Kinetics of fat and protein secretion in dairy cattle, sheep, goats and buffaloes

The negative correlations of fat and protein concentrations and milk yield, existing in all ruminants dairy species (Oftedal, 1984; Mepham, 1987), reflect a deep mechanism regulating the respective kinetics of secretion of carrier (mainly lactose which is the major responsible for the water drawn to the milk) and of fat and protein. Whereas the correlation coefficients are low (from –0.2 to – 0.4), fat and protein daily yield and milk production are positively and strongly linked (r = 0.8÷0.9). It means that more productive animals have higher fat and protein yield, but their milk has lower concentration of these components. The aim of this work is to investigate the relationships between milk, fat and protein yield in all main ruminant dairy species by using a simple mathematical model

Admissions for personality disorders in Italy from 1988 to 1998

BACKGROUND: Personality disorders affect a substantial proportion of the population. It is unclear, however, whether the burden of personality disorders on modern mental health services has been increasing. To fill this gap, we analyzed trends in admissions for personality disorders in Italy from 1988 to 1998. METHODS: We used the yearly data from the Italian Central Institute of Statistics to analyse trends in the total number of admissions for personality disorders and in the total number of first admissions for personality disorders. RESULTS: The absolute number of admissions for personality disorders almost trebled from 1988 to 1998, as well as the proportion of all psychiatric admissions that were for personality disorders. Whilst there has been a marked increase in the absolute number of first admissions, the proportion of all first psychiatric admissions that were for personality disorders showed a steady but modest increase, from 5.7% to 7.6%. CONCLUSION: In Italy, the burden of personality disorders on modern mental health services has been increasing. In terms of public health, these findings highlight the urgent need of developing policies to tackle the increasing demand of care of this difficult-to-treat patient population

Efficient model-free Q-factor approximation in value space via log-sum-exp neural networks

We propose an efficient technique for performing data-driven optimal control of discrete-time systems. In particular, we show that log-sum-exp ($lse$) neural networks, which are smooth and convex universal approximators of convex functions, can be efficiently used to approximate Q-factors arising from finite-horizon optimal control problems with continuous state space. The key advantage of these networks over classical approximation techniques is that they are convex and hence readily amenable to efficient optimization

A Variation on a Random Coordinate Minimization Method for Constrained Polynomial Optimization

In this paper, an algorithm is proposed for solving constrained and unconstrained polynomial minimization problems. The algorithm is a variation on random coordinate descent, in which transverse steps are seldom taken. Differently from other methods available in the literature, the proposed technique is guaranteed to converge in probability to the global solution of the minimization problem, even when the objective polynomial is nonconvex. The theoretical results are corroborated by a complexity analysis and by numerical tests that validate its efficiency

Valutazione multicriteriale dello spazio pubblico: un metodo per le pubbliche amministrazioni

La gestione, manutenzione e riqualificazione degli spazi pubblici richiede strumenti di valutazione multicriteriali, sensibili a condizioni socio-ambientali spesso trascurate nel processo decisionale di una Pubblica Amministrazione. La ricerca ha elaborato un sistema di valutazione transcalare composto di otto indicatori. Gli indicatori concorrono, attraverso la visualizzazione su base GIS e la computazione tabellare a definire un percorso progressivo di valutazione che partendo dalla scala della città giunge all'analisi di uno spazio verde e della sua dotazione di arredi. Il metodo sperimentale tiene conto del ciclo di vita delle dotazioni degli spazi pubblici, dei vincoli normativi, delle opportunità morfologiche del territorio, del fabbisogno sociale di spazi

Anisakiasis in italy: analysis of hospital discharge records in the years 2005-2015

