were designed to burn out at ∼4.5 × 10[superscript −3] A and maintain post-burnout leakage currents less than 10[superscript −7] A at 70 V sustained for several minutes. Experimental fuse data are presented and successful incorporation of the fuses into a 256 × 64 pixel InP-based Geiger-mode avalanche photodiode array is reported

DeepCount: In-Field Automatic Quantification of Wheat Spikes Using Simple Linear Iterative Clustering and Deep Convolutional Neural Networks

Crop yield is an essential measure for breeders, researchers and farmers and is comprised of and may be calculated by the number of ears/m2, grains per ear and thousand grain weight. Manual wheat ear counting, required in breeding programmes to evaluate crop yield potential, is labour intensive and expensive; thus, the development of a real-time wheat head counting system would be a significant advancement. In this paper, we propose a computationally efficient system called DeepCount to automatically identify and count the number of wheat spikes in digital images taken under the natural fields conditions. The proposed method tackles wheat spike quantification by segmenting an image into superpixels using Simple Linear Iterative Clustering (SLIC), deriving canopy relevant features, and then constructing a rational feature model fed into the deep Convolutional Neural Network (CNN) classification for semantic segmentation of wheat spikes. As the method is based on a deep learning model, it replaces hand-engineered features required for traditional machine learning methods with more efficient algorithms. The method is tested on digital images taken directly in the field at different stages of ear emergence/maturity (using visually different wheat varieties), with different canopy complexities (achieved through varying nitrogen inputs), and different heights above the canopy under varying environmental conditions. In addition, the proposed technique is compared with a wheat ear counting method based on a previously developed edge detection technique and morphological analysis. The proposed approach is validated with image-based ear counting and ground-based measurements. The results demonstrate that the DeepCount technique has a high level of robustness regardless of variables such as growth stage and weather conditions, hence demonstrating the feasibility of the approach in real scenarios. The system is a leap towards a portable and smartphone assisted wheat ear counting systems, results in reducing the labour involved and is suitable for high-throughput analysis. It may also be adapted to work on RGB images acquired from UAVs

Modulation of innate immune-related genes and glucocorticoid synthesis in gnotobiotic full-sibling European sea bass (<i>Dicentrarchus labrax</i>) larvae challenged with <i>Vibrio anguillarum</i>

Although several efforts have been made to describe the immunoendocrine interaction in fish, there are no studies to date focusing on the characterization of the immune response and glucocorticoid synthesis using the host–pathogen interaction on larval stage as an early developmental stage model of study. Therefore, the aim of this study was to evaluate the glucocorticoid synthesis and the modulation of stress- and innate immune-related genes in European sea bass (Dicentrarchus labrax) larvae challenged with Vibrio anguillarum. For this purpose, we challenged by bath full-sibling gnotobiotic sea bass larvae with 107 CFU mL−1 of V. anguillarum strain HI 610 on day 5 post-hatching (dph). The mortality was monitored up to the end of the experiment [120 hours post-challenge (hpc)]. While no variations were registered in non-challenged larvae maintained under gnotobiotic conditions (93.20% survival at 120 hpc), in the challenged group a constant and sustained mortality was observed from 36 hpc onward, dropping to 18.31% survival at 120 hpc. Glucocorticoid quantification and expression analysis of stress- and innate immunity-related genes were carried out in single larvae. The increase of cortisol, cortisone and 20β-dihydrocortisone was observed at 120 hpc, although did not influence upon the modulation of stress-related genes (glucocorticoid receptor 1 [gr1], gr2, and heat shock protein 70 [hsp70]). On the other hand, the expression of lysozyme, transferrin, and il-10 differentially increased at 120 hpc together with a marked upregulation of the pro-inflammatory cytokines (il-1β and il-8) and hepcidin, suggesting a late activation of defense mechanisms against V. anguillarum. Importantly, this response coincided with the lowest survival observed in challenged groups. Therefore, the increase in markers associated with glucocorticoid synthesis together with the upregulation of genes associated with the anti-inflammatory response suggests that in larvae infected with V. anguillarum a pro-inflammatory response at systemic level takes place, which then leads to the participation of other physiological mechanisms at systemic level to counteract the effect and the consequences of such response. However, this late systemic response could be related to the previous high mortality observed in sea bass larvae challenged with V. anguillarum

Using expert elicitation to abridge the Welfare Quality® protocol for monitoring the most adverse dairy cattle welfare impairments

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14–17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R(2) = 0.91). The WI allows both numerical (0–100) as a qualitative (“not classified” to “excellent”) evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects that cannot be detected adequately by the current selection of measures