Energy level decay and excited state absorption processes in erbium-doped tellurium glass

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Office of the State Long-Term Care Ombudsman: Role in Involuntary Discharges, November 25, 2014

Iowa law requires that a copy of the Notice of an Involuntary Discharge action given to residents of nursing facilities or residential care facilities also be given to the Office of the State Long-Term Care Ombudsman. In addition, the law requires that a copy of the Notice of an Involuntary Transfer/Eviction action given to tenants of an elder group home or assisted living program also be given to the Office of the State Long-Term Care Ombudsman.

Determinants of transfer of training: A comprehensive literature review

Investments in training measures can only be considered effective if the transfer of the learned contents to practical situations is continuously successful. In this context the scientific and professional discourse regarding the effectiveness of further education, especially regarding training transfer, has intensified considerably. This analysis provides a systematic and comprehensive overview of the current state of international empirical research regarding major influencing factors of learning transfer in the context of formalized further vocational training. Our review of literature differentiates the most important influencing factors on the micro-level of the specific individual characteristics of the participants, the meso-level of measure-specific characteristics of the field of learning, as well as institutional characteristics of the work environment at the macro-level. Decades of transfer research brings forth a wealth of information regarding factors which influence the learning transfer. The current analysis systematizes these results and clarifies that the current state of research regarding the determinants of the process of learning transfer shows clear trends. But there are also some inconsistent findings. Thus the question of which factors positively influence the success of learning transfer is well-studied for the micro-level in particular. The article shows that there is still a research deficit concerning the major determinants of learning transfer at the meso- and macro-level. Finally, in this context this article identifies promising directions for future research. (DIPF/Orig.)

Applications of Photoinduced Electron Transfer Chemistry: Photoremovable Protecting Groups and Carbon Dioxide Conversion

Traditional organic chemistry has long been dominated by ground state thermal reactions. The alternative to this is excited state chemistry, which uses light to drive chemical transformations. There is considerable interest in using this clean renewable energy source due to concerns surrounding the combustion byproducts associated with the consumption of fossil fuels. The work presented in this text will focus on the use of light (both ultraviolet and visible) for the following quantitative chemical transformations: (1) the release of compounds containing carboxylic acid and alcohol functional groups and (2) the conversion of carbon dioxide into other useable chemicals. Chapters 1-3 will introduce and explore the use of photoremovable protecting groups (PPGs) for the spatiotemporal control of molecular concentrations. Two new PPGs are discussed, the 2,2,2-tribromoethoxy group for the protection of carboxylic acids and the 9-phenyl-9-tritylone group for the protection of alcohols. Fundamental interest in the factors that affect C–X bond breaking has driven the work presented in this text for the release of carboxylic acid substrates. Product analysis from the UV photolysis of 2,2,2-tribromoethyl-(2′-phenylacetate) in various solvents results in the formation of H–atom abstraction products as well as the release of phenylacetic acid. The deprotection of alcohols is realized through the use of UV or visible light photolysis of 9-phenyl-9-tritylone ethers. Central to this study is the use of photoinduced electron transfer chemistry for the generation of ion diradicals capable of undergoing bond-breaking chemistry leading to the release of the alcohol substrates. Chapters 4 and 5 will explore the use of N-heterocyclic carbenes (NHCs) as a catalyst for the photochemical reduction of carbon dioxide. Previous experiments have demonstrated that NHCs can add to CO2 to form stable zwitterionic species known as N-heterocylic-2-carboxylates (NHC–CO2). Work presented in this text illustrate that the stability of these species is highly dependent on solvent polarity, consistent with a lengthening of the imidazolium to carbon dioxide bond (CNHC–CCO2). Furthermore, these adducts interact with excited state electron donors resulting in the generation of ion diradicals capable of converting carbon dioxide into formic acid.

Distribution of Ra-226, Th-232 and K-40 in soils and sugar cane crops at Corumbatai river basin, São Paulo State, Brazil

The common use of phosphate fertilizers NPK and amendments in sugar cane crops in Brazilian agriculture may increase the Ra-226, Th-232 and K-40 activity concentrations in soils and their availability for plants and human food chain. Thus, the main aim of this study was to evaluate the distribution of Ra-226, Th-232 and K-40 in soils and sugar cane crops in the Corumbatai river basin, São Paulo State, Brazil. The gamma spectrometry was utilized to measure the Ra-226, Th-232 and K-40 activity concentration in all samples. The soil-to-sugar cane transfer factors (TF) were quantified using the ratio between the radionuclide activity concentration in sugar cane and its activity concentration in soil. The results show that, although radionuclides incorporated in phosphate fertilizers and amendments are annually added in the sugar cane crops, if utilized in accordance with the recommended rates, their use does not lead to hazards levels in soils. The soil-to-sugar cane transfer of radionuclides occurred in the following order K-40 > Ra-226 > Th-232. Therefore, under these conditions, radionuclides intake through consumption of sugar is not hazardous to human health. (C) 2009 Elsevier Ltd. All rights reserved.

H-infinity control design for time-delay linear systems: a rational transfer function based approach

The aim of this paper is to present new results on H-infinity control synthesis for time-delay linear systems. We extend the use of a finite order LTI system, called comparison system to H-infinity analysis and design. Differently from what can be viewed as a common feature of other control design methods available in the literature to date, the one presented here treats time-delay systems control design with classical numeric routines based on Riccati equations arisen from H-infinity theory. The proposed algorithm is simple, efficient and easy to implement. Some examples illustrating state and output feedback design are solved and discussed in order to put in evidence the most relevant characteristic of the theoretical results. Moreover, a practical application involving a 3-DOF networked control system is presented.

