Ilaria Fontana

Scintillation characteristics of Lu3Al5O12:Ce optical ceramics

Optical absorption, luminescence, and scintillation characteristics of Lu3Al5O12:Ce optical ceramics were measured and compared with an analogous high quality single crystal. Optical absorption of the former shows an additional light scattering loss due to nanovoids and/or refraction index inhomogeneities. Even though radioluminescence intensity of the optical ceramics prepared by a coprecipitation route exceeds that of single crystal, its scintillation light yield is lower due to the charge carrier retrapping in the process of energy transfer towards the Ce3+ emission centers. Retrapping processes are evidenced by thermoluminescence measurements below room temperature. Lu3Al5O12:Ce optical ceramics does not show the presence of the LuAl antisite defects which decreases the scintillation figure of merit in single crystals grown from the melt [M. Nikl, Phys. Status Solidi A 202, 201 (2005)]. Furthermore, using the ceramic technology, one can achieve both the homogeneous doping and higher Ce concentration. ...

Scintillator Materials—Achievements, Opportunities, and Puzzles

Participation of shallow and deep traps in the processes of energy transfer and capture is studied by means of time- resolved emission spectroscopy and thermoluminescence in several groups of the Ce3+ and Pr3+-doped complex oxide single crystal scintillators. Tunnelling-driven recombination processes are distinguished in all the groups of examined materials: closely spaced electron and hole traps give rise to the t-1 phosphorescence decays at low temperatures in the Ce-doped aluminum garnets and perovskites, while thermally assisted tunneling process is proposed to explain temperature independent trap depth in glow curve peaks within 50-250 degC in Ce-doped lutetium orthosilicates.

Technical note: Validation of a commercial system for the continuous and automated monitoring of dairy cow activity

Current farm sizes do not allow the precise identification and tracking of individual cows and their health and behavioral records. Currently, the application of information technology within intensive dairy farming takes a key role in proper routine management to improve animal welfare and to enhance the comfort of dairy cows. An existing application based on information technology is represented by the GEA CowView system (GEA Farm Technologies, Bönen, Germany). This system is able to detect and monitor animal behavioral activities based on positioning, through the creation of a virtual map of the barn that outlines all the areas where cows have access. The aim of this study was to validate the accuracy, sensitivity, and specificity of data provided by the CowView system. The validation was performed by comparing data automatically obtained from the CowView system with those obtained by a manual labeling procedure performed on video recordings. Data used for the comparisons were represented by the zone-related activities performed by the selected dairy cows and were classified into 2 categories: activity and localization. The duration in seconds of each of the activities/localizations detected both with the manual labeling and with the automated system were used to evaluate the correlation coefficients among data; and subsequently the accuracy, sensitivity, specificity, and positive and negative predictive values of the automated monitoring system were calculated. The results of this validation study showed that the CowView automated monitoring system is able to identify the cow localization/position (alley, trough, cubicles) with high reliability in relation to the zone-related activities performed by dairy cows (accuracy higher than 95%). The results obtained support the CowView system as an innovative potential solution for the easier management of dairy cows.

