One reason, several logics

Humans have used arguments for defending or refuting statements long before the creation of logic as a specialized discipline. This can be interpreted as the fact that an intuitive notion of "logical consequence" or a psychic disposition to articulate reasoning according to this pattern is present in common sense, and logic simply aims at describing and codifying the features of this spontaneous capacity of human reason. It is well known, however, that several arguments easily accepted by common sense are actually "logical fallacies", and this indicates that logic is not just a descriptive, but also a prescriptive or normative enterprise, in which the notion of logical consequence is defined in a precise way and then certain rules are established in order to maintain the discourse in keeping with this notion. Yet in the justification of the correctness and adequacy of these rules commonsense reasoning must necessarily be used, and in such a way its foundational role is recognized. Moreover, it remains also true that several branches and forms of logic have been elaborated precisely in order to reflect the structural features of correct argument used in different fields of human reasoning and yet insufficiently mirrored by the most familiar logical formalisms.

Longitudinal distribution of bean seeds in horizontal plate meter operating with one or two seed outlets

This study aimed to evaluate the effect of horizontal plate meter with oblong holes operating with one or two seed outlets at different speeds over the accuracy of longitudinal distribution of common bean seeds (Phaseolus vulgaris L.). The experiment was performed in laboratory using the meter with one and two seed outlet points in relation to ten tangential disk plate speeds (0.03 to 0.30 m s-1). It was used a complete randomized design with four replications, summing up 80 experimental treatments. Tangential speed quantitative factor was estimated through a 2nd order polynomial regression. There was no significant difference in the behavior of the seed meter operating with one or two outlets in the metering of bean seeds in all tested speeds, with percentage of single seeds spacing over 60% in tangential speeds below of 0.24 m s-1.

Evaluation of left ventricular diastolic echocardiographic parameters in healthy dogs by pulsed-wave Doppler

Left ventricular diastolic dysfunction plays an important role on heart failure progression. In order to obtain additional reference values of left ventricular diastolic parameters and investigate influence of common variables, peak E wave (peak E), peak A wave (peak A), E/A ratio (E/A), E wave deceleration time (EDT) and isovolumic relaxation time (IRVT) were studied in 40 clinically healthy dogs, by pulsed wave Doppler. The following values were obtained: peak E = 0.747 ± 0.117 m/s, peak A = 0.487 ± 0.062 m/s, E/A = 1.533 ± 0.198, EDT = 88.7 ± 9.2 ms and IRVT = 0.080 ± 0.009 s. Some parameters were influenced by heart rate (peak E, peak A and IRVT), by age (peak A and E/A) and by body weight (TRIV). Gender influence was absent. Values obtained can be used as reference for canine specimens but its interpretation should consider on the influence of related variables.

Records of performance and sanitary status from a dairy cattle herd in southern Brazil

Over the last decades, the emphasis on the health of dairy cows has changed from an individual to a herd level. In this scenario, the role played by the recording system and its interpretation by veterinarians has gained primordial importance. The records of productive and reproductive performance and of sanitary status from a southern Brazilian dairy cattle herd have been presented and discussed. The period of study was 2000-2009. Mean values per lactation period were 349D 8436M 290F 275P 201SCS (D: days in lactation, M: kg of milk yield, F: kg of fat, P: kg of protein and SCS: somatic cell score in 1000 cells/ml of milk). Major indexes of reproductive efficiency included age at first calving (31 months), services per conception (2.1), intercalving interval (428 days), calving to conception interval (146 days), mean annual rates of parturitions (76.2%), fetal losses (9.8-19.0%), and stillbirths (3.6%), apart of voluntary waiting period (94 days). Main information on sanitary status of the herd was associated with the mean prevalence of common disorders of dairy cattle such as anaplasmosis (29.8%), mastitis (27.8%), digital diseases (26.3%), ovarian cysts (21.3%), placental retention (19.7%), postpartum uterine infections (10.6%), and calf diarrhea (23.7%) and pneumonia (16.8%), among others. In addition, culling reasons (low reproductive performance [56.3%] and udder/mastitis problems [33.6%]), causes of cattle deaths (anaplasmosis [16.4%] and leukosis [11.4]), and the impact of cattle diseases such as tuberculosis, leukosis, and neosporosis on the herd have also been presented and succinctly discussed. Numbers between brackets represent rates accumulated in the 10-year period.

