Multivariate genetic divergence and hybrid performance of cacao (Theobroma cacao L.)

Genetic distances among cacao cultivars were calculated through multivariate analysis, using the D2 statistic, to examine racial group classification and to assess heterotic hybrids. A 5 x 5 complete diallel was evaluated. Over a five-year period (1986-1990), five cultivars of the S1 generation, pertaining to the Lower Amazon Forastero and Trinitario racial groups and 20 crosses between the corresponding S0 parents were analyzed, based upon five yield components - number of healthy and collected fruits per plant (NHFP and NCFP), wet seed weight per plant and per fruit (WSWP and WSWF), and percentage of diseased fruits per plant (PDFP). The diversity analysis suggested a close relationship between the Trinitario and Lower Amazon Forastero groups. A correlation coefficient (r) was calculated to determine the association between genetic diversity and heterosis. Genetic distance of parents by D2 was found to be linearly related to average performance of hybrids for WSWP and WSWF (r = 0.68, P < 0.05 and r = 0.76, P < 0.05, respectively). The heterotic performance for the same components was also correlated with D2, both with r = 0.66 (P < 0.05). A relationship between genetic divergence and combining ability effects was suggested because the most divergent cultivar exhibited a high general combining ability, generating the best performing hybrids. Results indicated that genetic diversity estimates can be useful in selecting parents for crosses and in assessing relationships among cacao racial groups.

Natural preference of zebrafish (Danio rerio) for a dark environment

The zebrafish (Danio rerio) has been used as a model in neuroscience but knowledge about its behavior is limited. The aim of this study was to determine the preference of this fish species for a dark or light environment. Initially we used a place preference test and in a second experiment we applied an exit latency test. A two-chamber aquarium was used for the preference test. The aquarium consisted of a black chamber and a white chamber. In the first experiment the animal was placed in the aquarium and the time spent in the two compartments was recorded for 10 min. More time was spent in the black compartment (Wilcoxon matched-pairs signed-rank test, T = 7, N1 = N2 = 18, P = 0.0001). In the second experiment the animal was placed in the black or white compartment and the time it took to go from the initial compartment to the opposite one was recorded. The test lasted a maximum of 10 min. The results showed that the animal spent more time to go from the black to the white compartment (Mann-Whitney rank sum test, T = 48, N1 = 9, N2 = 8, P<0.0230). These data suggest that this fish species has a natural preference for a dark environment and this characteristic can be very useful for the development of new behavioral paradigms for fish.

Stiffness based trajectory planning and feedforward based vibration suppression control of parallel robot machines

The dissertation proposes two control strategies, which include the trajectory planning and vibration suppression, for a kinematic redundant serial-parallel robot machine, with the aim of attaining the satisfactory machining performance. For a given prescribed trajectory of the robot's end-effector in the Cartesian space, a set of trajectories in the robot's joint space are generated based on the best stiffness performance of the robot along the prescribed trajectory. To construct the required system-wide analytical stiffness model for the serial-parallel robot machine, a variant of the virtual joint method (VJM) is proposed in the dissertation. The modified method is an evolution of Gosselin's lumped model that can account for the deformations of a flexible link in more directions. The effectiveness of this VJM variant is validated by comparing the computed stiffness results of a flexible link with the those of a matrix structural analysis (MSA) method. The comparison shows that the numerical results from both methods on an individual flexible beam are almost identical, which, in some sense, provides mutual validation. The most prominent advantage of the presented VJM variant compared with the MSA method is that it can be applied in a flexible structure system with complicated kinematics formed in terms of flexible serial links and joints. Moreover, by combining the VJM variant and the virtual work principle, a systemwide analytical stiffness model can be easily obtained for mechanisms with both serial kinematics and parallel kinematics. In the dissertation, a system-wide stiffness model of a kinematic redundant serial-parallel robot machine is constructed based on integration of the VJM variant and the virtual work principle. Numerical results of its stiffness performance are reported. For a kinematic redundant robot, to generate a set of feasible joints' trajectories for a prescribed trajectory of its end-effector, its system-wide stiffness performance is taken as the constraint in the joints trajectory planning in the dissertation. For a prescribed location of the end-effector, the robot permits an infinite number of inverse solutions, which consequently yields infinite kinds of stiffness performance. Therefore, a differential evolution (DE) algorithm in which the positions of redundant joints in the kinematics are taken as input variables was employed to search for the best stiffness performance of the robot. Numerical results of the generated joint trajectories are given for a kinematic redundant serial-parallel robot machine, IWR (Intersector Welding/Cutting Robot), when a particular trajectory of its end-effector has been prescribed. The numerical results show that the joint trajectories generated based on the stiffness optimization are feasible for realization in the control system since they are acceptably smooth. The results imply that the stiffness performance of the robot machine deviates smoothly with respect to the kinematic configuration in the adjacent domain of its best stiffness performance. To suppress the vibration of the robot machine due to varying cutting force during the machining process, this dissertation proposed a feedforward control strategy, which is constructed based on the derived inverse dynamics model of target system. The effectiveness of applying such a feedforward control in the vibration suppression has been validated in a parallel manipulator in the software environment. The experimental study of such a feedforward control has also been included in the dissertation. The difficulties of modelling the actual system due to the unknown components in its dynamics is noticed. As a solution, a back propagation (BP) neural network is proposed for identification of the unknown components of the dynamics model of the target system. To train such a BP neural network, a modified Levenberg-Marquardt algorithm that can utilize an experimental input-output data set of the entire dynamic system is introduced in the dissertation. Validation of the BP neural network and the modified Levenberg- Marquardt algorithm is done, respectively, by a sinusoidal output approximation, a second order system parameters estimation, and a friction model estimation of a parallel manipulator, which represent three different application aspects of this method.

