Neural mechanisms underlying adaptive actions after slips

An increase in cognitive control has been systematically observed in responses produced immediately after the commission of an error. Such responses show a delay in reaction time (post-error slowing) and an increase in accuracy. To characterize the neurophysiological mechanism involved in the adaptation of cognitive control, we examined oscillatory electrical brain activity by electroencephalogram and its corresponding neural network by event-related functional magnetic resonance imaging in three experiments. We identified a new oscillatory thetabeta component related to the degree of post-error slowing in the correct responses following an erroneous trial. Additionally, we found that the activity of the right dorsolateral prefrontal cortex, the right inferior frontal cortex, and the right superior frontal cortex was correlated with the degree of caution shown in the trial following the commission of an error. Given the overlap between this brain network and the regions activated by the need to inhibit motor responses in a stop-signal manipulation, we conclude that the increase in cognitive control observed after the commission of an error is implemented through the participation of an inhibitory mechanism.

A human immune data-informed vaccine concept elicits strong and broad T-cell specificities associated with HIV-1 control in mice and macaques

Background: None of the HIV T-cell vaccine candidates that have reached advanced clinical testing have been able to induce protective T cell immunity. A major reason for these failures may have been suboptimal T cell immunogen designs. Methods: To overcome this problem, we used a novel immunogen design approach that is based on functional T cell response data from more than 1,000 HIV-1 clade B and C infected individuals and which aims to direct the T cell response to the most vulnerable sites of HIV-1. Results: Our approach identified 16 regions in Gag, Pol, Vif and Nef that were relatively conserved and predominantly targeted by individuals with reduced viral loads. These regions formed the basis of the HIVACAT T-cell Immunogen (HTI) sequence which is 529 amino acids in length, includes more than 50 optimally defined CD4+ and CD8+ T-cell epitopes restricted by a wide range of HLA class I and II molecules and covers viral sites where mutations led to a dramatic reduction in viral replicative fitness. In both, C57BL/6 mice and Indian rhesus macaques immunized with an HTI-expressing DNA plasmid (DNA.HTI) induced broad and balanced T-cell responses to several segments within Gag, Pol, and Vif. DNA.HTI induced robust CD4+ and CD8+ T cell responses that were increased by a booster vaccination using modified virus Ankara (MVA.HTI), expanding the DNA.HTI induced response to up to 3.2% IFN-γ T-cells in macaques. HTI-specific T cells showed a central and effector memory phenotype with a significant fraction of the IFN-γ+ CD8+ T cells being Granzyme B+ and able to degranulate (CD107a+). Conclusions: These data demonstrate the immunogenicity of a novel HIV-1 T cell vaccine concept that induced broadly balanced responses to vulnerable sites of HIV-1 while avoiding the induction of responses to potential decoy targets that may divert effective T-cell responses towards variable and less protective viral determinants.

Cyclin-dependent kinases 4 and 6 control tumor progression and direct glucose oxidation in the pentose cycle

Cyclin-dependent kinases CDK4 and CDK6 are essential for the control of the cell cycle through the G1 phase. Aberrant expression of CDK4 and CDK6 is a hall- mark of cancer, which would suggest that CDK4 and CDK6 are attractive targets for cancer therapy. Herein, we report that calcein AM is a potent specific inhibitor of CDK4 and CDK6 in HCT116 human colon adenocarcinoma cells, inhibiting retinoblastoma protein (pRb) phosphorylation and inducing cell cycle arrest in the G1 phase. The metabolic effects of calcein AM (the calcein acetoxymethyl-ester) on HCT116 cells were also evaluated and the flux between the oxidative and non-oxidative branches of the pentose phos-phate pathway was significantly altered. To elucidate whe-ther these metabolic changes were due to the inhibition of CDK4 and CDK6, we also characterized the metabolic profile of a CDK4, CDK6 and CDK2 triple knockout of mouse embryonic fibroblasts. The results show that the metabolic profile associated with the depletion of CDK4, CDK6 and CDK2 coincides with the metabolic changes induced by calcein AM on HCT116 cells, thus confirming that the inhibition of CDK4 and CDK6 disrupts the balance between the oxidative and non-oxidative branches of the pentose phosphate pathway. Taken together, these results indicate that low doses of calcein can halt cell division and kill tumor cells. Thus, selective inhibition of CDK4 and CDK6 may be of greater pharmacological interest, since inhibitors of these kinases affect both cell cycle progression and the robust metabolic profile of tumors.

