The decline of malaria in Finland – the impact of the vector and social variables

Background: Malaria was prevalent in Finland in the 18th century. It declined slowly without deliberate counter-measures and the last indigenous case was reported in 1954. In the present analysis of indigenous malaria in Finland, an effort was made to construct a data set on annual malaria cases of maximum temporal length to be able to evaluate the significance of different factors assumed to affect malaria trends. Methods: To analyse the long-term trend malaria statistics were collected from 1750–2008. During that time, malaria frequency decreased from about 20,000 – 50,000 per 1,000,000 people to less than 1 per 1,000,000 people. To assess the cause of the decline, a correlation analysis was performed between malaria frequency per million people and temperature data, animal husbandry, consolidation of land by redistribution and household size. Results: Anopheles messeae and Anopheles beklemishevi exist only as larvae in June and most of July. The females seek an overwintering place in August. Those that overwinter together with humans may act as vectors. They have to stay in their overwintering place from September to May because of the cold climate. The temperatures between June and July determine the number of malaria cases during the following transmission season. This did not, however, have an impact on the longterm trend of malaria. The change in animal husbandry and reclamation of wetlands may also be excluded as a possible cause for the decline of malaria. The long-term social changes, such as land consolidation and decreasing household size, showed a strong correlation with the decline of Plasmodium. Conclusion: The indigenous malaria in Finland faded out evenly in the whole country during 200 years with limited or no counter-measures or medication. It appears that malaria in Finland was basically a social disease and that malaria trends were strongly linked to changes in human behaviour. Decreasing household size caused fewer interactions between families and accordingly decreasing recolonization possibilities for Plasmodium. The permanent drop of the household size was the precondition for a permanent eradication of malaria.

Patent Price Dynamics in the Context of Patent Age and Patent Latent Variables

The decision to patent a technology is a difficult one to make for the top management of any organization. The expected value that the patent might deliver in the market is an important factor that impacts this judgement. Earlier researchers have suggested that patent prices are better indicators of value of a patent and that auction prices are the best way of determining value. However, the lack of public data on pricing has prevented research on understanding the dynamics of patent pricing. Our paper uses singleton patent auction price data of Ocean Tomo LLC to study the prices of patents. We describe price characteristics of these patents. The price of these patents was correlated with their age, and a significant correlation was found. A price - age matrix was developed and we describe the price characteristics of patents using four quadrants of the matrix, namely young and old patents with low and high prices. We also found that patents owned by small firms get transacted more often and inventor owned patents attracted a better price than assignee owned patents.

Abrasive Jet Machining - Process variables and current applications

brusive Jet Machining (AJM) or Micro Blast Machining is a non-traditional machining process, wherein material removal is effected by the erosive action of a high velocity jet of a gas, carrying fine-grained abrasive particles, impacting the work surface. The AJM process differs from conventional sand blasting in that the abrasive is much finer and the process parameters and cutting action are carefully controlled. The process is particularly suitable to cut intricate shapes in hard and brittle materials which are sensitive to heat and have a tendency to chip easily. In other words, AJM can handle virtually any hard or brittle material. Already the process has found its ways Into dozens of applications; sometimes replacing conventional alternatives often doing jobs that could not be done in any other way. This paper reviews the current status of this non-conventional machining process and discusses the unique advantages and possible applications.

SiO Maser Emission and the Intrinsic Properties of Mira Variables

This paper presents observations of SiO maser emission from 161 Mira variables distributed over a wide range of intrinsic parameters like spectral type, bolometric magnitude and amplitude of pulsation. The observations were made at 86.243 GHz, using the 10.4 m millimeter-wave telescope of the Raman Research Institute at Bangalore, India. These are the first observations made using this telescope. From these observations, we have established that the maser emission is restricted to Miras having mean spectral types between M6 and M10. The infrared period-luminosity relation for Mira variables is used to calculate their distances and hence estimate their maser luminosities from the observed fluxes. The maser luminosity is found to be correlated with the bolometric magnitude of the Mira variable. On an H-R diagram, the masing Mira variables are shown to lie in a region distinct from that for the non-masing ones.

Role of Management Decision Variables in Determining Technology Progress and Technical Efficiency in Indian Electronic Industry

This paper analyses the influence of management on Technical Efficiency Change (TEC) and Technological Progress (TP) in the communication equipment and consumer electronics sub-sectors of Indian hardware electronics industry. Each sub-sector comprises 13 sample firms for two time periods.The primary objective is to determine the relative contribution of TP and TEC to TFP Growth (TFPG) and to establish the influence of firm specific operational management decision variables on these two components. The study finds that both the sub-sectors have strived and achieved steady TP but not TEC in the period of economic liberalisation to cope with the intensifying competition. The management decisions with respect to asset and profit utilization, vertical integration, among others, improved TP and TE in the sub-sectors. However, R&D investments and technology imports proved costly for TFP indicating inadequate efforts and/or poor resource utilisation by the management. Management was found to be complacent in terms of improving or developing their own technology as indicated by their higher dependence on import of raw materials and no influence of R&D on TP.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Dynamics between patent latent variables and patent price

This paper focuses on studying the relationship between patent latent variables and patent price. From the existing literature, seven patent latent variables, namely age, generality, originality, foreign filings, technology field, forward citations, and backward citations were identified as having an influence on patent value. We used Ocean Tomo's patent auction price data in this study. We transformed the price and the predictor variables (excluding the dummy variables) to its logarithmic value. The OLS estimates revealed that forward citations and foreign filings were positively correlated to price. Both the variables jointly explained 14.79% of the variance in patent pricing. We did not find sufficient evidence to come up with any definite conclusions on the relationship between price and the variables such as age, technology field, generality, backward citations and originality. The Heckman two-stage sample selection model was used to test for selection bias. (C) 2011 Elsevier Ltd. All rights reserved.