Polysiloxane/PVA-glutaraldehyde hybrid composite as solid phase for immunodetections by ELISA

We developed an efficient method to prepare a hybrid inorganic-organic composite based on polyvinyl alcohol (PVA) and polysiloxane using the sol-gel disc technique. Antigen obtained from Yersinia pestis was covalently immobilized onto these discs with glutaraldehyde and used as solid phase in ELISA for antibody detection in serum of rabbits experimentally immunized with plague. Using 1.25 µg antigen per disc, a peroxidase conjugate dilution of 1:4,000 and a serum dilution of 1:200 were adequate for the establishment of the procedure. These values are similar to those used for PVA-glutaraldehyde discs, plasticized filter paper discs and the polyaniline-Dacron composite discs. This procedure is comparable to that which utilizes the adsorption of the antigen to conventional PVC plates, with the amount of antigen being one fourth that employed in conventional PVC plates (5 µg/well). In addition to the performance of the polysiloxane/PVA-glutaraldehyde disc as a matrix for immunodetection, its easy synthesis and low cost are additional advantages for commercial application.

Presence of the RHD pseudogene and the hybrid RHD-CE-Ds gene in Brazilians with the D-negative phenotype

The molecular basis for RHD pseudogene or RHDpsi is a 37-bp insertion in exon 4 of RHD. This insertion, found in two-thirds of D-negative Africans, appears to introduce a stop codon at position 210. The hybrid RHD-CE-Ds, where the 3' end of exon 3 and exons 4 to 8 are derived from RHCE, is associated with the VS+V- phenotype, and leads to a D-negative phenotype in people of African origin. We determined whether Brazilian blood donors of heterogeneous ethnic origin had RHDpsi and RHD-CE-Ds. DNA from 206 blood donors were tested for RHDpsi by a multiplex PCR that detects RHD, RHDpsi and the C and c alleles of RHCE. The RHD genotype was determined by comparison of size of amplified products associated with the RHD gene in both intron 4 and exon 10/3'-UTR. VS was determined by amplification of exon 5 of RHCE, and sequencing of PCR products was used to analyze C733G (Leu245Val). Twenty-two (11%) of the 206 D-negative Brazilians studied had the RHDpsi, 5 (2%) had the RHD-CE-Ds hybrid gene associated with the VS+V- phenotype, and 179 (87%) entirely lacked RHD. As expected, RHD was deleted in all the 50 individuals of Caucasian descent. Among the 156 individuals of African descent, 22 (14%) had inactive RHD and 3% had the RHD-CE-Ds hybrid gene. These data confirm that the inclusion of two different multiplex PCR for RHD is essential to test the D-negative Brazilian population in order to avoid false-positive typing of polytransfused patients and fetuses.