Control d'un sistema de marcatge làser de caixes

Avui en dia, l’alta competitivitat que existeix al mercat, fa que les empreses hagin d’esprémer al màxim les seves possibilitats per no quedar-se enrere. Un dels processos en que aquest fet hi és més present és el productiu. L’empresa JCM Technologies també engloba aquest camp i és en un dels seus processos productius on aquest projecte pren part. L’objectiu d’aquest projecte final de carrera ha estat desenvolupar un sistema per poder marcar caixes mitjançant un làser de CO2 i un automatisme manipulador de caixes. D’aquesta manera aquest procés productiu té una durada molt inferior a l’antic procés, que consistia en enganxar una etiqueta al lloc on ara és marcat pel làser. Per satisfer els objectius, s’ha creat una aplicació de Windows que per mitjà d’una interfície gràfica, permet a l’usuari realitzar els passos necessaris per fer el marcatge. Primerament es recullen les dades procedents de la comanda; seguidament es seleccionen les que s’han de marcar a les caixes i s’envien al làser mitjançant comunicació sèrie; una vegada aquesta inicialització ha finalitzat correctament, s’engega la seqüència de marcatge de les caixes, que en marcarà la quantitat indicada. Aquest procés de marcatge consisteix en supervisar l’estat en que es troben certes senyals, procedents de l’automatisme i del làser, i depenent d’aquestes generar-ne unes altres. Aconseguint així realitzar el procés de marcatge de cada caixa. Com a conclusions cal dir, que els objectius s’han complert, ja que s’ha aconseguit un procés de marcatge ràpid i robust. També s’ha aconseguit que les parts de configuració de l’aplicació, i de les caixes siguin de fàcil manipulació. Per tant, amb l’acompliment dels objectius d’aquest projecte, aconseguim completar el sistema de marcatge, i permetre que les caixes siguin marcades de forma correcta, ràpida i eficient.

Green tea in transdermal formulation: HPLC method for quality control and in vitro drug release assays

RP-HPLC based analytical method for use in both quality control of green tea in a semisolid formulation and for in vitro drug release assays was developed and validated. The method was precise (CV < 5%), accurate (recovery between 98% and 102%), linear (R² > 0.99), robust, and specific for the determination of epigallocatechin 3-gallate (EGCG), caffeine (CAF), and gallic acid (GA). In a diffusion cell chamber, the release rate of EGCG was 8896.01 µg cm-2. This data showed that EGCG will be able to exert its systemic activity when delivered though the transdermal formulation, due to its good flux rates with the synthetic membrane.

Phase voltage control and filtering in a converter-fed single-phase customer-end system of the LVDC distribution network