PET Imaging of Osteomyelitis. Feasibility of 18F-FDG, 68Ga-Chloride and 68Ga-DOTAVAP-P1 Tracers in Staphylococcal Bone Infections

Due to technical restrictions of the database system the title of the thesis does not show corretly on this page. Numbers in the title are in superscript. Please see the PDF-file for correct title. ---- Osteomyelitis is a progressive inflammatory disease of bone and bone marrow that results in bone destruction due to an infective microorganism, most frequently Staphylococcus aureus. Orthopaedic concern relates to the need for reconstructive and trauma-related surgical procedures in the fast grow¬ing population of fragile, aged patients, who have an increased susceptibility to surgical site infections. Depending on the type of osteomyelitis, infection may be acute or a slowly progressing, low-grade infection. Peri-implant infections lead to implant loosening. The emerging antibiotic resistance of com¬mon pathogens further complicates the situation. With current imaging methods, significant limitations exist in the diagnosing of osteomyelitis and implant-related infections. Positron emission tomography (PET) with a glucose analogue, 18F-fluoro¬deoxyglucose (18F-FDG), seems to facilitate a more accurate diagnosis of chronic osteomyelitis. The method is based on the increased glucose consumption of activated inflammatory cells. Unfortunately, 18F-FDG accumulates also in sterile inflammation regions and causes false-positive findings, for exam¬ple, due to post-operative healing processes. Therefore, there is a clinical need for new, more infection-specific tracers. In addition, it is still unknown why 18F-FDG PET imaging is less accurate in the detec¬tion of periprosthetic joint infections, most frequently due to Staphylococcus epidermidis. This doctoral thesis focused on testing novel PET tracers (68Ga-chloride and 68Ga-DOTAVAP-P1) for early detections of bone infections and evaluated the role of pathogen-related factors in the appli¬cations of 18F-FDG PET in the diagnostics of bone infections. For preclinical models of S. epidermidis and S. aureus bone/implant infections, the significance of the causative pathogen was studied with respect to 18F-FDG uptake. In a retrospective analysis of patients with confirmed bone infections, the significance of the presence or absence of positive bacterial cultures on 18F-FDG uptake was evalu¬ated. 18F-FDG and 68Ga-chloride resulted in a similar uptake in S. aureus osteomyelitic bones. However, 68Ga-chloride did not show uptake in healing bones, and therefore it may be a more-specific tracer in the early post-operative or post-traumatic phase. 68Ga-DOTAVAP-P1, a novel synthetic peptide bind¬ing to vascular adhesion protein 1 (VAP-1), was able to detect the phase of inflammation in healing bones, but the uptake of the tracer was elevated also in osteomyelitis. Low-grade peri-implant infec¬tions due to S. epidermidis were characterized by a low uptake of 18F-FDG, which reflects the virulence of the causative pathogen and the degree of leukocyte infiltration. In the clinical study, no relationship was found between the level of 18F-FDG uptake and the presence of positive or negative bacterial cul¬tures. Thus 18F-FDG PET may help to confirm metabolically active infection process in patients with culture-negative, histologically confirmed, low-grade osteomyelitis.

Adaptation of TRIZ Method for Problem Solving in Process Engineering

TRIZ is one of the well-known tools, based on analytical methods for creative problem solving. This thesis suggests adapted version of contradiction matrix, a powerful tool of TRIZ and few principles based on concept of original TRIZ. It is believed that the proposed version would aid in problem solving, especially those encountered in chemical process industries with unit operations. In addition, this thesis would help fresh process engineers to recognize importance of various available methods for creative problem solving and learn TRIZ method of creative problem solving. This thesis work mainly provides idea on how to modify TRIZ based method according to ones requirements to fit in particular niche area and solve problems efficiently in creative way. Here in this case, the contradiction matrix developed is based on review of common problems encountered in chemical process industry, particularly in unit operations and resolutions are based on approaches used in past to handle those issues.

