Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Käsinhitsauksen mekanisointiratkaisujen kehittäminen

Työn tavoitteena on kehittää asiakkaiden käsinhitsausta kartoittamalla heidän hitsaavaa tuotantoa, sekä sen mahdollisia ongelmia. Järjestettävän hitsauskokeen avulla mitataan mekanisoidun hitsauksen tuottavuutta, laatua ja työergonomiaa. Työ sisältää teoreettisen ja käytännöllisen osuuden. Teoreettinen osuus pohjautuu kirjallisuuteen ja käytännöllinen osuus eri yrityksien kyselyihin ja haastatteluihin sekä hitsauskokeeseen. Teoreettinen osuus käsittelee käsinhitsausta ja siihen liittyviä mekanisointiratkaisuja. Käsinhitsauksessa käsitellään yleisimmät käsinhitsausprosessit, käsinhitsattava tuote ja tuotanto sekä sen tuottavuutta. Mekanisointiratkaisuissa käsitellään yleisimmät mekanisointiratkaisut ja laitteet sekä käytännön toteutusta. Käytännöllisessä osuudessa yritykset pitivät nykyisin hitsauksessa tärkeimpänä hitsaajien ammattitaitoa, tuottavuutta, työn mielekkyyttä, laatua sekä työturvallisuutta. Yrityksien tulisi tarkastella tuotannossaan hitsaussolujen sisältöä, sisäistä logistiikkaa ja kappaleiden kiinnitystä. Kappaleenkäsittelijään yrityksiltä tuli paljon kehitysideoita, kuten kiinnitykseen valmiita ratkaisuja sekä pöytälevyyn erilaisia vaihtoehtoja. Hitsauskokeen perusteella kappaleenkäsittelijällä työaika oli 29,4 % pienempi kuin työpöydällä. Laadullisesti koe antoi myös positiivisia tuloksia, käsittelypöydässä hitsattuja rakenteita ei tarvinnut korjata, mutta normaalissa työpöydässä piti, jotta C –luokan vaatimukset täyttyivät. Työturvallisuuden ja ergonomian kannalta suurimmat hyödyt olivat hyvä työasento, huurujen ja kurkottelun vähentyminen, mahdollisten palovammojen vähentyminen sekä vähemmän vaaraa osien putoamisesta.

Lognormal abundance distribution of woody species in a cerrado fragment (São Carlos, southeastern Brazil)

The lognormal distribution model is frequently found in communities, especially those which are rich in species and influenced by many environmental factors, as those of the cerrado. We tested the hypothesis that the abundance distribution of woody plant species in a cerrado fragment fits the lognormal model. We placed 20 lines in a cerrado fragment and sampled, with the point-quarter method, 800 individuals with stem perimeter equal or larger than 3 cm. We plotted the abundance-class histogram of the species, verified its normality with the Kolmogorov-Smirnov test, and estimated the expected number of woody species for this community. Of the 63 obtained species, Anadenanthera falcata (with 185 species), Eriotheca gracilipes (43), Stryphnodendron obovatum (37), and Miconia albicans (36) were the most abundant ones. Twelve species were represented by only one individual. We did not reject the null hypotheses that the distribution of woody component species was normal and, thus, their abundances fitted the lognormal model. Therefore, with our work, we can predict that cerrado plant communities fit the lognormal model. If this pattern is maintained in other cerrado communities, there would be implications for the conservation of this vegetation type, because rare species are susceptible of extinction, and implications to their structure, because the dominant species may act as keystone species.

Influence of air temperature on proteinase activity and beverage quality in Coffea arabica

Fruits were collected from trees of Coffea arabica cv. Obatã grown at Mococa and Adamantina in São Paulo State, Brazil, which are regions with marked differences in air temperature that produce coffee with distinct qualities. Mococa is a cooler location that produces high-quality coffee, whereas coffee from Adamantina is of lower quality. The amino acid and protein contents, amino acid profile, and proteinase activity and type in endosperm protein extracts were analysed. Proteinase genes were identified, and their expression was assayed. All results indicate that temperature plays a role in controlling proteinase activity in coffee endosperm. Proteinase activity was higher in the endosperm of immature fruits from Adamantina, which was correlated with higher amino acid content, changes in the amino acid profile, and increased gene expression. Cysteine proteinases were the main class of proteinases in the protein extracts. These data suggest that temperature plays an important role in coffee quality by altering nitrogen compound composition.