In recent years, the network vulnerability to natural hazards has been noticed. Moreover, operating on the limits of the network transmission capabilities have resulted in major outages during the past decade. One of the reasons for operating on these limits is that the network has become outdated. Therefore, new technical solutions are studied that could provide more reliable and more energy efficient power distributionand also a better profitability for the network owner. It is the development and price of power electronics that have made the DC distribution an attractive alternative again. In this doctoral thesis, one type of a low-voltage DC distribution system is investigated. Morespecifically, it is studied which current technological solutions, used at the customer-end, could provide better power quality for the customer when compared with the current system. To study the effect of a DC network on the customer-end power quality, a bipolar DC network model is derived. The model can also be used to identify the supply parameters when the V/kW ratio is approximately known. Although the model provides knowledge of the average behavior, it is shown that the instantaneous DC voltage ripple should be limited. The guidelines to choose an appropriate capacitance value for the capacitor located at the input DC terminals of the customer-end are given. Also the structure of the customer-end is considered. A comparison between the most common solutions is made based on their cost, energy efficiency, and reliability. In the comparison, special attention is paid to the passive filtering solutions since the filter is considered a crucial element when the lifetime expenses are determined. It is found out that the filter topology most commonly used today, namely the LC filter, does not provide economical advantage over the hybrid filter structure. Finally, some of the typical control system solutions are introduced and their shortcomings are presented. As a solution to the customer-end voltage regulation problem, an observer-based control scheme is proposed. It is shown how different control system structures affect the performance. The performance meeting the requirements is achieved by using only one output measurement, when operating in a rigid network. Similar performance can be achieved in a weak grid by DC voltage measurement. An additional improvement can be achieved when an adaptive gain scheduling-based control is introduced. As a conclusion, the final power quality is determined by a sum of various factors, and the thesis provides the guidelines for designing the system that improves the power quality experienced by the customer.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Applications and Benefits of Adaptive Pulsed GMAW

In ship and offshore terminal construction, welded cross sections are thick and the number of welds very high. Consequently, there are two aspects of great importance; cost and heat input. Reduction in the welding operation time decreases the costs of the work force and avoids excessive heat, preventing distortion and other weld defects. The need to increase productivity while using a single wire in the GMAW process has led to the use of a high current and voltage to improve the melting rate. Unfortunately, this also increases the heat input. Innovative GMAW processes, mostly implemented for sheet plate sections, have shown significant reduction in heat input (Q), low distortion and increase in welding speed. The aim of this study is to investigate adaptive pulsed GMAW processes and assess relevant applications in the high power range, considering possible benefits when welding thicker sections and high yield strength steel. The study experimentally tests the usability of adaptive welding processes and evaluates their effects on weld properties, penetration and shapes of the weld bead.The study first briefly reviews adaptive GMAW to evaluate different approaches and their applications and to identify benefits in adaptive pulsed. Experiments are then performed using Synergic Pulsed GMAW, WiseFusionTM and Synergic GMAW processes to weld a T-joint in a horizontal position (PB). The air gap between the parts ranges from 0 to 2.5 mm. The base materials are structural steel grade S355MC and filler material G3Si1. The experiment investigates heat input, mechanical properties and microstructure of the welded joint. Analysis of the literature reveals that different approaches have been suggested using advanced digital power sources with accurate waveform, current, voltage, and feedback control. In addition, studies have clearly indicated the efficiency of lower energy welding processes. Interest in the high power range is growing and a number of different approaches have been suggested. The welding experiments in this study reveal a significant reduction of heat input and a weld microstructure with the presence of acicular ferrite (AF) beneficial for resistance to crack propagation. The WiseFusion bead had higher dilution, due to the weld bead shape, and low defects. Adaptive pulse GMAW processes can be a favoured choice when welding structures with many welded joints. The total heat reduction mitigates residual stresses and the bead shape allows a higher amperage limit. The stability of the arc during the process is virtually spatter free and allows an increase in welding speed.

Variable structure position control of an industrial robotic manipulator

The use of a robust position controller for a robotic manipulator moving in free space is presented. The aim is to implement in practice a controller that is robust to uncertainties in the model of the system, as well as being inexpensive from a computational point of view. Variable structure theory provides the technique for the design of such controller. The design steps are presented, first from a theoretical perspective and then applied to the control of a two degree-of-freedom manipulator. Simulation results that backed the implementation are presented, followed by the experiments conducted and the results that were obtained. The conclusion is that variable structure control is readily applicable to industrial robots for the robust control of positions.

Control of transients in water distribution networks by H¥ Control

In this work, a controller for regulating the transients in water distribution networks is established. The control technique is the H¥ Control. The developed controller is applied to a water distribution network and the results of this application demonstrate that the technique allowed the establishment of a robust controller, capable of attenuating the disturbances in a suitable way, being effective in controlling the oscillations of the state variables in question.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

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.

