982 resultados para Hybrid integrated circuits


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RAPD-PCR molecular markers were used to identify common bean and soybean hybrid plants derived from crosses between closely related progenitors, with no apparent phenotypic differences. Primers OP-F12 and OP-0O3 were used to identify true hybrids derived from crosses between common bean cultivars Rudá (A 285) and AN 910408, and soybean cultivars Cristalina and Bossier, respectively. Each primer generated one polymorphic DNA band which was present in the male progenitor and absent in the female progenitor. As RAPD bands are normally inherited as dominant characters, the presence of these bands in the F1 plants confirmed their status.

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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.

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The greatest threat that the biodegradable waste causes on the environment is the methane produced in landfills by the decomposition of this waste. The Landfill Directive (1999/31/EC) aims to reduce the landfilling of biodegradable waste. In Finland, 31% of biodegradable municipal waste ended up into landfills in 2012. The pressure of reducing disposing into landfills is greatly increased by the forthcoming landfill ban on biodegradable waste in Finland. There is a need to discuss the need for increasing the utilization of biodegradable waste in regional renewable energy production to utilize the waste in a way that allows the best possibilities to reduce GHG emissions. The objectives of the thesis are: (1) to find important factors affecting renewable energy recovery possibilities from biodegradable waste, (2) to determine the main factors affecting the GHG balance of biogas production system and how to improve it and (3) to find ways to define energy performance of biogas production systems and what affects it. According to the thesis, the most important factors affecting the regional renewable energy possibilities from biodegradable waste are: the amount of available feedstock, properties of feedstock, selected utilization technologies, demand of energy and material products and the economic situation of utilizing the feedstocks. The biogas production by anaerobic digestion was seen as the main technology for utilizing biodegradable waste in agriculturally dense areas. The main reason for this is that manure was seen as the main feedstock, and it can be best utilized with anaerobic digestion, which can produce renewable energy while maintaining the spreading of nutrients on arable land. Biogas plants should be located close to the heat demand that would be enough to receive the produced heat also in the summer months and located close to the agricultural area where the digestate could be utilized. Another option for biogas use is to upgrade it to biomethane, which would require a location close to the natural gas grid. The most attractive masses for biogas production are municipal and industrial biodegradable waste because of gate fees the plant receives from them can provide over 80% of the income. On the other hand, directing gate fee masses for small-scale biogas plants could make dispersed biogas production more economical. In addition, the combustion of dry agricultural waste such as straw would provide a greater energy amount than utilizing them by anaerobic digestion. The complete energy performance assessment of biogas production system requires the use of more than one system boundary. These can then be used in calculating output–input ratios of biogas production, biogas plant, biogas utilization and biogas production system, which can be used to analyze different parts of the biogas production chain. At the moment, it is difficult to compare different biogas plants since there is a wide variation of definitions for energy performance of biogas production. A more consistent way of analyzing energy performance would allow comparing biogas plants with each other and other recovery systems and finding possible locations for further improvement. Both from the GHG emission balance and energy performance point of view, the energy consumption at the biogas plant was the most significant factor. Renewable energy use to fulfil the parasitic energy demand at the plant would be the most efficient way to reduce the GHG emissions at the plant. The GHG emission reductions could be increased by upgrading biogas to biomethane and displacing natural gas or petrol use in cars when compared to biogas CHP production. The emission reductions from displacing mineral fertilizers with digestate were seen less significant, and the greater N2O emissions from spreading digestate might surpass the emission reductions from displacing mineral fertilizers.

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This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