Memory-impairing effects of local anesthetics in an elevated plus-maze test in mice

Post-training intracerebroventricular administration of procaine (20 µg/µl) and dimethocaine (10 or 20 µg/µl), local anesthetics of the ester class, prolonged the latency (s) in the retention test of male and female 3-month-old Swiss albino mice (25-35 g body weight; N = 140) in the elevated plus-maze (mean ± SEM for 10 male mice: control = 41.2 ± 8.1; procaine = 78.5 ± 10.3; 10 µg/µl dimethocaine = 58.7 ± 12.3; 20 µg/µl dimethocaine = 109.6 ± 5.73; for 10 female mice: control = 34.8 ± 5.8; procaine = 55.3 ± 13.4; 10 µg/µl dimethocaine = 59.9 ± 12.3 and 20 µg/µl dimethocaine = 61.3 ± 11.1). However, lidocaine (10 or 20 µg/µl), an amide class type of local anesthetic, failed to influence this parameter. Local anesthetics at the dose range used did not affect the motor coordination of mice exposed to the rota-rod test. These results suggest that procaine and dimethocaine impair some memory process(es) in the plus-maze test. These findings are interpreted in terms of non-anesthetic mechanisms of action of these drugs on memory impairment and also confirm the validity of the elevated plus-maze for the evaluation of drugs affecting learning and memory in mice

Konepajan hitsaustuotannon kehittäminen kattavien laatuvaatimusten mukaiseksi

TIIVISTELMÄ Lappeenrannan teknillinen yliopisto Konetekniikan koulutusohjelma Voitto Kettunen Konepajan hitsaustuotannon kehittäminen kattavien laatuvaatimusten mukaiseksi Diplomityö 2015 167 sivua, 39 kuvaa, 26 taulukkoa ja 3 liitettä Tarkastajat: Professori Jukka Martikainen DI Pertti Kaarre Hakusanat: hitsaus, hitsauksen laatu, konepajan laadunhallinta, kattavat laatuvaatimukset, ISO 9001, ISO 3834, EN 1090 Keywords: welding, quality of welding, engineering workshop quality management, comprehensive quality requirements, ISO 9001, ISO 3834, EN 1090 Hitsaamalla liitetyt teräksiset rakenteet muodostavat ylivoimaisesti suurimman osan konepajatuotannosta. Niihin kuuluu esimerkiksi ajoneuvoja, koneita, laitteita, säiliöitä, siiloja, siltoja, mastoja, piippuja, tukirakenteita ja rakennusten runkoja. Tämän diplomityön tavoitteena on kehittää konepajan laadunhallinta sellaiseksi, että se mahdollistaa kattavien laatuvaatimusten täyttämisen hitsaustuotannossa. Laatuvaatimusten täyttämiseen pyritään käyttämällä hitsaustoimintojen standardia EN ISO 3834-2 sekä kantavien teräsrakenteiden standardeja EN 1090-1 ja EN 1090-2. Teräsrakenteiden suunnittelua ohjaa EN 1993 ja niiden toiminnallisia ominaisuuksia tuotestandardit, kuten terässavupiippu- ja säiliöstandardit. Kantavien teräsrakenteiden suunnittelua ja tuotantoa ohjaa myös seuraamusluokan CC, käyttöluokan SC ja tuotantoluokan PC kautta määräytyvä toteutusluokka EXC. Aikaisempaa enemmän tullaan panostamaan esimerkiksi asiakirjojen sähköiseen hallintaan, raaka-aineiden jäljitettävyyteen tuotteeseen, särmien ja kulmien muotoiluun, pintojen käsittelyyn, hitsien tarkastukseen, hitsaushenkilöstön pätevyyteen ja hitsaustuotannon tehokkuuteen. Saarijärven Säiliövalmiste Oy:n hitsauksen laadunhallinta sertifioitiin standardin ISO 3834-2 mukaan ja kantavien teräsrakenteiden FPC-järjestelmä standardisarjaa EN 1090 noudattaen. Samalla tehtiin päivitys laadunhallintajärjestelmään ISO 9001. Toteutus, joka tehtiin sovitussa aikataulussa, haastaa jokaisen toimijan konepajassa toiminnan, tuotannon ja tuotteiden laadun kehittämiseen uusia käytänteitä ja menetelmiä soveltaen. Kehitystoimien tuloksena toiminta on selkeämpää, ennakoitavampaa ja hallitumpaa, mikä lisää yrityksen toiminnan tuottavuutta ja kannattavuutta. Sertifioidut laatujärjestelmät ovat myötävaikuttaneet tilausten lisääntymiseen yrityksen kaikkien tuotteiden osalta.