Reservoir Operation with Fuzzy State Variables for Irrigation of Multiple Crops

This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.

Cybernetic Modeling Revisited: A Method for Inferring the Cybernetic Variables u(i) from Experimental Data

The cybernetic modeling framework for the growth of microorganisms provides for an elegant methodology to account for the unknown regulatory phenomena through the use of cybernetic variables for enzyme induction and activity. In this paper, we revisit the assumption of limited resources for enzyme induction (Sigma u(i) = 1) used in the cybernetic modeling framework by presenting a methodology for inferring the individual cybernetic variables u(i) from experimental data. We use this methodology to infer u(i) during the simultaneous consumption of glycerol and lactose by Escherichia coli and then model the fitness trade-offs involved in the recently discovered predictive regulation strategy of microorganisms.

A Viscoelastic Constitutive Model with Nonlinear Evolutionary Internal Variables

Based on the internal variable theory, a viscoelastic constitutive model of a highly deformable continuous medium is proposed. A set of second rank tensorial internal state variables corresponding to Biot's strain is introduced, and a nonlinear evolution

Diagnostico de prevalencia a leptospirosis canina con respecto a las variables edad, sexo y raza, en ocho barrios del distrito 2 de la ciudad de Managua Septiembre 2007 - Enero 2008

La leptospirosis es considerada una de las zoonosis más difundidas en el mundo entero. El perro actúa como un potencial diseminador de esta enfermedad ya que mantiene una estrecha relación con el hombre, y al mismo tiempo con otros animales tanto domésticos como salvajes. Con el objetivo de conocer la presencia de leptospirosis canina, se realizó estudio en ocho barrios del distrito dos de la cuidad de Managua entre 8 de septiembre al 9 de diciembre 2007. Se realizó un muestreo de 76 canes, correspondiente al 5% del total de canes en los ocho barrios. Se extrajo 3ml de sangre de la vena safena externa, luego de procesarlas para separar el suero sanguíneo del plasma mediante centrifugación, fueron trasladadas al laboratorio del Centro Veterinario de Diagnóstico e Investigación CEVEDI, UNAN-León, para su análisis mediante los métodos ELISA y MAT. De acuerdo con los resultados obtenidos mediante la prueba ELISA un 93.4%, 71 canes, son negativos y un 6.6%, o bien 5 especímenes, son seropositivos a Leptospira spp. Según los resultados de la prueba de micro aglutinación MAT, el 96.1% de la población muestreada es negativa y el 3.9% es positiva a leptospirosis encontrándose los siguientes serovares canico/a, icterohemorragiae, pyrogenes.

Comportamiento de variables de crecimiento y rendimiento en maiz (Zea mays L.) var. NB-6 bajo practicas de fertilizacion, organica y convencional en la Finca El Plantel 2007-2008

El presente trabajo de investigación se estableció entre los meses de Noviembre 2007-Marzo 2008, bajo sistema de riego en la estación experimental El Plantel propiedad de la Universidad Nacional Agraria (UNA), ubicada en el km 42 ½ de la carretera Tipitapa–Masaya, municipio de Tisma en las coordenadas 12 o 07’ 3.84’’ latitud norte y 86 o 05’ 26.085’’ longitud oeste a una altura de 200 msnm. Con el objetivo de comparar el crecimiento y rendimiento del cultivo maíz, variedad NB-6, se establecierondos tratamientos, con prácticas de manejo convencional y orgánico, el tamaño de la parcela experimental fué de 432m2 (16 m x 27 m) y el tamaño de cada parcela útil fue de 46.8 m2 (6 m x 7.8 m), en ambos manejos. Las variables evaluadas fueron; altura de planta, diámetro de tallo, número de hojas, área foliar, longitud de mazorca, diámetro de mazorca, número de hileras por mazorca, número de granos por hileras, número de granos por mazorca, peso de mil granos y rendimiento. Los datos fueron analizados con el programa estadístico SAS versión 9.1, año 2006; realizando comparaciones de medias para cada variable en las dos prácticas de manejo. Los resultados muestran que no hubo diferencia significativa para las variables de crecimiento, tomadas en momentos diferentes. Se encontró diferencia significativa para las variables de rendimiento; longitud de la mazorca y diámetro de la mazorca. El manejo orgánico obtuvo los mayores rendimientos con un total de 3869.78kgha-1, seguido del manejo convencional con 3060.29 kgha-1.

Identificación de variables en modelización de líneas de producción industrial y su análisis mediante redes neuronales artificiales

Resumen: En el marco de la integración de etapas en procesos de producción industrial en serie, se identifican, clasifican y caracterizan las variables que permiten modelizar dicho proceso, como estrategia con vistas a su optimización. El estudio se aplica en el ámbito de la industria metalúrgica, a partir de los datos de un conjunto de empresas de la región centro y sur de Santa Fe. La estructura secuencial de un proceso industrial hace que cualquier falla en una etapa cause demoras o reducción de calidad en el producto final obtenido. Como herramienta integradora de análisis, se plantea la implementación de un sistema de redes neuronales artificiales.