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Preparative liquid chromatography is one of the most selective separation techniques in the fine chemical, pharmaceutical, and food industries. Several process concepts have been developed and applied for improving the performance of classical batch chromatography. The most powerful approaches include various single-column recycling schemes, counter-current and cross-current multi-column setups, and hybrid processes where chromatography is coupled with other unit operations such as crystallization, chemical reactor, and/or solvent removal unit. To fully utilize the potential of stand-alone and integrated chromatographic processes, efficient methods for selecting the best process alternative as well as optimal operating conditions are needed. In this thesis, a unified method is developed for analysis and design of the following singlecolumn fixed bed processes and corresponding cross-current schemes: (1) batch chromatography, (2) batch chromatography with an integrated solvent removal unit, (3) mixed-recycle steady state recycling chromatography (SSR), and (4) mixed-recycle steady state recycling chromatography with solvent removal from fresh feed, recycle fraction, or column feed (SSR–SR). The method is based on the equilibrium theory of chromatography with an assumption of negligible mass transfer resistance and axial dispersion. The design criteria are given in general, dimensionless form that is formally analogous to that applied widely in the so called triangle theory of counter-current multi-column chromatography. Analytical design equations are derived for binary systems that follow competitive Langmuir adsorption isotherm model. For this purpose, the existing analytic solution of the ideal model of chromatography for binary Langmuir mixtures is completed by deriving missing explicit equations for the height and location of the pure first component shock in the case of a small feed pulse. It is thus shown that the entire chromatographic cycle at the column outlet can be expressed in closed-form. The developed design method allows predicting the feasible range of operating parameters that lead to desired product purities. It can be applied for the calculation of first estimates of optimal operating conditions, the analysis of process robustness, and the early-stage evaluation of different process alternatives. The design method is utilized to analyse the possibility to enhance the performance of conventional SSR chromatography by integrating it with a solvent removal unit. It is shown that the amount of fresh feed processed during a chromatographic cycle and thus the productivity of SSR process can be improved by removing solvent. The maximum solvent removal capacity depends on the location of the solvent removal unit and the physical solvent removal constraints, such as solubility, viscosity, and/or osmotic pressure limits. Usually, the most flexible option is to remove solvent from the column feed. Applicability of the equilibrium design for real, non-ideal separation problems is evaluated by means of numerical simulations. Due to assumption of infinite column efficiency, the developed design method is most applicable for high performance systems where thermodynamic effects are predominant, while significant deviations are observed under highly non-ideal conditions. The findings based on the equilibrium theory are applied to develop a shortcut approach for the design of chromatographic separation processes under strongly non-ideal conditions with significant dispersive effects. The method is based on a simple procedure applied to a single conventional chromatogram. Applicability of the approach for the design of batch and counter-current simulated moving bed processes is evaluated with case studies. It is shown that the shortcut approach works the better the higher the column efficiency and the lower the purity constraints are.

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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.

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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.

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In the last five years, a number of detailed anatomical, electrophysiological, optical imaging and simulation studies performed in a variety of non-human species have revealed that the functional organization of callosal connections between primary visual areas is more elaborate than previously thought. Callosal cell bodies and terminals are clustered in columns whose correspondence to features mapped in the visual cortex, such as orientation and ocularity, are starting to be understood. Callosal connections are not restricted to the vertical midline representation nor do they establish merely point-to-point retinotopic correspondences across the hemispheres, as traditionally believed. In addition, anatomical studies have revealed the existence of an ipsilateral component of callosal axons. The aim of this short review is to propose how these new data can be integrated into an updated scheme of the circuits responsible for assembling the primary visual field map.

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The purpose of this thesis is to examine how the reporting of operations related to green supply chain management and industrial symbiosis has evolved in UPM, Fortum and Kemira within the last ten years. The focus is on the improved operations, which are studied based on annual reports of these companies. The study provides a deeper understanding of the nature of green supply chain management and industrial symbiosis as well as the possibilites that their combination offers. The research is part of the DemaNET research project The study indicates that the environmental regulations and reporting standards have forced the studied companies to report their operations related to green supply chain management and industrial symbiosis more in detail during the last ten years. The operations related to green supply chain management in the studied companies are more common compared to operations related to industrial symbiosis. Often these two operations were also partially integrated, indicating a hybrid model. Even though firms often used hybrid models they still focused mainly on greening the internal operations rather than finding alternative ways for symbiosis outside the organization. The integration of green supply chain management and industrial symbiosis is most likely to occur when mutually beneficial relationships align the interests of all parties, thus resulting in the co-creation of value. The findings suggest that identifying mutual benefits and the flow of by-products are the ones that companies should give more attention to.

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The global interest towards renewable energy production such as wind and solar energy is increasing, which in turn calls for new energy storage concepts due to the larger share of intermittent energy production. Power-to-gas solutions can be utilized to convert surplus electricity to chemical energy which can be stored for extended periods of time. The energy storage concept explored in this thesis is an integrated energy storage tank connected to an oxy-fuel combustion plant. Using this approach, flue gases from the plant could be fed directly into the storage tank and later converted into synthetic natural gas by utilizing electrolysis-methanation route. This work utilizes computational fluid dynamics to model the desublimation of carbon dioxide inside a storage tank containing cryogenic liquid, such as liquefied natural gas. Numerical modelling enables the evaluation of the transient flow patterns caused by the desublimation, as well as general fluid behaviour inside the tank. Based on simulations the stability of the cryogenic storage and the magnitude of the key parameters can be evaluated.