Background Anisakiasis is a fish-borne zoonosis caused by the ingestion of marine food infected with Anisakis third-stage larvae, widespread marine parasitic nematodes. Gastrointestinal and/ or allergic clinical signs and symptoms are not specific. While frequently reported in countries with large raw fish consumption as Japan, the global prevalence of anisakiasis may be severely underestimated due to limitations of available diagnostic tools and to diverse clinical manifestations. Recently, infective larvae were found in the same localization with gastrointestinal tumors. The occurrence of allergic exacerbation upon secondary exposure and the possible occupational exposure, highlight the need to increase scientific evidences on anisakiasis. Methods We performed a retrospective descriptive study using analysis of Hospital Discharge Records (HDRs) from 2005 to 2015 in Italy, with particular attention to allergic manifestations. Descriptive statistics and multivariate analyses were performed using backward step-wise logistic regression models to assess spatial distribution and temporal trend as well as the variables independently associated with the allergic clinical signs and symptoms in Italian cases of anisakiasis. Results HDRs reporting the ICD-9 code for anisakiasis were retrieved (370), with a higher number of cases reported from central and southern regions, with particular regard to populations inhabiting the coastal territories. Around 40% of patients presented allergic manifestations and half of them showed serious allergic reactions. The multivariate analyses showed an independent association between allergic manifestations and features as living in southern regions and female gender, while anaphylactic episodes was independently associated only with female gender. Conclusion The present study is the first attempt to a better understanding of the epidemiological picture of anisakiasis in Italy, mining official data. A common strategy on data collection, monitoring and reporting would favor a more accurate epidemiological scenario in Italy, since the report of the diseases is not mandatory

Towards fabrication of ordered gallium nanostructures by laser manipulation of neutral atoms: study of self-assembling phenomena

Surface diffusion has an impact on the lateral resolution of nanostructures in bottom-up atom nanofabrication. In this paper we study the effects of the gallium atoms self-assembled on silicon surfaces (100) patterned with trenches at different slopes. These particular substrate morphologies have been made to enable an effective deposition rate variation along the surface. In this way we experimentally mimic the effect of the atomic flux modulation created by standing wave during an atom nanofabrication experiment. Even if we observe self organization of gallium atoms on the surface, we conclude that the nano-islands are not affected by surface diffusion processes and the effective variation of the deposition rate per unit area is the dominant factor affecting the growth differences along the surface. This result demonstrates that the gallium atoms self-organization should not prevent the observation of a periodic nano-patterning created by atom nano-fabrication techniques.Comment: 7 pages, 5 figures, EMRS conference procee

The Mathematical description of lactation curves in dairy cattle

This review gives an overview of the mathematical modelling of lactation curves in dairy cattle. Over the last ninety years, the development of this field of study has followed the main requirements of the dairy cattle industry. Non-linear parametric functions have represented the preferred tools for modelling average curves of homogeneous groups of animals, with the main aim of predicting yields for management purposes. The increased availability of records per individual lactations and the genetic evaluation based on test day records has shifted the interest of modellers towards more flexible and general linear functions, as polynomials or splines. Thus the main interest of modelling is no longer the reconstruction of the general pattern of the phenomenon but the fitting of individual deviations from an average curve. Other specific approaches based on the modelling of the correlation structure of test day records within lactation, such as mixed linear models or principal component analysis, have been used to test the statistical significance of fixed effects in dairy experiments or to create new variables expressing main lactation curve traits. The adequacy of a model is not an absolute requisite, because it has to be assessed according to the specific purpose it is used for. Occurrence of extended lactations and of new productive and functional traits to be described and the increase of records coming from automatic milking systems likely will represent some of the future challenges for the mathematical modelling of the lactation curve in dairy cattle

Utilization of big data to improve management of the emergency departments. Results of a systematic review

Background. The emphasis on using big data is growing exponentially in several sectors including biomedicine, life sciences and scientific research, mainly due to advances in information technologies and data analysis techniques. Actually, medical sciences can rely on a large amount of biomedical information and Big Data can aggregate information around multiple scales, from the DNA to the ecosystems. Given these premises, we wondered if big data could be useful to analyze complex systems such as the Emergency Departments (EDs) to improve their management and eventually patient outcomes. Methods. We performed a systematic review of the literature to identify the studies that implemented the application of big data in EDs and to describe what have already been done and what are the expectations, issues and challenges in this field. Results. Globally, eight studies met our inclusion criteria concerning three main activities: the management of ED visits, the ED process and activities and, finally, the prediction of the outcome of ED patients. Although the results of the studies show good perspectives regarding the use of big data in the management of emergency departments, there are still some issues that make their use still difficult. Most of the predictive models and algorithms have been applied only in retrospective studies, not considering the challenge and the costs of a real-time use of big data. Only few studies highlight the possible usefulness of the large volume of clinical data stored into electronic health records to generate evidence in real time. Conclusion. The proper use of big data in this field still requires a better management information flow to allow real-time application