Pythagorean Approximations for LEGO: Merging Educational Robot Construction with Programming and Data Analysis

Abstract. This paper can be used in two ways. It can provide reference information for incorporating diagonal elements (for bracing or gear meshing) in educational robots built from standard LEGO kits. Alternatively, it can be used as the basis for an assignment for high school or college students to recreate this information; in the process, students will exercise skills in both computer programming and data analysis. Using the paper in the second way can be an excellent integrative experience to add to an existing course; for example, the Exploring Computer Science high school curriculum concludes with the units “Introduction to Programming”, “Computing and Data Analysis”, and “Robotics”

Housing problems in a changing society. Regulation and training needs in Italy

The paper focuses on the social, economic and environmental trends of recent years in Italy, highlighting the issue of housing emergency, both in quantitative and qualitative terms. What emerges are several shortages in housing especially in the suburbs of large cities, emphasizing the relevance of this issue in terms of health consequences and its priority for the definition of local policies. The authors underline that the availability of accessible and healthy housing is a human right, and a multisectoral responsibility, achievable only if a contribution is made by all relevant sectors including housing, environmental, social welfare, urban planning, building management and public health. The authors conclude by stressing the strategic role of training and illustrating a proposal addressed to all stakeholders, aiming to provide health evidences in terms of impact of housing hazards on health and to describe good building practices, helpful in order to obtain safe and healthy homes

Relationship between milk urea, blood plasma urea and body condition score in primiparous browsing goats with different milk yield level

Abstract. The aim of this study was to investigate the relationships among milk urea, blood plasma urea, milk yield and body condition score (BCS) in primiparous goats fed at pasture. Ninety goats of Sarda breed were used and, on the basis of their yield level, divided in three groups of 30 animals each, low (LY), intermediate (IY) and high milk yield (HY). Daily milk yield, milk protein content, milk urea, plasma total protein and albumin, plasma urea and BCS were measured at monthly intervals from 45 days in milking (45 DIM) to 165 DIM. Milk yield level affected protein concentration of milk and plasma, whereas albumin showed no variation. Plasma and milk urea showed a high correlation (P<0.001) despite of the yield level; plasma urea was always lower than milk urea. BCS decreased on 75 DIM and again after 135 DIM, and it was not affected by the milk yield level. Because milk urea and plasma urea were closely correlated and not influenced by the yield level, the study pointed out that measurement of milk urea could be utilized to evaluate urea metabolism also for browsing goats

The Use of cork in antiquity: some archaeological data in Sardinia

In this paper, we report some archaeological data from Sardinian contexts useful to summarize the use of the cork and the cork oak in antiquity. This use has its roots in the prehistory of Sardinia Island. Many archaeological researches document that it was already used during the Nuragic period (Bronze Age). The cork was extracted and processed in order to obtain plates, foils, planks, shavings and it was shaped to create various artefacts, such as footwear, containers, boxes, cases, stoppers, etc. Cork wedges were also used in nuragic dry stonewalls as thermal insulating

Prediction accuracies of cheese-making traits using Fourier-transform infrared spectra in goat milk

The objectives of this study were to explore the use of Fourier-transform infrared (FITR) spectroscopy on 458 goat milk samples for predicting cheese-making traits, and to test the effect of the farm variability on their prediction accuracy. Calibration equations were developed using a Bayesian approach with three different scenarios: i) a random cross-validation (CV) [80% calibration (CAL); 20% validation (VAL) set], ii) a stratified CV [(SCV), 13 farms used as CAL, and the remaining one as VAL set], and iii) a SCV where 20% of the goats randomly selected from the VAL farm were included in the CAL set (SCV80). The best prediction performance was obtained for cheese yield solids, justifying for its practical application at population level. Overall results were similar to or outperformed those reported for bovine milk. Our results suggest considering specific procedures for calibration development to propose reliable tools applicable along the dairy goat chain

