Artrópodos associados à copa de Attalea phalerata Mart. (Arecaceae), na região do Pantanal de Poconé, Mato Grosso, Brasil

Six individuals of the palm A. phalerata, in Poconé floodplains of Mato Grosso, were sprayed with a synthetic pyrethroid (0.25% concentration) in order to study the biomass, diversity, and richness of the canopy arthropods. A total of 17,188 (238.7±80.6 ind./m²) arthropods belonging to 22 Orders, was collected in a 72 m² funnel area. Two hours after spraying, 58.9% of the total number fell into the funnels, 37.6% was obtained by shaking the trees, and finally, 3.5% after cutting and washing all the palm leaves. The Coleoptera (27.4%), Hymenoptera-Formicidae (19.0%), Collembola (13.6%), Psocoptera (10.7%), Diptera (9.0%) and Araneae (6.4%) were the predominant. The total biomass was 15.1 g dry weight (0.4mg/m²; 0.13+0.04/tree). A total of 4,715 beetles representing 48 families and 326 morphospecies were obtained. Tenebrionidae (22.9%), Curculionidae (22.0%), Carabidae (10.9%) and Staphylinidae (7.9%) were the most abundant, while Curculionidae (44 spp.), Staphylinidae (40 spp.) and Chrysomelidae (34 spp.) presented the largest number of morphospecies. Herbivores (37.5%) were the dominant in the trophic guilds of adult Coleoptera, followed by predators (35.4%), fungivores (14.6%), and saprophages (12.5%). Although most arthropod Orders were represented in all the palms sampled, analysis of variance showed no significant differences in their composition, however there was a significant difference in their frequency of occurrence.

Executive Order Number Four, October 26, 2007

Orders that State Agencies achieve and maintain a diverse workforce in state government.

Implicit collusion on wide spreads

Recent empirical findings suggest that spreads quoted in dealershipmarkets might be uncompetitive. This paper analyzes theoretically if pricecompetition between risk--averse market--makers leaves room for implicitcollusive behavior. We compare the spread and risk--sharing efficiencyarising in several market structures differing in terms of i) the priorityrule followed in case of ties, and ii) the type of schedules market makersmay use, namely: general schedules, linear schedules, or limit orders. Ingeneral, competitive pricing does not arise in equilibrium, and there isa conflict between risk sharing efficiency and the tightness of the spread.This conflict can be mitigated by an appropriate market structure design.The limit order market is the only market structure in which the competitiveequilibrium is the unique equilibrium.

A new order, a new family and a new genus of Paleozoic Radiolaria: Latentifistularia, Cauletellidae and Cauletella

Since the genus Deflandrella De Wever and Caridroit 1984 is a homonym of Deflandrella Loeblich and Tappan 1961, the new name Cauletella is :herein proposed, and the genus is redefined. Consequently, the family name Deflandrellidae De Wever and Caridroit, previously erected, becomes Cauletellidae, and its definiton is emended. This important radiolarian group, typical of the Permian times, is closely related to the families Ruzhencevispongidae Kozur 1980 and Latentifistulidae Nazarov and Ormiston 1983. These Paleozoic radiolarians are characterized by an initial skeleton quite different from that of the other radiolarian orders and are assigned to the new order Latentifistularia, which is herein defined and briefly discussed. ((C) 1999 Academie des sciences/ Editions scientifiques et medicales Elsevier SAS.).