Aurapten, a coumarin with growth inhibition against Leishmania major promastigotes

Several natural compounds have been identified for the treatment of leishmaniasis. Among them are some alkaloids, chalcones, lactones, tetralones, and saponins. The new compound reported here, 7-geranyloxycoumarin, called aurapten, belongs to the chemical class of the coumarins and has a molecular weight of 298.37. The compund was extracted from the Rutaceae species Esenbeckia febrifuga and was purified from a hexane extract starting from 407.7 g of dried leaves and followed by four silica gel chromatographic fractionation steps using different solvents as the mobile phase. The resulting compound (47 mg) of shows significant growth inhibition with an LD50 of 30 µM against the tropical parasite Leishmania major, which causes severe clinical manifestations in humans and is endemic in the tropical and subtropical regions. In the present study, we investigated the atomic structure of aurapten in order to determine the existence of common structural motifs that might be related to other coumarins and potentially to other identified inhibitors of Leishmania growth and viability. This compound has a comparable inhibitory activity of other isolated molecules. The aurapten is a planar molecule constituted of an aromatic system with electron delocalization. A hydrophobic side chain consisting of ten carbon atoms with two double bonds and negative density has been identified and may be relevant for further compound synthesis.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Meningoencephalitis caused by a zygomycete fungus (Basidiobolus) associated with septic shock in an immunocompetent patient: 1-year follow-up after treatment

Zygomycosis is an infection caused by opportunistic fungi of the Zygomycetes class, specifically those from the Mucorales and Entomophthorales orders. It is an uncommon disease, mainly restricted to immunocompromised patients. We report a case of a 73-year-old male patient with a history of fever (39°C) lasting for 1 day, accompanied by shivering, trembling, and intense asthenia. The patient was admitted to the intensive care unit with complex partial seizures, and submitted to orotracheal intubation and mechanical ventilation under sedation with midazolam. The electroencephalogram showed evidence of non-convulsive status epilepticus. There is no fast specific laboratory test that permits confirmation of invasive fungal disease. Unless the physician suspects this condition, the disease may progress rapidly while the patient is treated with broad-spectrum antibiotics. Differential diagnosis between fungal and bacterial infection is often difficult. The clinical presentation is sometimes atypical, and etiological investigation is not always successful. In the present case, the histopathological examination of the biopsy obtained from the right temporal lobe indicated the presence of irregular, round, thick-walled fungi forming papillae and elongated structures of irregular diameter, with no septa, indicative of zygomycete (Basidiobolus). Treatment with liposomal amphotericin B and fluconazole was initiated after diagnosis of meningoencephalitis by zygomycete, with a successful outcome.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Socially shared metacognitive regulation during collaborative learning processes in student dyads and small groups