Modeling of weeds interference periods in bean

The research objective was to determine the effects of spacing and seeding density of common bean to the period prior to weed interference (PPI) and weed period prior to economic loss (WEEPPEL). The treatments consisted of periods of coexistence between culture and the weeds, with 0 to 10, 0 to 20, 0 to 30, 0 to 40, 0 to 50, 0 to 60, 0 to 70, and 0 to 80 days and a control maintained without weeds. In addition to the periods of coexistence, there were still studies with an inter-row of 0.45 and 0.60 m, 10 and 15 plants m-1. The experimental delineation used was randomized blocks with four repetitions per treatment. The grain productivity of the culture had a reduction of 63, 50, 42 and 57% when the coexistence with the weed plants was during the entire cycle of the culture for a row spacing of 0.45 m and a seeding density of 10 and 15 plants per meter; and a row spacing of 0.60m and a seeding density of 10 and 15 plants per meter, respectively. The PPI occurred in 23, 27, 13, and 19 days after crop emergence and WEEPPEL in 10, 9, 8, and 8 days, respectively.

Interoperability specifications and an automatic validation tool as a key factor for the support of a repository ecosystem

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Evolution of circadian organization in vertebrates

Circadian organization means the way in which the entire circadian system above the cellular level is put together physically and the principles and rules that determine the interactions among its component parts which produce overt rhythms of physiology and behavior. Understanding this organization and its evolution is of practical importance as well as of basic interest. The first major problem that we face is the difficulty of making sense of the apparently great diversity that we observe in circadian organization of diverse vertebrates. Some of this diversity falls neatly into place along phylogenetic lines leading to firm generalizations: i) in all vertebrates there is a "circadian axis" consisting of the retinas, the pineal gland and the suprachiasmatic nucleus (SCN), ii) in many non-mammalian vertebrates of all classes (but not in any mammals) the pineal gland is both a photoreceptor and a circadian oscillator, and iii) in all non-mammalian vertebrates (but not in any mammals) there are extraretinal (and extrapineal) circadian photoreceptors. An interesting explanation of some of these facts, especially the differences between mammals and other vertebrates, can be constructed on the assumption that early in their evolution mammals passed through a "nocturnal bottleneck". On the other hand, a good deal of the diversity among the circadian systems of vertebrates does not fall neatly into place along phylogenetic lines. In the present review we will consider how we might better understand such "phylogenetically incoherent" diversity and what sorts of new information may help to further our understanding of the evolution of circadian organization in vertebrates

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Contested dominance modifies the anovulatory consequences of social subordination in female marmosets

Dominance status among female marmosets is reflected in agonistic behavior and ovarian function. Socially dominant females receive submissive behavior from subordinates, while exhibiting normal ovulatory function. Subordinate females, however, receive agonistic behavior from dominants, while exhibiting reduced or absent ovulatory function. Such disparity in female fertility is not absolute, and groups with two breeding females have been described. The data reported here were obtained from 8 female-female pairs of captive female marmosets, each housed with a single unrelated male. Pairs were classified into two groups: "uncontested" dominance (UD) and "contested" dominance (CD), with 4 pairs each. Dominant females in UD pairs showed significantly higher frequencies (4.1) of agonism (piloerection, attack and chasing) than their subordinates (0.36), and agonistic behaviors were overall more frequently displayed by CD than by UD pairs. Subordinates in CD pairs exhibited more agonistic behavior (2.9) than subordinates in UD pairs (0.36), which displayed significantly more submissive (6.97) behaviors than their dominants (0.35). The data suggest that there is more than one kind of dominance relationship between female common marmosets. Assessment of progesterone levels showed that while subordinates in UD pairs appeared to be anovulatory, the degree of ovulatory disruption in subordinates of CD pairs was more varied and less complete. We suggest that such variation in female-female social dominance relationships and the associated variation in the degree and reliability of fertility suppression may explain variations of the reproductive condition of free-living groups of common marmosets.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