A Template for Cloud Technology Deployment in an Energy Trading Environment

Nykyaikaiset pilvipalvelut tarjoavat suurille yrityksille mahdollisuuden tehostaa laskennallista tietojenkäsittelyä. Pilvipalveluiden käyttöönotto tuo mukanaan kuitenkin esimerkiksi useita tietoturvakysymyksiä, joiden vuoksi käyttöönoton tulee olla tarkasti suunniteltua. Tämä tutkimus esittelee kirjallisuuskatsaukseen perustuvan, asteittaisen suunnitelman pilvipalveluiden käyttöönotolle energialiiketoimintaympäristössä. Kohdeyrityksen sisäiset haastattelut ja katsaus nykyisiin energiateollisuuden pilviratkaisuihin muodostavat kokonaiskuvan käyttöönoton haasteista ja mahdollisuuksista. Tutkimuksen päätavoitteena on esittää ratkaisut tyypillisiin pilvipalvelun käyttöönotossa esiintyviin ongelmiin käyttöönottomallin avulla. Tutkimuksessa rakennettu käyttöönottomalli testattiin esimerkkitapauksen avulla ja malli todettiin toimivaksi. Ulkoisten palveluiden herättämien tietoturvakysymysten takia käyttöönoton ensimmäiset osiot, kuten lopputuotteen määrittely ja huolellinen suunnittelu, ovat koko käyttöönottoprosessin ydin. Lisäksi pilvipalveluiden käyttöönotto vaatii nykyiseltä käyttöympäristöltä uusia teknisiä ja hallinnollisia taitoja. Tutkimuksen tulokset osoittavat pilvipalveluiden monipuolisen hyödyn erityisesti laskentatehon tarpeen vaihdellessa. Käyttöönottomallin rinnalle luotu kustannusvertailu tukee kirjallisuuskatsauksessa esille tuotuja hyötyjä ja tarjoaa kohdeyritykselle perusteen tutkimuksen eteenpäin viemiselle.

Utilization of AMI-Technology in a Multilayered Demand Response Service Environment

This thesis studied the performance of Advanced metering infrastructure systems in a challenging Demand Response environment. The aim was to find out what kind of challenges and bottlenecks could be met when utilizing AMI-systems in challenging Demand Response tasks. To find out the challenges and bottlenecks, a multilayered demand response service concept was formed. The service consists of seven different market layers which consist of Nordic electricity market and the reserve markets of Fingrid. In the simulations the AMI-systems were benchmarked against these seven market layers. It was found out, that the current generation AMI-systems were capable of delivering Demand Response on the most challenging market layers, when observed from time critical viewpoint. Additionally, it was found out, that to enable wide scale Demand Response there are three major challenges to be acknowledged. The challenges hindering the utilization of wide scale Demand Response were related to poor standardization of the systems in use, possible problems in data connectivity solutions and the current electricity market regulation model.

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.

Novel virtual environment and real-time simulation based methods for improving life-cycle efficiency of non-road mobile machinery

Virtual environments and real-time simulators (VERS) are becoming more and more important tools in research and development (R&D) process of non-road mobile machinery (NRMM). The virtual prototyping techniques enable faster and more cost-efficient development of machines compared to use of real life prototypes. High energy efficiency has become an important topic in the world of NRMM because of environmental and economic demands. The objective of this thesis is to develop VERS based methods for research and development of NRMM. A process using VERS for assessing effects of human operators on the life-cycle efficiency of NRMM was developed. Human in the loop simulations are ran using an underground mining loader to study the developed process. The simulations were ran in the virtual environment of the Laboratory of Intelligent Machines of Lappeenranta University of Technology. A physically adequate real-time simulation model of NRMM was shown to be reliable and cost effective in testing of hardware components by the means of hardware-in-the-loop (HIL) simulations. A control interface connecting integrated electro-hydraulic energy converter (IEHEC) with virtual simulation model of log crane was developed. IEHEC consists of a hydraulic pump-motor and an integrated electrical permanent magnet synchronous motorgenerator. The results show that state of the art real-time NRMM simulators are capable to solve factors related to energy consumption and productivity of the NRMM. A significant variation between the test drivers is found. The results show that VERS can be used for assessing human effects on the life-cycle efficiency of NRMM. HIL simulation responses compared to that achieved with conventional simulation method demonstrate the advances and drawbacks of various possible interfaces between the simulator and hardware part of the system under study. Novel ideas for arranging the interface are successfully tested and compared with the more traditional one. The proposed process for assessing the effects of operators on the life-cycle efficiency will be applied for wider group of operators in the future. Driving styles of the operators can be analysed statistically from sufficient large result data. The statistical analysis can find the most life-cycle efficient driving style for the specific environment and machinery. The proposed control interface for HIL simulation need to be further studied. The robustness and the adaptation of the interface in different situations must be verified. The future work will also include studying the suitability of the IEHEC for different working machines using the proposed HIL simulation method.