Traditionally metacognition has been theorised, methodologically studied and empirically tested from the standpoint mainly of individuals and their learning contexts. In this dissertation the emergence of metacognition is analysed more broadly. The aim of the dissertation was to explore socially shared metacognitive regulation (SSMR) as part of collaborative learning processes taking place in student dyads and small learning groups. The specific aims were to extend the concept of individual metacognition to SSMR, to develop methods to capture and analyse SSMR and to validate the usefulness of the concept of SSMR in two different learning contexts; in face-to-face student dyads solving mathematical word problems and also in small groups taking part in inquiry-based science learning in an asynchronous computer-supported collaborative learning (CSCL) environment. This dissertation is comprised of four studies. In Study I, the main aim was to explore if and how metacognition emerges during problem solving in student dyads and then to develop a method for analysing the social level of awareness, monitoring, and regulatory processes emerging during the problem solving. Two dyads comprised of 10-year-old students who were high-achieving especially in mathematical word problem solving and reading comprehension were involved in the study. An in-depth case analysis was conducted. Data consisted of over 16 (30–45 minutes) videotaped and transcribed face-to-face sessions. The dyads solved altogether 151 mathematical word problems of different difficulty levels in a game-format learning environment. The interaction flowchart was used in the analysis to uncover socially shared metacognition. Interviews (also stimulated recall interviews) were conducted in order to obtain further information about socially shared metacognition. The findings showed the emergence of metacognition in a collaborative learning context in a way that cannot solely be explained by individual conception. The concept of socially-shared metacognition (SSMR) was proposed. The results highlighted the emergence of socially shared metacognition specifically in problems where dyads encountered challenges. Small verbal and nonverbal signals between students also triggered the emergence of socially shared metacognition. Additionally, one dyad implemented a system whereby they shared metacognitive regulation based on their strengths in learning. Overall, the findings suggested that in order to discover patterns of socially shared metacognition, it is important to investigate metacognition over time. However, it was concluded that more research on socially shared metacognition, from larger data sets, is needed. These findings formed the basis of the second study. In Study II, the specific aim was to investigate whether socially shared metacognition can be reliably identified from a large dataset of collaborative face-to-face mathematical word problem solving sessions by student dyads. We specifically examined different difficulty levels of tasks as well as the function and focus of socially shared metacognition. Furthermore, the presence of observable metacognitive experiences at the beginning of socially shared metacognition was explored. Four dyads participated in the study. Each dyad was comprised of high-achieving 10-year-old students, ranked in the top 11% of their fourth grade peers (n=393). Dyads were from the same data set as in Study I. The dyads worked face-to-face in a computer-supported, game-format learning environment. Problem-solving processes for 251 tasks at three difficulty levels taking place during 56 (30–45 minutes) lessons were video-taped and analysed. Baseline data for this study were 14 675 turns of transcribed verbal and nonverbal behaviours observed in four study dyads. The micro-level analysis illustrated how participants moved between different channels of communication (individual and interpersonal). The unit of analysis was a set of turns, referred to as an ‘episode’. The results indicated that socially shared metacognition and its function and focus, as well as the appearance of metacognitive experiences can be defined in a reliable way from a larger data set by independent coders. A comparison of the different difficulty levels of the problems suggested that in order to trigger socially shared metacognition in small groups, the problems should be more difficult, as opposed to moderately difficult or easy. Although socially shared metacognition was found in collaborative face-to-face problem solving among high-achieving student dyads, more research is needed in different contexts. This consideration created the basis of the research on socially shared metacognition in Studies III and IV. In Study III, the aim was to expand the research on SSMR from face-to-face mathematical problem solving in student dyads to inquiry-based science learning among small groups in an asynchronous computer-supported collaborative learning (CSCL) environment. The specific aims were to investigate SSMR’s evolvement and functions in a CSCL environment and to explore how SSMR emerges at different phases of the inquiry process. Finally, individual student participation in SSMR during the process was studied. An in-depth explanatory case study of one small group of four girls aged 12 years was carried out. The girls attended a class that has an entrance examination and conducts a language-enriched curriculum. The small group solved complex science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry during 22 lessons (á 45–minute). Students’ network discussion were recorded in written notes (N=640) which were used as study data. A set of notes, referred to here as a ‘thread’, was used as the unit of analysis. The inter-coder agreement was regarded as substantial. The results indicated that SSMR emerges in a small group’s asynchronous CSCL inquiry process in the science domain. Hence, the results of Study III were in line with the previous Study I and Study II and revealed that metacognition cannot be reduced to the individual level alone. The findings also confirm that SSMR should be examined as a process, since SSMR can evolve during different phases and that different SSMR threads overlapped and intertwined. Although the classification of SSMR’s functions was applicable in the context of CSCL in a small group, the dominant function was different in the asynchronous CSCL inquiry in the small group in a science activity than in mathematical word problem solving among student dyads (Study II). Further, the use of different analytical methods provided complementary findings about students’ participation in SSMR. The findings suggest that it is not enough to code just a single written note or simply to examine who has the largest number of notes in the SSMR thread but also to examine the connections between the notes. As the findings of the present study are based on an in-depth analysis of a single small group, further cases were examined in Study IV, as well as looking at the SSMR’s focus, which was also studied in a face-to-face context. In Study IV, the general aim was to investigate the emergence of SSMR with a larger data set from an asynchronous CSCL inquiry process in small student groups carrying out science activities. The specific aims were to study the emergence of SSMR in the different phases of the process, students’ participation in SSMR, and the relation of SSMR’s focus to the quality of outcomes, which was not explored in previous studies. The participants were 12-year-old students from the same class as in Study III. Five small groups consisting of four students and one of five students (N=25) were involved in the study. The small groups solved ill-defined science problems in an asynchronous CSCL environment, participating in research-like processes of inquiry over a total period of 22 hours. Written notes (N=4088) detailed the network discussions of the small groups and these constituted the study data. With these notes, SSMR threads were explored. As in Study III, the thread was used as the unit of analysis. In total, 332 notes were classified as forming 41 SSMR threads. Inter-coder agreement was assessed by three coders in the different phases of the analysis and found to be reliable. Multiple methods of analysis were used. Results showed that SSMR emerged in all the asynchronous CSCL inquiry processes in the small groups. However, the findings did not reveal any significantly changing trend in the emergence of SSMR during the process. As a main trend, the number of notes included in SSMR threads differed significantly in different phases of the process and small groups differed from each other. Although student participation was seen as highly dispersed between the students, there were differences between students and small groups. Furthermore, the findings indicated that the amount of SSMR during the process or participation structure did not explain the differences in the quality of outcomes for the groups. Rather, when SSMRs were focused on understanding and procedural matters, it was associated with achieving high quality learning outcomes. In turn, when SSMRs were focused on incidental and procedural matters, it was associated with low level learning outcomes. Hence, the findings imply that the focus of any emerging SSMR is crucial to the quality of the learning outcomes. Moreover, the findings encourage the use of multiple research methods for studying SSMR. In total, the four studies convincingly indicate that a phenomenon of socially shared metacognitive regulation also exists. This means that it was possible to define the concept of SSMR theoretically, to investigate it methodologically and to validate it empirically in two different learning contexts across dyads and small groups. In-depth micro-level case analysis in Studies I and III showed the possibility to capture and analyse in detail SSMR during the collaborative process, while in Studies II and IV, the analysis validated the emergence of SSMR in larger data sets. Hence, validation was tested both between two environments and within the same environments with further cases. As a part of this dissertation, SSMR’s detailed functions and foci were revealed. Moreover, the findings showed the important role of observable metacognitive experiences as the starting point of SSMRs. It was apparent that problems dealt with by the groups should be rather difficult if SSMR is to be made clearly visible. Further, individual students’ participation was found to differ between students and groups. The multiple research methods employed revealed supplementary findings regarding SSMR. Finally, when SSMR was focused on understanding and procedural matters, this was seen to lead to higher quality learning outcomes. Socially shared metacognition regulation should therefore be taken into consideration in students’ collaborative learning at school similarly to how an individual’s metacognition is taken into account in individual learning.

