Mice emit ultrasonic vocalizations (USV) that communicate socially-relevant information. To detect and classify these USVs, here we describe VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect USVs in audio files, eliminating the need for user-defined parameters. VocalMat also uses computational vision and machine learning methods to classify USVs into distinct categories. In a dataset of >4,000 USVs emitted by mice, VocalMat detected over 98% of manually labeled USVs and accurately classified ~86% of the USVs out of eleven USV categories. We then used dimensionality reduction tools to analyze the probability distribution of USV classification among different experimental groups, providing a robust method to quantify and qualify the vocal repertoire of mice. Thus, VocalMat makes it possible to perform automated, accurate, and quantitative analysis of USVs without the need for user inputs, opening the opportunity for detailed and high-throughput analysis of this behavior.

Artificial lighting is one of the most powerful management tools available to commercial layer producers. Artificial light allows anticipating or delaying the beginning of lay, improving egg production, and optimizing feed efficiency. This study aimed at comparing the performance of commercial layers submitted to lighting using different LED colors or conventional incandescent lamps. The study was carried out in a layer house divided in isolated environments in order to prevent any influenced from the neighboring treatments. In total, 360 Isa Brown layers, with an initial age of 56 weeks, were used. The following light sources were used: blue LED, yellow LED, green LED, red LED, white LED, and 40W incandescent light. Birds in all treatment were submitted to a 17-h continuous lighting program, and were fed a corn and soybean meal-based diet. A completely randomized experimental design with subplots was applied, with 24 treatments (six light sources and four periods) of three replicates. Egg production (%) was significantly different (p<0.05) among treatments, with the best results obtained with red LED, white LED, and incandescent light sources. Egg weight, feed intake, and internal egg quality (albumen height, specific gravity, and Haugh units) were not influenced (p>0.05) by light source. It was concluded that the replacement of incandescent light bulbs by white and red LEDs does not cause any negative effect on the egg production of commercial layers.

Novel nickel complexes containing {O,O}-chelating hydroxamate ligands were prepared by attack of the hydroxamic acid by the hydroxo ligand, and the crystal structure shows the nickel atom in a five-coordinate environment that has structural features similar to those of inhibited urease.

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Mice emit ultrasonic vocalizations (USV) to transmit socially-relevant information. To detect and classify these USVs, here we describe the development of VocalMat. VocalMat is a software that uses image-processing and differential geometry approaches to detect USVs in audio files, eliminating the need for user-defined parameter tuning. VocalMat also uses computational vision and machine learning methods to classify USVs into distinct categories. In a dataset of >4,000 USVs emitted by mice, VocalMat detected more than >98% of the USVs and accurately classified ≈86% of USVs when considering the most likely label out of 11 different USV types. We then used Diffusion Maps and Manifold Alignment to analyze the probability distribution of USV classification among different experimental groups, providing a robust method to quantify and qualify the vocal repertoire of mice. Thus, VocalMat allows accurate and highly quantitative analysis of USVs, opening the opportunity for detailed and high-throughput analysis of this behavior. * Present address: Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven -CT, United States of America 2 Results Detection of mouse USVs using imaging processingVocalMat uses multiple steps to analyze USVs from vocalizing mice in audio files (see Figure 1A for the general workflow). Initially, the audio recordings are converted into high-resolution spectrograms through a short-time Fourier transformation (see Methods and Materials). The resulting spectrogram consists of a matrix, wherein each element corresponds to an intensity value (power spectrum represented in decibels) for each time-frequency component. The spectrogram is then analyzed in terms of its time-frequency plane, where high-intensity values are represented by brighter pixels in a gray-scale image ( Figure 1B). The gray-scale image undergoes contrast enhancement and adaptive thresholding for binarization (see Methods and materials). The segmented objects are further refined via morphological operations ( Figure 1C and Figure S1), thus resulting in a list of segmented blobs (hereafter referred to as USV candidates) with their corresponding spectral features ( Figure 1D).This list of USV candidates may contain noise (i.e., detected particles that are not part of any USV) and multiple candidates that correspond to the same USV. To address this, a minimum of 10 ms interval between two successive and distinct syllables is assumed based on experimental observations [9]. To reduce the amount of data stored for each USV, the features extracted from detected candidates are represented by a mean frequency and intensity every 0.5 ms. The means are calculated for all the individual candidates, including the ones overlapping in time, hence preserving relevant features such as duration, frequency, intensity, and harmonic components ( Figure 1D).Harmonic components are also referred to as nonlinear components or composite [31,30]. Here, we did not consider harmonic components as a different syllable, but rather as an extra fea...

The pre-slaughter period is considered critical in broiler production. Several factors contribute to increase the birds' stress, such as handling, harvesting, and transportation, negatively affecting their welfare. This study aimed at evaluating the addition of lemon grass (Cymbopogon citratus Stapf) to the drinking water of broilers during the pre-slaughter period on their behavior, blood cortisol, and surface temperature. The study was carried out at the experimental farm of the Federal University of Grande Dourados (UFGD), Dourados, MS, Brazil. In total, 2594 broilers were distributed according to a completely randomized experimental design, in a 3x2x2 factorial arrangement, with four replicates per treatment. Treatments consisted of three different lemon grass levels (Cymbopogon citratus Stapf) used in the form of an infusion (0, 0.1, and 5 g per L of water), sex (male or female), and genetic strain (Ross® 308 or Cobb® 500). The infusion was offered when birds were 42 days old. On that day, blood was collected for blood cortisol level determination, broiler surface temperature was recorded, and an ethogram was applied to register broiler behavior. Blood cortisol level and broiler surface temperature were not affected by treatments (p>0.05). The behavior of beak opening was different between the genetic strains (p<0.05), being more frequent in Ross® 308 broilers. Lemon grass water content did not affect broilers' surface temperature when consumed during the pre-slaughter period.

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