An innovative approach to predict the growth in intensive poultry farming

Chicken weight provides information about growth and feed conversion of the flock.We record and analyse broiler vocalisations under normal farm conditions.We find a significant correlation between frequency of sounds and weight of the birds.The more the birds grow, the lower the frequency of the sounds emitted by the animals.Young chicks vocalise at high frequency under non-stress condition. Chicken weight provides information about growth and feed conversion of the flock in order to identify deviations from the expected homogeneous growth trend of the birds. This paper proposes a novel method to automatically measure the growth rate of broiler chickens by sound analysis.Through the application of process engineering, Precision Livestock Farming (PLF) can combine audio and video information into on-line automated tools that can be used to control, monitor and model the behaviour, health and production of animals and their biological response.The aim of this study was to record and analyse broiler vocalisations under normal farm conditions, to identify the relation between animal sounds and their weight. Recordings were made at regular intervals, during the entire life of birds, in order to evaluate the variation of frequency and bandwidth of the sounds emitted by the animals.Two experimental trials were carried out in an indoor reared broiler farm; the audio recording procedures lasted for 38days. The recordings were made, in an automated, non-invasive and non-intrusive way and without disturbing the animals in to the broiler house. Once a week, 50 birds were selected at random and their weight recorded in order to follow the growth trend in the birds.Sound recordings were manually analysed and labelled using the Adobe� Audition� CS6 software.Analysing the sounds recorded, it was possible to find a significant correlation (P<0.001) between the frequencies of the vocalisations recorded and the weight of the broilers.The results explained how the frequency of the sounds emitted by the animals was inversely proportional to the age and to the weight of the broilers; the more they grow, the lower the frequency of the sounds emitted by the animals.This preliminary study, conducted in an indoor reared broiler farm, shows how this method based on the identification of specific frequencies of the sounds, linked to the age and to the weight of the birds, might be used as an early warning method/system to evaluate the health and welfare status of the animals at farm level. This is the basis for a further development of an automated growth monitoring tool.

LabeLLing the behaviour of pigLets and activity monitoring from video as a tooL of assessing interest in different environmentaL enrichments

Abstract The aim of this study was to explore the preference and the duration of interest of weaned pigs to two different types of environmental enrichments using labelling techniques and activity monitoring. Two pens each housing 14 Dalland piglets were monitored using a video camera. The videos were labelled during the weaning phase from 30 to 60 days of age. During this time, the video recording software continuously calculated the activity index of the pigs. To detect pig exploratory and playing behaviour, a wooden block and chain enrichment were introduced into each pen for 30 days. Each video frame was manually labelled during the Day 1, 5 and 30 (24 hours a day) for each pen using the Labelling Tool software. To identify the duration and frequency of interactive episodes with environmental enrichments, pig behaviour was labelled as either: no activity, interacting with chain or interacting with the wooden block. The mean duration of interactive episodes for the chain was greater than for the wooden block (P<0.001), while the frequency of interactive episodes was 28.8% higher for the wooden block than for the chain. By day 5, the mean duration of interaction episodes decreased in both pens and by day 30, only a few interaction episodes were observed. The number of interactive episodes were strictly related to the activity index and depended on the time of the day. The peaks of the mean number of interactive episodes calculated for all days of observations corresponded to the peaks of the mean activity index. Streszczenie Celem badań było sprawdzenie preferencji oraz czasu trwania zainteresowania prosiąt odsadzonych dwoma typami elementów wzbogacających środowisko kojca. Użyto do tego technik analizy obrazu oraz monitoringu aktywności zwierząt. Dwa kojce z 14 prosiętami rasy Dalland (24 prosięta) w wieku od 30 do 60 dni były monitorowane za pomocą kamery. Indeks aktywności prosiąt został obliczony podczas rejestracji nagrań wideo przez oprogramowanie do automatycznego pomiaru aktywności zwierząt. W kojcu został umieszczony na 30 dni drewniany pieniek oraz łańcuch w celu wykrycia zachowań eksploracyjnych i zabawy. Każda klatka zarejestrowanego filmu wideo została przeanalizowana w 1., 5. oraz 30. dniu (24 godziny na dzień) eksperymentu za pomocą oprogramowania do analizy obrazu. W celu zidentyfikowania czasu trwania i częstotliwości interakcji z elementami wzbogacającymi środowisko kojca zachowanie zwierząt zostało oznaczone jako brak aktywności, interakcja z łańcuchem lub interakcja z drewnianym pieńkiem. Zainteresowanie łańcuchem średnio było dłuższe (P<0.001) niż drewnianym pieńkiem. Częstotliwość zabawy drewnianym pieńkiem była 28.8% wyższa niż łańcuchem. Średni czas interakcji z elementami wzbogacającymi środowisko kojca uległ skróceniu w piątym dniu eksperymentu, w obu kojcach. W trzydziestym dniu eksperymentu zauważono ich tylko kilka. Liczba interakcji z elementami wzbogacającymi środowisko kojca była ściśle powiązana z wartością indeksu aktywności zarejestrowanym przez oprogramowanie i zależała od pory dnia. W każdym dniu prowadzonej obserwacji wzrost średniej liczby interakcji odpowiadał wzrostowi średniej wartości indeksu aktywności.

