Weather Forecast Activity at MZS, Terra Nova Bay:Automated Antarctic ECMWF Data Processing and Distribution Management

The Weather Forecast at the Italian base in Antarctica “Mario Zucchelli Station”, is a service conducted by personnel from Aeronautica Militare Italiana (Italian Air Force) and is very important for operational activity during the summer expedition. It allows to manage the base activities in order to use resources in a very safe mode. Currently, weather forecasts, are based on the Global Model of European Centre for Medium Weather Forecast (ECMWF, Reading, UK) data, and on the AMPS forecasts provided by NCAR. Concerning ECMWF data, PNRA staff manages the system architecture from data acquisition directly from Centro Nazionale Meteorologia e Climatologia of Aeronautica Militare (CNMCA, Pratica di Mare, Italy), the italian meteorological service, to data processing and distribution. The final result is the GRADS maps production, utilized by base staff for forecasting activity. During the XXI Antartic expedition the system architecture was changed. It was migrated on Linux-Red Hat platform with the aid of open-source software and it was improved in order to: 1. to supply a more reliable system in term of data distribution and 2. to upgrade the product in the respect of the technical requirements suggested by the meteorological staff

Role and task recommendation and social tagging to enable social business process management

Traditional Business Process Management (BPM) poses a number of limitations for the management of ad-hoc processes, where the execution paths are not designed a priori and evolve during enactment. Social BPM, which predicates to integrate social software into the BPM lifecycle, has emerged as an answer to such limitations. This paper presents a framework for social BPM in which social tagging is used to capture process knowledge emerging during the enactment and design of the processes. Process knowledge concerns both the type of activities chosen to fulfil a certain goal and the skills and experience of users in executing specific tasks. Such knowledge is exploited by recommendation tools to support the design and enactment of future process instances. We first provide an overview of our framework, introducing the concepts of role and task recommendations, which are supported by social tagging. These mechanisms are then elaborated further by an example. Eventually, we discuss a prototype of our framework enabling collaborative process design and execution

Data-Oriented Declarative Language for Optimizing Business Processes

There is a signifi cant number of declarative languages to describe business processes. They tend to be used when business processes need to be fl exible and adaptable, being not possible to use an imperative description. Declarative languages in business process have been traditionally used to describe the order of activities, specifi cally the order allowed or prohibited. Unfortunately, none of them is worried about a declarative description of exchanged data between the activities and how they can infl uence the model. In this paper, we analyse the data description capacity of a variety of declarative languages in business processes. Using this analysis, we have detected the necessity to include data exchanged aspects in the declarative descriptions. In order to solve the gap, we propose a Data-Oriented Optimization Declarative LanguagE, called DOODLE, which includes the process requirements referred to data description, and the possibility to include an optimization function about the process output data

Seasonal variation in the incidence of preeclampsia and eclampsia in tropical climatic conditions

<p>Abstract</p> <p>Background</p> <p>Observational studies have demonstrated various correlations between hypertensive disorders of pregnancy and different weather parameters. We aim to study if a correlation exists between the incidence of eclampsia and pre-eclampsia and various weather parameters in the tropical coastal city of Mumbai which has the distinction of having relatively uniform meteorological variables all throughout the year, except for the monsoon season.</p> <p>Methods</p> <p>We retrospectively analysed data from a large maternity centre in Mumbai, India over a period of 36 months from March 1993 to February 1996, recording the incidence of preeclampsia and eclampsia. Meteorological data was acquired from the regional meteorological centre recording the monthly average temperature, humidity, barometric pressure and rainfall during the study period. Study period was then divided into two climate conditions: monsoon season (June to August) and dry season September to May. The incidence of preeclampsia and eclampsia and the meteorological differences between the two seasons were compared.</p> <p>Results</p> <p>Over a 36-month period, a total of 29562 deliveries were recorded, of which 1238 patients developed preeclampsia (4.18%) and 34 developed eclampsia (0.11%). The incidence of preeclampsia did not differ between the monsoon and the dry season (4.3% vs. 4.15%, p = 0.5). The incidence of eclampsia was significantly higher in the monsoon (0.2% vs. 0.08%, p = 0.01). The monsoon was significantly cooler (median maximum temperature 30.7°C vs. 32.3°C, p = 0.01), more humid (median relative humidity 85% vs. 70%, p = 0.0008), and received higher rainfall (median 504.9 mm vs. 0.3 mm, p = 0.0002) than the rest of the year. The median barometric pressure (1005 mb) during the monsoon season was significantly lower than the rest of the year (1012 mb, p < 0.0001).</p> <p>Conclusion</p> <p>In the tropical climate of Mumbai, the incidence of eclampsia is significantly higher in monsoon, when the weather is cooler and humid with a lower barometric pressure than the rest of the year. This effect is not seen with preeclampsia. This strengthens the association of low temperature and high humidity with triggering of eclampsia.</p

Moose and snowshoe hare competition and a mechanistic explanation from foraging theory

Moose ( Alces alces ) and snowshoe hare ( Lepus americanus ) appear to compete with each other. This was determined using the “natural experiments” of populations found in sympatry and allopatry on islands at Isle Royale National Park, Michigan, and manipulated exclosures. The population densities from these areas are fit to a series of competition models based upon different competitive mechanisms (Schoener 1974a), using non-linear regression techniques. A model of competition for food where the food can be separated into exclusively used and shared categories is found to predict observed densities of moose and hare best. Finally, the competition model's parameters (fraction of food shared and competition coefficients) are shown to agree with values predicted independently from a foraging model.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47750/1/442_2004_Article_BF00396753.pd

Ligand-induced endocytosis of the asialoglycoprotein receptor : evidence for heterogeneity in subunit oligomerization

The hepatic asialoglycoprotein receptor, a noncovalent hetero-oligomer of two subunits, is a constitutively cycling endocytic receptor. However, the ligand asialoorosomucoid caused downregulation of up to 40% of surface binding sites and a twofold increase in internalization rate. This was not the result of receptor crosslinking, since monovalent ligands had the same effect. Ligand binding thus appears to transmit a signal to the cytosolic portion of the receptor not unlike in signaling receptors. The two subunits were endocytosed at different average rates lower than that of ligand, indicating heterogeneity in oligomer formation and potentially in ligand specificity