Technologies and logistics for phosphorus recovery from livestock waste

Phosphorus (P) runoff from livestock waste can trigger algal blooms that adversely affect aquatic life and human health. One strategy to mitigate this problem is to install nutrient recovery technologies that concentrate and mobilize nutrients from nutrient-rich regions to nutrient-deficient ones. We present supply chain design formulations to identify optimal types and locations for P recovery technologies. The formulations capture trade-offs in transportation costs, technology efficiency, investment/operational costs, revenue collected from different recovered products (struvite and nutrient cakes), and environmental impact. Our computational framework is used to analyze the impact of different scenarios for market prices of recovered products, recovery yields, and remediation costs. We find that transportation of waste alone (without any processing) can achieve significant reductions in environmental impact at low cost, but cannot achieve economic sustainability in the long run due to the lack of direct revenue streams. Mechanical separation technologies that recover P in the form of nutrient cakes are low-cost solutions that can achieve high environmental benefits and reduced transportation costs, but revenues are also limited due to low values of the cakes. Struvite crystallization in fluidized beds is found to be a highly attractive option under current struvite prices, but economic sustainability is strongly dependent on yield recoveries (which are currently highly uncertain).     

Effects of a startling acoustic stimulus on reaction time in different parkinsonian syndromes

BACKGROUND: The functional assessment of the startle circuit is usually done by analyzing the acoustic startle response (ASR). However, a startling acoustic stimulus (SAS) also induces changes in the excitability of neural structures that can be demonstrated by studying the SAS-induced change in the behavior of certain neurophysiologic responses. OBJECTIVE: To examine the effects induced by an SAS on voluntary reaction time in patients with parkinsonian syndromes (StartReact effect) and to compare the results with those obtained in a group of age-matched healthy volunteers. METHODS: Twelve patients with idiopathic PD (IPD), seven patients with progressive supranuclear palsy (PSP), seven patients with multisystem atrophy (MSA), and seven healthy age-matched control volunteers performed a simple visual reaction time task and received SAS together with the "go" signal in random trials. RESULTS: Baseline reaction time was significantly slower in PSP patients than in control subjects and MSA patients. The SAS induced a significant shortening of the reaction time in control subjects and in patients with IPD and MSA, but not in patients with PSP. The percentage of reaction time shortening with regard to the baseline values also differed significantly between PSP patients and the other groups of subjects. The StartReact effect was consistent throughout the experiment and showed reduced habituation with repeated testing. CONCLUSIONS: The results are consistent with an abnormal function of the startle circuit in patients with PSP and agree with previous studies using the ASR. The reduced habituation of the StartReact effect favors its clinical applicability in the assessment of differences between patients with parkinsonian syndromes.     

Design of product as source of variance in composition of meat-based infant beikosts

The influence of both the design of the product (formulated raw ingredients) and type of product (on the meat type formulated base) on the mineral composition, crude protein (CP), protein digestibility (PD), total dietary fiber (TDF) and phytic acid (FA) contents of meat-based infant beikosts was studied. The product design was the main factor determining the CP, TDF, Ca, Na and K contents, while the type of product was the main factor determining the PD, FA, Zn, Fe and Mn contents. High K and Mn levels were related to high TDF contents. CP and Zn showed a significant relationship but the CP Fe relationship was not significant.     

Diseases of the digestive system and a system for patient classification: diagnostic-related groups (DRG)

In the last years different classification systems for hospitalized patients have been developed in the United States, that allow to evaluate different aspects of any Hospital: The quality, the efficacy and the efficiency. The classification of "The Diagnosis Related Groups" (DRG) relates the hospitalized patients with the expenses that they generate, and it is the most used in Europe. In the version DRG-All Patient, all the diagnoses and procedures of the hospitalized patients, using the International Classification of Diseases, are divided in to 25 Major Diagnostic Categories (MDC) where each one excludes all the others. We describe the behavior with respect to the age, sex and stay of all the GDR integrated in the CDM 6 and 7: diseases and disorders of the digestive tract, and diseases and disorders of the hepatobiliary system and the pancreas. The study has been carried out with a national data base of two millions of cases seen from 214 acute-care Hospitals. The MDC number 6 is the most frequent, with an important number of patients in the pediatric age; it is more frequent in males; the average stay is 8.59 days and 19 GDR (36.5%) have a variation coefficient greater than one. The other MDC, number 7 is less frequent, the majority of the patients are between 60-80 years of age, the average stay is 12.2 days with a coefficient of variation greater than one in 4 GDR (17.4%). Clinical Services should know the characteristics and behavior of their patients, as well as the comparison with the national data bases. This may allow a control of the quality and the costs by using a common "language" with the managers.     

Automatic metro map layout using multicriteria optimization

This paper describes an automatic mechanism for drawing metro maps. We apply multicriteria optimization to find effective placement of stations with a good line layout and to label the map unambiguously. A number of metrics are defined, which are used in a weighted sum to find a fitness value for a layout of the map. A hill climbing optimizer is used to reduce the fitness value, and find improved map layouts. To avoid local minima, we apply clustering techniques to the map-the hill climber moves both stations and clusters when finding improved layouts. We show the method applied to a number of metro maps, and describe an empirical study that provides some quantitative evidence that automatically-drawn metro maps can help users to find routes more efficiently than either published maps or undistorted maps. Moreover, we have found that, in these cases, study subjects indicate a preference for automatically-drawn maps over the alternatives.     

Efficient estimation of a semiparametric dynamic copula model

A new semiparametric dynamic copula model is proposed where the marginals are specified as parametric GARCH-type processes, and the dependence parameter of the copula is allowed to change over time in a nonparametric way. A straightforward two-stage estimation method is given by local maximum likelihood for the dependence parameter, conditional on consistent first stage estimates of the marginals. First, the properties of the estimator are characterized in terms of bias and variance and the bandwidth selection problem is discussed. The proposed estimator attains the semiparametric efficiency bound and its superiority is demonstrated through simulations. Finally, the wide applicability of the model in financial time series is illustrated, and it is compared with traditional models based on conditional correlations.     

TRIMS,a privacy-aware trust and reputation model for identity management systems

Electronic transactions are becoming more important everyday. Several tasks like buying goods, booking flights or hotel rooms, or paying for streaming a movie, for instance, can be carried out through the Internet. Nevertheless, they are still some drawbacks due to security threats while performing such operations. Trust and reputation management rises as a novel way of solving some of those problems. In this paper we present our work TRIMS (a privacy-aware trust and reputation model for identity management systems), which applies a trust and reputation model to guarantee an acceptable level of security when deciding if a different domain might be considered reliable when receiving certain sensitive user’s attributes. Specifically, we will address the problems which surfaces when a domain needs to decide whether to exchange some information with another possibly unknown domain to effectively provide a service to one of its users. This decision will be determined by the trust deposited in the targeting domain. As far as we know, our proposal is one of the first approaches dealing with trust and reputation management in a multi-domain scenario. Finally, the performed experiments have demonstrated the robustness and accuracy of our model in a wide variety of scenarios.     

A new fast prototype selection method based on clustering

In supervised classification, a training set T is given to a classifier for classifying new prototypes. In practice, not all information in T is useful for classifiers, therefore, it is convenient to discard irrelevant prototypes from T. This process is known as prototype selection, which is an important task for classifiers since through this process the time for classification or training could be reduced. In this work, we propose a new fast prototype selection method for large datasets, based on clustering, which selects border prototypes and some interior prototypes. Experimental results showing the performance of our method and comparing accuracy and runtimes against other prototype selection methods are reported.