Consumers' opinions on scent marketing usage in retail environment

Tutkielman tarkoituksena on tutkia suomalaisten kuluttajien mielipiteitä ja käsityksiä tuoksumarkkinoinnin käytöstä vähittäistavarakauppa olosuhteissa. Tutkielma keskittyy tuoksumarkkinoinnin kahteen pääasialliseen osa-alueeseen vähittäistavarakaupassa; tuoksumarkkinointiin osana brändäystä ja tuoksumarkkinoinnin alitajuntaiseen käyttöön. Tutkielma on laadullinen tutkimus. Aineisto kerättiin viideltä suomalaiselta kuluttajalta ja aineistonkeruumenetelmänä toimi haastattelu. Tutkimuksen tulokset osoittavat kuluttajien mielipiteiden olevan positiivisia tuoksumarkkinoinnin käyttöä kohtaan. Tuloksien mukaan kuluttajat suosivat tuoksumarkkinoinnin käyttöä ennemmin brändäyksessä kuin tuoksumarkkinoinnin alitajuista käyttöä. Tuoksumarkkinoinnin alitajuista käyttöä ei kuitenkaan todettu täysin negatiiviseksi, sillä kuluttajat uskovat, että ostopäätös tehdään perustuen tärkeämpiin asioihin kuin tuoksuun, kuten esimerkiksi tuotteen hintaan perustuen. Kuluttajat uskovat, että alitajuisella käytöllä ei ole suurta vaikutusta asiakkaan ostopäätökseen muulloin kuin joissakin yksittäisissä heräteostoksissa.

Readout architectures for hybrid pixel detector readout chips

The original contribution of this thesis to knowledge are novel digital readout architectures for hybrid pixel readout chips. The thesis presents asynchronous bus-based architecture, a data-node based column architecture and a network-based pixel matrix architecture for data transportation. It is shown that the data-node architecture achieves readout efficiency 99% with half the output rate as a bus-based system. The network-based solution avoids “broken” columns due to some manufacturing errors, and it distributes internal data traffic more evenly across the pixel matrix than column-based architectures. An improvement of > 10% to the efficiency is achieved with uniform and non-uniform hit occupancies. Architectural design has been done using transaction level modeling (TLM) and sequential high-level design techniques for reducing the design and simulation time. It has been possible to simulate tens of column and full chip architectures using the high-level techniques. A decrease of > 10 in run-time is observed using these techniques compared to register transfer level (RTL) design technique. Reduction of 50% for lines-of-code (LoC) for the high-level models compared to the RTL description has been achieved. Two architectures are then demonstrated in two hybrid pixel readout chips. The first chip, Timepix3 has been designed for the Medipix3 collaboration. According to the measurements, it consumes < 1 W/cm^2. It also delivers up to 40 Mhits/s/cm^2 with 10-bit time-over-threshold (ToT) and 18-bit time-of-arrival (ToA) of 1.5625 ns. The chip uses a token-arbitrated, asynchronous two-phase handshake column bus for internal data transfer. It has also been successfully used in a multi-chip particle tracking telescope. The second chip, VeloPix, is a readout chip being designed for the upgrade of Vertex Locator (VELO) of the LHCb experiment at CERN. Based on the simulations, it consumes < 1.5 W/cm^2 while delivering up to 320 Mpackets/s/cm^2, each packet containing up to 8 pixels. VeloPix uses a node-based data fabric for achieving throughput of 13.3 Mpackets/s from the column to the EoC. By combining Monte Carlo physics data with high-level simulations, it has been demonstrated that the architecture meets requirements of the VELO (260 Mpackets/s/cm^2 with efficiency of 99%).