Cardiovascular control in experimental diabetes

Several studies have reported impairment in cardiovascular function and control in diabetes. The studies cited in this review were carried out from a few days up to 3 months after streptozotocin administration and were concerned with the control of the circulation. We observed that early changes (5 days) in blood pressure control by different peripheral receptors were maintained for several months. Moreover, the impairment of reflex responses observed after baroreceptor and chemoreceptor stimulation was probably related to changes in the efferent limb of the reflex arc (sympathetic and parasympathetic), but changes also in the central nervous system could not be excluded. Changes in renal sympathetic nerve activity during volume expansion were blunted in streptozotocin-treated rats, indicating an adaptive natriuretic and diuretic response in the diabetic state. The improvement of diabetic cardiovascular dysfunction induced by exercise training seems to be related to changes in the autonomic nervous system. Complementary studies about the complex interaction between circulation control systems are clearly needed to adequately address the management of pathophysiological changes associated with diabetes.

Vascular adaptive responses to physical exercise and to stress are affected differently by nandrolone administration

Androgenic anabolic steroid, physical exercise and stress induce cardiovascular adaptations including increased endothelial function. The present study investigated the effects of these conditions alone and in combination on the vascular responses of male Wistar rats. Exercise was started at 8 weeks of life (60-min swimming sessions 5 days per week for 8 weeks, while carrying a 5% body-weight load). One group received nandrolone (5 mg/kg, twice per week for 8 weeks, im). Acute immobilization stress (2 h) was induced immediately before the experimental protocol. Curves for noradrenaline were obtained for thoracic aorta, with and without endothelium from sedentary and trained rats, submitted or not to stress, treated or not with nandrolone. None of the procedures altered the vascular reactivity to noradrenaline in denuded aorta. In intact aorta, stress and exercise produced vascular adaptive responses characterized by endothelium-dependent hyporeactivity to noradrenaline. These conditions in combination did not potentiate the vascular adaptive response. Exercise-induced vascular adaptive response was abolished by nandrolone. In contrast, the aortal reactivity to noradrenaline of sedentary rats and the vascular adaptive response to stress of sedentary and trained rats were not affected by nandrolone. Maximum response for 7-10 rats/group (g): sedentary 3.8 ± 0.2 vs trained 3.0 ± 0.2*; sedentary/stress 2.7 ± 0.2 vs trained/stress 3.1 ± 0.1*; sedentary/nandrolone 3.6 ± 0.1 vs trained/nandrolone 3.8 ± 0.1; sedentary/stress/nandrolone 3.2 ± 0.1 vs trained/stress/nandrolone 2.5 ± 0.1*; *P < 0.05 compared to its respective control. Stress and physical exercise determine similar vascular adaptive response involving distinct mechanisms as indicated by the observation that only the physical exercise-induced adaptive response was abolished by nandrolone.

Design of automatic control system for the precipitation of bromelain from the extract of pineapple wastes

In this work, bromelain was recovered from ground pineapple stem and rind by means of precipitation with alcohol at low temperature. Bromelain is the name of a group of powerful protein-digesting, or proteolytic, enzymes that are particularly useful for reducing muscle and tissue inflammation and as a digestive aid. Temperature control is crucial to avoid irreversible protein denaturation and consequently to improve the quality of the enzyme recovered. The process was carried out alternatively in two fed-batch pilot tanks: a glass tank and a stainless steel tank. Aliquots containing 100 mL of pineapple aqueous extract were fed into the tank. Inside the jacketed tank, the protein was exposed to unsteady operating conditions during the addition of the precipitating agent (ethanol 99.5%) because the dilution ratio "aqueous extract to ethanol" and heat transfer area changed. The coolant flow rate was manipulated through a variable speed pump. Fine tuned conventional and adaptive PID controllers were on-line implemented using a fieldbus digital control system. The processing performance efficiency was enhanced and so was the quality (enzyme activity) of the product.