Twinning is a multifactorial trait influenced by both genetic and environmental factors that can negatively impact animal welfare and economic sustainability on commercial dairy operations. To date, using genetic selection as a tool for reducing twinning rates on commercial dairies has been proposed, but not yet implemented. In response to this market need, Zoetis (Kalamazoo, MI, USA) has developed a genomic prediction for twin pregnancies, and included it in a comprehensive multitrait selection index. The objectives of this study were to (1) describe a genetic evaluation for twinning in Holstein cattle, (2) demonstrate the efficacy of the predictions, (3) propose strategies to reduce twin pregnancies using this information. Data were retrieved from commercial dairies and provided directly by producers upon obtaining their permission. The twin pregnancies trait (TWIN) was defined as a pregnancy resulting in birth or abortion of twin calves, classified as a binary (0,1) event, and analysed using a threshold animal model. Predictions for a subset of cows were compared to their on-farm twin records. The heritability for twin pregnancies was 0.088, and genomic predicted transmitting abilities ((g)PTAs) ranged from -7.45-20.79. Genetic correlations between TWIN and other traits were low, meaning that improvement for TWIN will not negatively impact improvement for other traits. TWIN was effectively demonstrated to identify cows most and least likely to experience a twin pregnancy in a given lactation, regardless of reproductive protocol used. Effective inclusion of the prediction in a multitrait selection index offers producers a comprehensive tool to inform selection and management decisions. When combined with sound management practices, this presents a compelling opportunity for dairy producers to proactively reduce the incidence of twin pregnancies on commercial dairy operations.Wild edible plants are an essential component of people's diets in the Mediterranean basin. In Italy, ethnobotanical surveys have received increasing attention in the past two centuries, with some of these studies focusing on wild edible plants. In this regard, the literature in Italy lacks the coverage of some major issues focusing on plants used as herbs and spices. I searched national journals for articles on the use of wild food plants in Italy, published from 1963 to 2020. Aims of the present review were to document plant lore regarding wild herbs and spices in Italy, identify the wild plants most frequently used as spices, analyze the distribution of wild herbs and spices used at a national scale, and finally, to describe the most common phytochemical compounds present in wild plant species. Based on the 34 studies reviewed, I documented 78 wild taxa as being used in Italy as herbs or spices. The studies I included in this systematic review demonstrate that wild species used as herbs and spices enrich Italian folk cuisine and can represent an important resource for profitable, integrated local small-scale activities.The aim of our study was to determine how the ease of calving of cows may influence changes in lactose concentration and other milk components and whether these two factors correlate with each other. To achieve this, we compared data of calving ease scores and average percentage of in-line registered milk lactose and other milk components. A total of 4723 dairy cows from nine dairy farms were studied. The cows were from the second to the fourth lactation. All cows were classified according to the calving ease group 1 (score 1)-no problems; group 2 (score 2)-slight problems; group 3 (score 3)-needed assistance; group 4 (score 4)-considerable force or extreme difficulty. Based on the data from the milking robots, during complete lactation we recorded milk indicators milk yield MY (kg/day), milk fat (MF), milk protein (MP), lactose (ML), milk fat/lactose ratio (MF/ML), milk protein/lactose ratio (MP/ML), milk urea (MU), and milk electrical conductivity (EC) of all quarters of the udder. According to the results, we found that cows that had no calving difficulties, also had higher milk lactose concentration. ML > 4.7% was found in 58.8% of cows without calving problems. Cows with more severe calving problems had higher risk of mastitis (SCC and EC). Our data indicates that more productive cows have more calving problems compared to less productive ones.This paper presents the results of the investigations of the properties of saddle-shaped copper alloy chips briquettes produced in a roller press. The physical and mechanical properties of the investigated briquettes were examined on their external surfaces as well as on their cross-sections. The density, chemical composition, microstructure analysis obtained with a 3D and scanning microscope, surface roughness and hardness of the obtained briquettes were investigated. The research proved the differentiation of the physical and mechanical properties of briquettes depending on the investigated area of their surface. The analysis of changes in the porosity of briquettes on their cross-section showed zones of various densification levels. This research expands the knowledge of the processes taking place during the compaction and consolidation of granular materials in roller presses as well as the knowledge concerning designing the geometry of forming tools.In this article we present the study of electroencephalography (EEG) traits for emotion recognition process using a videogame as a stimuli tool, and considering two different kind of information related to emotions arousal-valence self-assesses answers from participants, and game events that represented positive and negative emotional experiences under the videogame context. We performed a statistical analysis using Spearman's correlation between the EEG traits and the emotional information. We found that EEG traits had strong correlation with arousal and valence scores; also, common EEG traits with strong correlations, belonged to the theta band of the central channels.  https://www.selleckchem.com/products/FK-506-(Tacrolimus).html  Then, we implemented a regression algorithm with feature selection to predict arousal and valence scores using EEG traits. We achieved better result for arousal regression, than for valence regression. EEG traits selected for arousal and valence regression belonged to time domain (standard deviation, complexity, mobility, kurtosis, skewness), and frequency domain (power spectral density-PDS, and differential entropy-DE from theta, alpha, beta, gamma, and all EEG frequency spectrum).