Detection and quantification of Roundup Ready® soybean residues in sausage samples by conventional and real-time PCR

The increasing presence of products derived from genetically modified (GM) plants in human and animal diets has led to the development of detection methods to distinguish biotechnology-derived foods from conventional ones. The conventional and real-time PCR have been used, respectively, to detect and quantify GM residues in highly processed foods. DNA extraction is a critical step during the analysis process. Some factors such as DNA degradation, matrix effects, and the presence of PCR inhibitors imply that a detection or quantification limit, established for a given method, is restricted to a matrix used during validation and cannot be projected to any other matrix outside the scope of the method. In Brazil, sausage samples were the main class of processed products in which Roundup Ready® (RR) soybean residues were detected. Thus, the validation of methodologies for the detection and quantification of those residues is absolutely necessary. Sausage samples were submitted to two different methods of DNA extraction: modified Wizard and the CTAB method. The yield and quality were compared for both methods. DNA samples were analyzed by conventional and real-time PCR for the detection and quantification of Roundup Ready® soybean in the samples. At least 200 ng of total sausage DNA was necessary for a reliable quantification. Reactions containing DNA amounts below this value led to large variations on the expected GM percentage value. In conventional PCR, the detection limit varied from 1.0 to 500 ng, depending on the GM soybean content in the sample. The precision, performance, and linearity were relatively high indicating that the method used for analysis was satisfactory.

Estimating microalgae Synechococcus nidulans daily biomass concentration using neuro-fuzzy network

In this study, a neuro-fuzzy estimator was developed for the estimation of biomass concentration of the microalgae Synechococcus nidulans from initial batch concentrations, aiming to predict daily productivity. Nine replica experiments were performed. The growth was monitored daily through the culture medium optic density and kept constant up to the end of the exponential phase. The network training followed a full 3³ factorial design, in which the factors were the number of days in the entry vector (3,5 and 7 days), number of clusters (10, 30 and 50 clusters) and internal weight softening parameter (Sigma) (0.30, 0.45 and 0.60). These factors were confronted with the sum of the quadratic error in the validations. The validations had 24 (A) and 18 (B) days of culture growth. The validations demonstrated that in long-term experiments (Validation A) the use of a few clusters and high Sigma is necessary. However, in short-term experiments (Validation B), Sigma did not influence the result. The optimum point occurred within 3 days in the entry vector, 10 clusters and 0.60 Sigma and the mean determination coefficient was 0.95. The neuro-fuzzy estimator proved a credible alternative to predict the microalgae growth.

