Efeito de subdoses de 2,4-D na produtividade de uva itália e suscetibilidade da cultura em função de seu estádio de desenvolvimento

Durante os anos agrícolas de 2002-2003 e 2003-2004 foram conduzidos trabalhos no município de Maringá - PR, com o objetivo de avaliar o dano potencial de subdoses de 2,4-D sobre plantas de uva, imitando depósitos decorrentes de deriva. No primeiro experimento, a aplicação foi realizada cerca de 30 dias após a poda de inverno, num pomar de uva Itália. As doses utilizadas foram de 6,72; 13,44; 26,88; 53,76 e 107,52 g de equivalente ácido (e.a.) por hectare de 2,4-D, equivalentes a depósitos de 1,0%; 2,0%; 4,0%; 8,0% e 16,0%, assumindo-se uma aplicação de 1 L ha-1 (670 g e.a. ha-1). Nessa data, as plantas encontravam-se na fase de emissão de cachos e florescimento (estádio 15). O surgimento de sintomas visuais de fitointoxicação foi imediato e proporcional às doses aplicadas. A produtividade da cultura foi afetada por todas as doses aplicadas nesse estádio de crescimento. No entanto, mesmo com as injúrias severas registradas na dose mais alta, as plantas afetadas se recuperaram após duas podas para as condições de manejo regionais (duas safras por ano). No segundo experimento, foram aplicadas doses equivalentes a derivas de 1,0 e 2,0% (6,72 e 13,44 g e.a. ha-1) em três estádios do ciclo de desenvolvimento. A aplicação de doses < 13,44 g e.a. ha-1 (2,0% de deriva simulada) a partir do estádio de "meia-baga", não causou repercussões negativas em termos de injúrias visuais e produtividade.

Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Using data mining to identify factors that influence the degree of leg injuries in broilers

Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.

The use of ALOS/PALSAR data for estimating sugarcane productivity

Some models have been developed using agrometeorological and remote sensing data to estimate agriculture production. However, it is expected that the use of SAR images can improve their performance. The main objective of this study was to estimate the sugarcane production using a multiple linear regression model which considers agronomic data and ALOS/PALSAR images obtained from 2007/08, 2008/09 and 2009/10 cropping seasons. The performance of models was evaluated by coefficient of determination, t-test, Willmott agreement index (d), random error and standard error. The model was able to explain 79%, 12% and 74% of the variation in the observed productions of the 2007/08, 2008/09 and 2009/10 cropping seasons, respectively. Performance of the model for the 2008/09 cropping season was poor because of the occurrence of a long period of drought in that season. When the three seasons were considered all together, the model explained 66% of the variation. Results showed that SAR-based yield prediction models can contribute and assist sugar mill technicians to improve such estimates.

Use of preclinical and early clinical data for dose selection of a selective estrogen receptor modulator toremifene in treatment of breast cancer

In development of human medicines, it is important to predict early and accurately enough the disease and patient population to be treated as well as the effective and safe dose range of the studied medicine. This is pursued by using preclinical research models, clinical pharmacology and early clinical studies with small sample sizes. When successful, this enables effective development of medicines and reduces unnecessary exposure of healthy subjects and patients to ineffectice or harmfull doses of experimental compounds. Toremifene is a selective estrogen receptor modulator (SERM) used for treatment of breast cancer. Its development was initiated in 1980s when selection of treatment indications and doses were based on research in cell and animal models and on noncomparative clinical studies including small number of patients. Since the early development phase, the treatment indication, the patient population and the dose range were confirmed in large comparative clinical studies in patients. Based on the currently available large and long term clinical study data the aim of this study was to investigate how the early phase studies were able to predict the treatment indication, patient population and the dose range of the SERM. As a conclusion and based on the estrogen receptor mediated mechanism of action early studies were able to predict the treatment indication, target patient population and a dose range to be studied in confirmatory clinical studies. However, comparative clinical studies are needed to optimize dose selection of the SERM in treatment of breast cancer.

Building object-oriented software with the D-Bus messaging system

Object-oriented programming is a widely adopted paradigm for desktop software development. This paradigm partitions software into separate entities, objects, which consist of data and related procedures used to modify and inspect it. The paradigm has evolved during the last few decades to emphasize decoupling between object implementations, via means such as explicit interface inheritance and event-based implicit invocation. Inter-process communication (IPC) technologies allow applications to interact with each other. This enables making software distributed across multiple processes, resulting in a modular architecture with benefits in resource sharing, robustness, code reuse and security. The support for object-oriented programming concepts varies between IPC systems. This thesis is focused on the D-Bus system, which has recently gained a lot of users, but is still scantily researched. D-Bus has support for asynchronous remote procedure calls with return values and a content-based publish/subscribe event delivery mechanism. In this thesis, several patterns for method invocation in D-Bus and similar systems are compared. The patterns that simulate synchronous local calls are shown to be dangerous. Later, we present a state-caching proxy construct, which avoids the complexity of properly asynchronous calls for object inspection. The proxy and certain supplementary constructs are presented conceptually as generic object-oriented design patterns. The e ect of these patterns on non-functional qualities of software, such as complexity, performance and power consumption, is reasoned about based on the properties of the D-Bus system. The use of the patterns reduces complexity, but maintains the other qualities at a good level. Finally, we present currently existing means of specifying D-Bus object interfaces for the purposes of code and documentation generation. The interface description language used by the Telepathy modular IM/VoIP framework is found to be an useful extension of the basic D-Bus introspection format.

Strategic outsourcing of R&D: The location-specific advantages of India to the pharmaceutical industry

Companies are increasingly under pressure to be more efficient both in terms of costs and overall performance and thus, they seek new ways to develop their products and innovate. For pharmaceutical industry it can take several decades to launch a new drug to the markets. Since pharmaceutical industry is one of the most research-intensive industries, is outsourcing one way to enhance the R&D processes of such companies. It is said that outsourcing to offshore locations is vastly more challenging and complicated than any other exporting activity or inter-company relationship that has evoked a lot of discussion. By outsourcing strategically, companies must also thoroughly focus on transaction costs and core competences. Today, the suppliers are looked for beyond national boundaries and furthermore, the location of the outsourcing activity must also be thoroughly considered. Consequently, the purpose of this study is to analyze what is known of strategic outsourcing of pharmaceutical R&D to India. In order to meet the purpose of the study, this study tries to answer three sub-questions set to it: first, what is strategic outsourcing, second, why pharmaceutical companies utilize strategic outsourcing of R&D and last, why pharmaceutical companies select India as the location for outsourcing their R&D. The study is a qualitative study. The purpose of the study was approached by a literature review with systematic elements and sub-questions were analyzed through different relevant theories, such as theory of transaction costs, core competences and location advantages. Applicable academic journal articles were comprehensively included in the study. The data was collected from electronic journal article databases using key words and almost only peer-reviewed, as new as possible articles were included. Also both the reference list of the included articles and article recommendations from professionals generated more articles for inclusion. The data was analyzed through thematization that resulted in themes that illuminate the purpose of the study and sub-questions. As an outcome of the analysis, each of the theory chapters in the study represents one sub-question. The literature used in this study revealed that strategic outsourcing of R&D is increasingly used in pharmaceutical industry and the major motives to practice it has to do with lowering costs, accessing skilled labor, resources and knowledge and enhancing their quality while speeding up the introduction of new drugs. Mainly for the above-mentioned motives India is frequently chosen as the target location for pharma outsourcers. Still, the literature is somewhat incomplete in this complex phenomenon and more research is needed.