Association between the increase in brain temperature and physical performance at different exercise intensities and protocols in a temperate environment

There is evidence that brain temperature (Tbrain) provides a more sensitive index than other core body temperatures in determining physical performance. However, no study has addressed whether the association between performance and increases in Tbrain in a temperate environment is dependent upon exercise intensity, and this was the primary aim of the present study. Adult male Wistar rats were subjected to constant exercise at three different speeds (18, 21, and 24 m/min) until the onset of volitional fatigue. Tbrain was continuously measured by a thermistor inserted through a brain guide cannula. Exercise induced a speed-dependent increase in Tbrain, with the fastest speed associated with a higher rate of Tbrain increase. Rats subjected to constant exercise had similar Tbrain values at the time of fatigue, although a pronounced individual variability was observed (38.7-41.7°C). There were negative correlations between the rate of Tbrain increase and performance for all speeds that were studied. These results indicate that performance during constant exercise is negatively associated with the increase in Tbrain, particularly with its rate of increase. We then investigated how an incremental-speed protocol affected the association between the increase in Tbrain and performance. At volitional fatigue, Tbrain was lower during incremental exercise compared with the Tbrain resulting from constant exercise (39.3±0.3 vs 40.3±0.1°C; P<0.05), and no association between the rate of Tbrain increase and performance was observed. These findings suggest that the influence of Tbrain on performance under temperate conditions is dependent on exercise protocol.

Hypertension is associated with greater heat exchange during exercise recovery in a hot environment

Individuals with systemic arterial hypertension have a higher risk of heat-related complications. Thus, the aim of this study was to examine the thermoregulatory responses of hypertensive subjects during recovery from moderate-intensity exercise performed in the heat. A total of eight essential hypertensive (H) and eight normotensive (N) male subjects (age=46.5±1.3 and 45.6±1.4 years, body mass index=25.8±0.8 and 25.6±0.6 kg/m2, mean arterial pressure=98.0±2.8 and 86.0±2.3 mmHg, respectively) rested for 30 min, performed 1 h of treadmill exercise at 50% of maximal oxygen consumption, and rested for 1 h after exercise in an environmental chamber at 38°C and 60% relative humidity. Skin and core temperatures were measured to calculate heat exchange parameters. Mean arterial pressure was higher in the hypertensive than in the normotensive subjects throughout the experiment (P<0.05, unpaired t-test). The hypertensive subjects stored less heat (H=-24.23±3.99 W·m−2vs N=-13.63±2.24 W·m−2, P=0.03, unpaired t-test), experienced greater variations in body temperature (H=-0.62±0.05°C vsN=-0.35±0.12°C, P=0.03, unpaired t-test), and had more evaporated sweat (H=-106.1±4.59 W·m−2vs N=-91.15±3.24 W·m−2, P=0.01, unpaired t-test) than the normotensive subjects during the period of recovery from exercise. In conclusion, essential hypertensive subjects showed greater sweat evaporation and increased heat dissipation and body cooling relative to normotensive subjects during recovery from moderate-intensity exercise performed in hot conditions.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

The new era of customer experience in the omni-channel environment of a communication service provider

This study discusses the evolution of an omni-channel model in managing customer experience. The purpose of this thesis is to expand the current academic literature available on omni-channel and offer suggestions for omni-channel creation. This is done by studying the features of an omni-channel approach into engaging with customers and through the sub-objectives of describing the process behind its initiation as well as the special features communication service providers need to take in consideration. Theories used as a background for this study are related to customer experience, channel management, omni-channel and finally change management. The empirical study of this thesis consists of seven expert interviews conducted in a case company. The interviews were held between March and November 2014. One of the interviewees is the manager of an omni-channel development team, whilst the rest were in charge of the management of the various customer channels of the company. The organization and analysis of the interview data was conducted topically. The use of themes related to major theories on the subject was utilized to create linkages between theory and practice. The responses were also organized in two groups based on the viewpoint to map responses related to the company perspective as well as the customers´ perspective. The findings in this study are that omni-channel is among the best tools for companies to respond to the challenge induced by changing customer needs and preferences, as well as intensifying competitive environment. The omni-channel model was found to promote excellent customer experience and thus to be a source of competition advantage and increasing financial returns by creating an omni-experience for the customer. Through omniexperience customers see all of the transactions with a company presenting one brand and providing ease and effortlessness in every encounter. The processes behind omni-channel formulation were identified as customer experience proclaimed as the most important strategic goal, mapping and establishing a unified brand experience in all (service) channels and empowering the first line personnel as the gate keepers of omniexperience. Further the tools, measurement and supporting strategies were to be in accordance with the omni-channel strategy and the customer needs to become a partner in a two way transaction with the firm. Based on these findings a model for omni-channel creation is offered. Future research is needed to firstly, further test these findings and expand the theoretical framework on omni-channel, as it is quite scarce to date and secondly, to increase the generalizability of the model suggested.