Cleavages in contemporary Finland : a study on party-voter ties

Cleavages have been central in understanding the relationship between political parties and voters but the credibility of cleavage approach has been increasingly debated. This is because of decreasing party loyalty, fewer ideological differences between the parties and general social structural change amongst other factors. By definition, cleavages arise when social structural groups recognize their clashing interests, which are reflected in common values and attitudes, and vote for parties that are dedicated to defend the interests of the groups concerned. This study assesses relevance of cleavage approach in the Finnish context. The research problem in this study is “what kind of a cleavage structure exists in Finland at the beginning of the 21st century? Finland represents a case that has traditionally been characterized by a strong and diverse cleavage structure, notable ideological fragmentation in the electorate and an ideologically diverse party system. Nevertheless, the picture of the party-voter ties in Finland still remains incomplete with regard to a thorough analysis of cleavages. In addition, despite the vast amount of literature on cleavages in political science, studies that thoroughly analyze national cleavage structures by assessing the relationship between social structural position, values and attitudes and party choice have been rare. The research questions are approached by deploying statistical analyses, and using Finnish National Election Studies from 2003, 2007 and 2011as data. In this study, seven different social structural cleavage bases are analyzed: native language, type of residential area, occupational class, education, denomination, gender and age cohorts. Four different value/attitudinal dimensions were identified in this study: economic right and authority, regional and socioeconomic equality, sociocultural and European Union dimensions. This study shows that despite the weak overall effect of social structural positions on values and attitudes, a few rather strong connections between them were identified. The overall impact of social structural position and values and attitudes on party choice varies significantly between parties. Cleavages still exist in Finland and the cleavage structure partly reflects the old basis in the Finnish party system. The cleavage that is based on the type of residential area and reflected in regional and socioeconomic equality dimensions concerns primarily the voters of the Centre Party and the Coalition Party. The linguistic cleavage concerns mostly the voters of the Swedish People’s Party. The classic class cleavage reflected in the regional and socioeconomic equality dimension concerns in turn first and foremost the blue-collar voters of the Left Alliance and the Social Democratic Party, the agricultural entrepreneur voters of the Centre Party and higher professional and manager voters of the Coalition Party. The conflict with the most potential as a cleavage is the one based on social status (occupational class and education) and it is reflected in sociocultural and EU dimensions. It sets the voters of the True Finns against the voters of the Green League and the Coalition Party. The study underlines the challenges the old parties have met after the volatile election in 2011, which shook the cleavage structure. It also describes the complexity involved in the Finnish conflict structure and the multidimensionality in the electoral competition between the parties.

Man måste tänka själv : klasslärares uppfattningar av undervisning i de naturvetenskapliga läroämnena

A teacher´s perception of a school subject affects a teacher´s teaching and by extension pupils´ learning. The main purpose of this thesis is to describe the variation in the ways class-teachers perceive teaching within science subjects and to illustrate how these teachers choose to work and why they choose as they do. This purpose is operationalized into three central research questions concerning a teacher´s perception of teaching, teachers´ experiences of working methods in the subject and different aspects that are consciously present when the teacher makes his or her choice of working methods. These aspects are viewed from two different perspectives: a subject educational perspective and a teacher perspective. The theoretical background of the study is interdisciplinary. The thesis is a qualitative study where the research approach is phenomenographic. The empirical investigation was made as two separate studies: a semistructured interview study (N = 15) followed by a stimulated recall study (N = 3), a combined interview and video-observation. Results from the empirical investigation indicate that regarding aims for science education teachers wish to awaken or maintain the pupils´ interest in nature and science and that the pupils within the science subjects shall build a base for fundamental general knowledge. As motives for teaching the science subjects teachers view the subjects as a foundation for everyday life, planning and democracy but also for pupils´ further studies and a possible career in the field. The interdisciplinary key competences and the care for the pupils´ well being are aspects that are consciously present when teachers make their choice of working methods. A great variation can be found in the teachers´ perceptions of the science subjects as subjects and of the working methods within these subjects. Teachers describe lack of time on their own part as well as for the pupil´s learning. Results from the empirical investigation also indicate that teachers modestly focus on aims for the teaching and communication regarding these aims. There seems to be an existing need for increased and qualitatively improved inservice education within these subjects.