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The main goal of this work is to clarify the idea of two thermochemical conversion processes of biomass - pyrolysis and torrefaction and to identify possible ways how and where exactly these processes can be integrated. Integration into CHP power plant process was chosen as one of the most promising ways. Multiple product development was determined by means of this integration concept. The analysis of the possible pros and cons was made based on some experimental data collected from the previous studies related to the topic of my work. In addition, one real integrated case was represented in the last part of the work. Finally, to highlight the main idea brief summarizing was done.

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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%).

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Happy emotional states have not been extensively explored in functional magnetic resonance imaging studies using autobiographic recall paradigms. We investigated the brain circuitry engaged during induction of happiness by standardized script-driven autobiographical recall in 11 healthy subjects (6 males), aged 32.4 ± 7.2 years, without physical or psychiatric disorders, selected according to their ability to vividly recall personal experiences. Blood oxygen level-dependent (BOLD) changes were recorded during auditory presentation of personal scripts of happiness, neutral content and negative emotional content (irritability). The same uniform structure was used for the cueing narratives of both emotionally salient and neutral conditions, in order to decrease the variability of findings. In the happiness relative to the neutral condition, there was an increased BOLD signal in the left dorsal prefrontal cortex and anterior insula, thalamus bilaterally, left hypothalamus, left anterior cingulate gyrus, and midportions of the left middle temporal gyrus (P < 0.05, corrected for multiple comparisons). Relative to the irritability condition, the happiness condition showed increased activity in the left insula, thalamus and hypothalamus, and in anterior and midportions of the inferior and middle temporal gyri bilaterally (P < 0.05, corrected), varying in size between 13 and 64 voxels. Findings of happiness-related increased activity in prefrontal and subcortical regions extend the results of previous functional imaging studies of autobiographical recall. The BOLD signal changes identified reflect general aspects of emotional processing, emotional control, and the processing of sensory and bodily signals associated with internally generated feelings of happiness. These results reinforce the notion that happiness induction engages a wide network of brain regions.

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The brain is a complex system, which produces emergent properties such as those associated with activity-dependent plasticity in processes of learning and memory. Therefore, understanding the integrated structures and functions of the brain is well beyond the scope of either superficial or extremely reductionistic approaches. Although a combination of zoom-in and zoom-out strategies is desirable when the brain is studied, constructing the appropriate interfaces to connect all levels of analysis is one of the most difficult challenges of contemporary neuroscience. Is it possible to build appropriate models of brain function and dysfunctions with computational tools? Among the best-known brain dysfunctions, epilepsies are neurological syndromes that reach a variety of networks, from widespread anatomical brain circuits to local molecular environments. One logical question would be: are those complex brain networks always producing maladaptive emergent properties compatible with epileptogenic substrates? The present review will deal with this question and will try to answer it by illustrating several points from the literature and from our laboratory data, with examples at the behavioral, electrophysiological, cellular and molecular levels. We conclude that, because the brain is a complex system compatible with the production of emergent properties, including plasticity, its functions should be approached using an integrated view. Concepts such as brain networks, graphics theory, neuroinformatics, and e-neuroscience are discussed as new transdisciplinary approaches dealing with the continuous growth of information about brain physiology and its dysfunctions. The epilepsies are discussed as neurobiological models of complex systems displaying maladaptive plasticity.

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This study aimed to assess the efficacy of a rural community-based integrated intervention for early prevention and management of chronic obstructive pulmonary disease (COPD) in China. This 18-year cluster-randomized controlled trial encompassing 15 villages included 1008 patients (454 men and 40 women in the intervention group [mean age, 54 ± 10 years]; 482 men and 32 women in the control group [mean age, 53 ± 10 years]) with confirmed COPD or at risk for COPD. Villages were randomly assigned to the intervention or the control group, and study participants residing within the villages received treatment accordingly. Intervention group patients took part in a program that included systematic health education, smoking cessation counseling, and education on management of COPD. Control group patients received usual care. The groups were compared after 18 years regarding the incidence of COPD, decline in lung function, and mortality of COPD. COPD incidence was lower in the intervention group than in the control group (10% vs 16%, <0.05). A decline in lung function was also significantly delayed in the intervention group compared to the control group of COPD and high-risk patients. The intervention group showed significant improvement in smoking cessation compared with the control group, and smokers in the intervention group had lower smoking indices than in the control group (350 vs 450, <0.05). The intervention group also had a significantly lower cumulative COPD-related death rate than the control group (37% vs 47%, <0.05). A rural community-based integrated intervention is effective in reducing the incidence of COPD among those at risk, delaying a decline in lung function in COPD patients and those at risk, and reducing mortality of COPD.