Microbial flora in organic honey samples of africanized honeybees from Parana river islands

The purpose of this study was to verify and compare the main contamination sources and the hygienic/sanitary conditions of organic honey samples of Apis mellifera from Parana River islands. Thirty-three (33) samples were analyzed between January 2005 and August 2006. Eleven (11) samples were collected by beekeepers and twenty-two (22) samples were collected and processed in accordance with ideal personal hygiene norms and good manufacturing practices. The samples underwent microbiological analysis in search of coliforms at 35 ºC and 45 ºC, as well as fungi enumeration analysis. As for fungi counting, the samples harvested by beekeepers showed values above the maximum established by Resolution nº 15/94 of Common Market Group - Mercosul. The results showed that secondary contamination sources are responsible for the reduction of organic honey quality.

Democracia consolidada e tamanho do Estado

Consolidated democracy and size of the State. Common sense suggests that the more consolidated democracies and advanced economies tend to be more efficient and produce smaller States. What is observed in practice, however, is a positive correlation between "democratic consolidation" and "tax burden" (as a proxy for"size of Government"). This finding, while not expressing any causal relationship between the two variables, is an evidence that a more republican and democratic State, as defined in Bresser-Pereira, must be able to provide, effectively and efficiently, broader public services with better quality. This is, in consolidated democracies, the State should not be small.

Käyttäjien manipulointi internetin yhteisöpalveluissa: Systemaattinen kirjallisuuskatsaus

Internetin yhteisöpalveluiden käyttäjien avoimuus ja sosiaalisuus altistavat heidät monenlaisille riskeille. “Social engineering” eli käyttäjien manipulointi on uhka, joka liittyy informaation hankkimiseen perinteisen kanssakäymisen kautta, mutta yhä enenevissä määrin myös internetissä. Kun kanssakäyminen tapahtuu internetin välityksellä, käyttäjien manipuloijat hyödyntävät yhteisöpalveluita yhteydenpitoon uhrien kanssa sekä paljon käyttäjäinformaatiota sisältävänä alustana. Tämän tutkielman tarkoitus on löytää internetin yhteisöpalveluiden ja käyttäjien manipuloinnin välinen yhteys. Tämä päämäärä saavutettiin etsimällä vastauksia kysymyksiin kuten: Mitkä ovat tyypilliset hyökkäystyypit? Miksi informaatiolla on niin suuri rooli? Mitä seurauksia ilmiöllä on ja miten hyökkäyksiltä on mahdollista suojautua? Vastaukset kysymyksiin löydettiin toteuttamalla systemaattinen kirjallisuuskatsaus. Katsaus muodostui yhdistämällä tärkeimmät löydökset 60 tarkoin valitusta ilmiötä käsittelevästä artikkelista. Käyttäjien manipuloinnin huomattiin olevan hyvin laaja ja monimutkainen ilmiö internetin yhteisöpalveluissa. Huomattiin, että manipulointia ilmenee sivustoilla useissa erilaisissa muodoissa, joita ovat muun muassa tietojen kalastelu, profiilien yhdistäminen, sosiaaliset sovellukset, roskaposti, haitalliset linkit, identiteettivarkaudet, tietovuodot ja erilaiset huijaukset, jotka hyödyntävät sekä ihmisluonnon että sivustojen perusominaisuuksia. Haavoittuvuus ja luottamus havaittiin myös tärkeiksi aspekteiksi, sillä ne yhdistävät informaation merkityksen ja ihmisluonnon, jotka molemmat ovat avaintekijöitä sekä manipuloinnissa että yhteisöpalvelusivustoilla. Vaikka ilmiön seurausten huomattiin olevan negatiivisia niin käyttäjien olemukselle internetissä kuin todellisessakin elämässä, havaittiin myös, että ilmiön ymmärtäminen ja tunnistaminen helpottaa siltä suojautumista