Terrestrial arthropods from tree canopies in the Pantanal of Mato Grosso, Brazil

Terrestrial arthropods from tree canopies in the Pantanal of Mato Grosso, Brazil. This study represents a contribution to the knowledge of the diversity of arthropods associated to the canopy of Vochysia divergens Pohl (Vochysiaceae). Three trees individuals were sampled during two seasonal periods in this region: a) by spraying one tree canopy during high water (February); b) by fogging two tree canopies during low water (September/October). The 15,744 arthropods (183.2±38.9 individuals/m²) obtained from all three trees (86 m²) represented 20 taxonomic orders, 87.1% were Insecta, and 12.9% Arachnida. The dominant groups were Hymenoptera (48.5%; 88.9 individuals/m²), mostly Formicidae (44.5%; 81.4 individuals/m²), followed by Coleoptera (14.0%; 25.5 individuals/m²) and Araneae (10.2%; 19.5 individuals/m²), together representing 62.5% of the total catch. Fourteen (70%) of all orders occurred on three trees. Dermaptera, Isoptera, Neuroptera, Odonata, Plecoptera and Trichoptera were collected from only one tree. Of the total, 2,197 adult Coleoptera collected (25.5±11.3 individuals/m²), 99% were assigned to 32 families and 256 morphospecies. Nitidulidae (17.9% of the total catch; 4.6 individuals/m²), Anobiidae (16.7%; 4.3 individuals/m²), Curculionidae (13.2%; 3.4 individuals/m²) and Meloidae (11.4%; 2.9 individuals/m²) dominated. The communitiy of adult Coleoptera on V. divergens indicated a dominance of herbivores (37.8% of the total catch, 127 spp.) and predators (35.2%, 82 spp.), followed by saprophages (16.2%, 32 spp.) and fungivores (10.8%, 15 spp.). The influence of the flood pulse on the community of arboreal arthropods in V. divergens is indicated by the seasonal variation in evaluated groups, causing changes in their structure and composition.

A total order in [0,1] defined through a 'next' operator

A `next' operator, s, is built on the set R1=(0,1]-{ 1-1/e} defining a partial order that, with the help of the axiom of choice, can be extended to a total order in R1. Besides, the orbits {sn(a)}nare all dense in R1 and are constituted by elements of the samearithmetical character: if a is an algebraic irrational of degreek all the elements in a's orbit are algebraic of degree k; if a istranscendental, all are transcendental. Moreover, the asymptoticdistribution function of the sequence formed by the elements in anyof the half-orbits is a continuous, strictly increasing, singularfunction very similar to the well-known Minkowski's ?(×) function.

Management of major accidents with on-site 144 dispatcher

Introduction: An excellent coordination between firefighters, policemen and medical rescue is the key to success in the management of major accidents. In order to improve and assist the medical teams engaged on site, the Swiss "medical command and control system" for rescue operations is based on a binomial set up involving one head emergency doctor and one head rescue paramedic, both trained in disaster medicine. We have recently experimented an innovative on-site "medical command and control system", based on the binomial team, supported by a dedicated 144 dispatcher. Methods: A major road traffic accident took place on the highway between Lausanne and Vevey on April 9th 2008. We have retrospectively collected all data concerning the victims as well as the logistics and dedicated structures, reported by the 144, the Hospitals, the Authority of the State and the Police and Fire Departments. Results: The 72-car pileup caused one death and 26 slightly injured patients. The management on the accident site was organized around a tripartite system, gathering together the medical command and control team with the police and fire departments. On the medical side, 16 ambulances, 2 medical response teams (SMUR), the Rega crew and the medical command and control team were dispatched by the 144. On that occasion an advanced medical command car equipped with communication devices and staffed with a 144 dispatcher was also engaged, allowing efficient medical regulation directly from the site. Discussion: The specific skills of one doctor and one paramedic both trained for disaster's management proved to be perfectly complementary. The presence of a dispatcher on site with a medical command car also proved to be useful, improving orders transmission from the medical command team to all other on- and off-site partners. It relieved the need of repeated back-and-forth communication with the 144, allowing both paramedic and doctor to focus on strategy and tactics rather than communication and logistics.

Key to the adults of the most common forensic species of Diptera in South America

Flies (Diptera, blow flies, house flies, flesh flies, horse flies, cattle flies, deer flies, midges and mosquitoes) are among the four megadiverse insect orders. Several species quickly colonize human cadavers and are potentially useful in forensic studies. One of the major problems with carrion fly identification is the lack of taxonomists or available keys that can identify even the most common species sometimes resulting in erroneous identification. Here we present a key to the adults of 12 families of Diptera whose species are found on carrion, including human corpses. Also, a summary for the most common families of forensic importance in South America, along with a key to the most common species of Calliphoridae, Muscidae, and Fanniidae and to the genera of Sarcophagidae are provided. Drawings of the most important characters for identification are also included.

Iowa Leading Indicators Index Report, July 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, August 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, September 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, October 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, November 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, December 2006

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index Report, January 2007

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.