Shallow Traps in Single Crystal Perovskites

The aim of this work is to investigate the influence of shallow traps on scintillating properties of YAlO3:Ce. Wavelength-resolved thermally stimulated luminescence measurements following X-ray irradiation at 10 K have been performed on both undoped and Ce-doped crystals. Different and composite glow curves and emission spectra were obtained. Following glow peaks analysis of YAlO3:Ce, their room temperature decay time was evaluated to be of the order of 10-4 s. The presence of an athermal tunneling recombination process between traps and Ce3+ ions below 100 K has been evidenced by phosphorescence decays.

Discerning Pig Screams in Production Environments

Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration.

Early recognition of bovine respiratory disease in calves using automated continuous monitoring of cough sounds

Abstract Bovine respiratory disease (BRD) complex in calves impairs health and welfare and causes severe economic losses for the Stockperson. Early recognition of BRD should lead to earlier veterinary (antibiotic/anti-inflammatory) treatment interventions thereby reducing the severity of the disease and associated costs. Coughing is one of the clinical manifestations of BRD. It is believed that by automatically and continuously monitoring the sounds within calf houses, and analysing the coughing frequency, early recognition of BRD in calves is possible. Therefore, the objective of the present study was to develop an automated calf cough monitor and examine its potential as an early warning system for BRD in artificially reared dairy calves. The coughing sounds of 62 calves were continuously recorded by a microphone over a three-month period. A sound analysis algorithm was developed to distinguish calf coughs from other sounds (e.g. mechanical sounds). During the sound recording period the health of the calves was assessed and scored periodically per week by a trained human observer. Calves presenting with BRD received antibiotic and/or anti-inflammatory treatment and the dates of treatment were recorded. This treatment date reference served as a comparison for the investigation of whether an increase in coughing frequency could be related to calves developing BRD. The calf cough detection algorithm achieved 50.3% sensitivity, 99.2% specificity and 87.5% precision. Four out of five periods, where coughing frequency was observed to be increased, coincided with the development of BRD in more than one calf. This period of increased coughing frequency was always observed before the calves were treated. Therefore, the calf cough monitor has the potential to identify early onset of BRD in calves.

Shallow traps in YAlO3:Ce single crystal perovskites

The aim of this work is to investigate the influence of shallow traps on scintillating properties of YAlO3:Ce. Wavelength-resolved thermally stimulated luminescence measurements following X-ray irradiation at 10 K have been performed on both undoped and Ce-doped crystals. Different and composite glow curves and emission spectra were obtained. Following glow peaks analysis of YAlO3:Ce, their room temperature decay time was evaluated to be of the order of 10-4 s. The presence of an athermal tunneling recombination process between traps and Ce3+ ions below 100 K has been evidenced by phosphorescence decays.

Application note: Labelling, a methodology to develop reliable algorithm in PLF

Abstract Automatic animal monitoring through Precision Livestock Farming (PLF) tools is a method to support farmers in achieving farm sustainability. The development of PLF systems requires close interdisciplinary collaboration between sector experts, farmers, animal scientists and bio-engineers. Labelling is a key activity in the development of reliable algorithm to be included in PLF tools. It is a set of procedures that animal experts must embark to precisely define and interpret detailed variations in measured field signals. This application note will describe the fundamental aspects of sound and image labelling and how this has enabled the engineering of useful automated PLF systems.