Predictive formulas for different measures of cheese yield using milk composition from individual goat samples

The objective of this study was to develop formulas based on milk composition of individual goat samples for predicting cheese yield (%CY) traits (fresh curd, milk solids, and water retained in the curd). The specific aims were to assess and quantify (1) the contribution of major milk components (fat, protein, and casein) and udder health indicators (lactose, somatic cell count, pH, and bacterial count) on %CY traits (fresh curd, milk solids, and water retained in the curd); (2) the cheese-making method; and (3) goat breed effects on prediction accuracy of the %CY formulas. The %CY traits were analyzed in duplicate from 600 goats, using an individual laboratory cheese-making procedure (9-MilCA method; 9 mL of milk per observation) for a total of 1,200 observations. Goats were reared in 36 herds and belonged to 6 breeds (Saanen, Murciano-Granadina, Camosciata delle Alpi, Maltese, Sarda, and Sarda Primitiva). Fresh %CY (%CYCURD), total solids (%CYSOLIDS), and water retained (%CYWATER) in the curd were used as response variables. Single and multiple linear regression models were tested via different combinations of standard milk components (fat, protein, casein) and indirect udder health indicators (UHI; lactose, somatic cell count, pH, and bacterial count). The 2 %CY observations within animal were averaged, and a cross-validation (CrV) scheme was adopted, in which 80% of observations were randomly assigned to the calibration (CAL) set and 20% to the validation (VAL) set. The procedure was repeated 10 times to account for sampling variability. Further, the model presenting the best prediction accuracy in CrV (i.e., comprehensive formula) was used in a secondary analysis to assess the accuracy of the %CY predictive formulas as part of the laboratory cheese-making procedure (within-animal validation, WAV), in which the first %CY observation within animal was assigned to CAL, and the second to the VAL set. Finally, a stratified CrV (SCrV) was adopted to assess the %CY traits prediction accuracy across goat breeds, again using the best model, in which 5 breeds were included in CAL and the remaining one in the VAL set. Fitting statistics of the formulas were assessed by coefficient of determination of validation (R2VAL) and the root mean square error of validation (RMSEVAL). In CrV, the formula with the best prediction accuracy for all %CY traits included fat, casein, and UHI (R2VAL = 0.65, 0.96, and 0.23 for %CYCURD, %CYSOLIDS, and %CYWATER, respectively). The WAV procedure showed R2VAL higher than those obtained in CrV, evidencing a low effect of the 9-MilCA method and, indirectly, its high repeatability. In the SCrV, large differences for %CYCURD and %CYWATER among breeds evidenced that the breed is a fundamental factor to consider in %CY predictive formulas. These results may be useful to monitor milk composition and quantify the influence of milk traits in the composite selection indices of specific breeds, and for the direct genetic improvement of cheese production

Towards an update of the Italian Ministerial Decree July 5th, 1975

In recent years, the Scientific Community and the Public Health world, in general, have devoted increasing interest to housing conditions, which are considered, to date, one of the main environmental and social determinants of the population's health. In particular, the Scientific Community has identified and studied various indoor well-being factors (e.g. lighting, temperature, ventilation, air quality, etc.). Some of these factors have been regulated by laws and regulations at various levels: the availability of clear and updated health requirements dictated by the regulations is fundamental to effectively protect public health, especially in confined environments. In the present work, we propose a revision of the Italian Ministerial Decree of July 5th, 1975 titled Modificazioni alle istruzioni ministeriali 20 giugno 1896 relativamente all'altezza minima ed ai requisiti igienico sanitari principali dei locali d'abitazione (Modifications to the ministerial instructions of June 20th, 1896 regarding the minimum height and the main hygienic-sanitary requirements of living spaces) in order to update the definition of the essential elements that qualify a space as habitable from the hygienic-sanitary point of view, taking into account the evidence gathered from the technical and scientific literature on the requirements and contents of the Building Codes of the major European countries