Feasibility of resting-state microstates neurofeedback

Despite major progress, currently available treatment options for patients suffering from schizophrenia remain suboptimal. Antipsychotic medication is one such option, and is helpful in acute phases of the disease. However, antipsychotics cause significant side-effects that often require additional medication, and can even trigger the discontinuation of treatment. Taken together, along with the fact that 20-30% of patients are medication-resistant, it is clear that new medical care options should be developed for patients with schizophrenia. Besides medication, an emerging option to treat psychiatric symptoms is through the use of neurofeedback. This technique has proven efficacy for other disorders and, more importantly, has also proven to be feasible in patients with schizophrenia. One of the major advantages of this approach is that it allows for the influence of brain states that otherwise would be inaccessible; i.e. the physiological markers underlying psychotic symptoms. EEG resting-state microstates are a very interesting electrophysiological marker of schizophrenia symptoms. Precisely, a specific class of resting-state microstates, namely microstate class D, has consistently been found to show a temporal shortening in patients with schizophrenia compared to controls, and this shortening is correlated with the presence positive psychotic symptoms. Under the scope of biological psychiatry, appropriate treatment of psychotic symptoms can be expected to modify the underlying physiological markers accompanying behavioral manifestations of a disease. We reason that if abnormal temporal parameters of resting-state microstates seem to be related to positive symptoms in schizophrenia, regulating this EEG feature might be helpful as a treatment for patients. The goal of this thesis was to prove the feasibility of microstate class D contribution self-regulation via neurofeedback. Given that no other study has attempted to regulate microstates via neurofeedback, we first tested its feasibility in a population of healthy subjects. In the first paper we describe the methodological characteristics of the neurofeedback protocol and its implementation. Neurofeedback performance was assessed by means of linear mixed effects modeling, which provided a complete profile of the neurofeedback’s training response within and between-subjects. The protocol included 20 training sessions, and each session contained three conditions: baseline (resting-state) and two active conditions: training (auditory feedback upon self-regulation performance) and transfer (self-regulation with no feedback). With linear modeling we obtained performance indices for each of them as follows: baseline carryover (baseline increments time-dependent) and learning and aptitude for each of the active conditions. Learning refers to the increase/decrease of the microstate class D contribution, time-dependent during each active condition, and aptitude refers to the constant difference of the microstate class D contribution between each active condition and baseline independent of time. The indices provided are discussed in terms of tailoring neurofeedback treatment to individual profiles so that it can be applied in future studies or clinical practice. In our sample of participants, neurofeedback proved feasible, as all participants at least showed positive results in one of the aforementioned learning indices. Furthermore, between-subjects we observed that the contribution of microstate class D across-sessions increased by 0.42% during baseline, 1.93% during training trials, and 1.83% during transfer. This range is expected to be effective in treating psychotic symptoms in patients. In the second paper presented in this thesis, we explored the possible predictors of neurofeedback success among psychological variables measured with questionnaires. An interesting finding was the negative correlation between “motivational incongruence” and some of the neurofeedback performance indices. Even though this finding requires replication, we discuss it in terms of the interfering effects of incompatible psychological processes with neurofeedback training requirements. In the third paper, we present a meta-analysis on all available studies that have related resting-state microstate abnormalities and schizophrenia. We obtained medium effect sizes for two microstate classes, namely C and D. Combining the meta-analysis results with the fact that microstate class D abnormalities are correlated with the presence of positive symptoms in patients with schizophrenia, these results add further support for the training of this precise microstate. Overall, the results obtained in this study encourage the implementation of this protocol in a population of patients with schizophrenia. However, future studies will have to show whether patients will be able to successfully self-regulate the contribution of microstate class D and, if so, whether this regulation will have an impact on symptomatology.

Theoretical Rationalization of the Singlet–Triplet Gap in OLEDs Materials: Impact of Charge-Transfer Character

New materials for OLED applications with low singlet–triplet energy splitting have been recently synthesized in order to allow for the conversion of triplet into singlet excitons (emitting light) via a Thermally Activated Delayed Fluorescence (TADF) process, which involves excited-states with a non-negligible amount of Charge-Transfer (CT). The accurate modeling of these states with Time-Dependent Density Functional Theory (TD-DFT), the most used method so far because of the favorable trade-off between accuracy and computational cost, is however particularly challenging. We carefully address this issue here by considering materials with small (high) singlet–triplet gap acting as emitter (host) in OLEDs and by comparing the accuracy of TD-DFT and the corresponding Tamm-Dancoff Approximation (TDA), which is found to greatly reduce error bars with respect to experiments thanks to better estimates for the lowest singlet–triplet transition. Finally, we quantitatively correlate the singlet–triplet splitting values with the extent of CT, using for it a simple metric extracted from calculations with double-hybrid functionals, that might be applied in further molecular engineering studies.

AN ASSESSMENT OF FLOW REGIME MAPS AND A NUMERICAL HEAT TRANSFER CORRELATION FOR THE STRATIFIED/ANNULAR REGIME OF SHEAR-DRIVEN INTERNAL CONDENSING FLOWS

Several modern-day cooling applications require the incorporation of mini/micro-channel shear-driven flow condensers. There are several design challenges that need to be overcome in order to meet those requirements. The difficulty in developing effective design tools for shear-driven flow condensers is exacerbated due to the lack of a bridge between the physics-based modelling of condensing flows and the current, popular approach based on semi-empirical heat transfer correlations. One of the primary contributors of this disconnect is a lack of understanding caused by the fact that typical heat transfer correlations eliminate the dependence of the heat transfer coefficient on the method of cooling employed on the condenser surface when it may very well not be the case. This is in direct contrast to direct physics-based modeling approaches where the thermal boundary conditions have a direct and huge impact on the heat transfer coefficient values. Typical heat transfer correlations instead introduce vapor quality as one of the variables on which the value of the heat transfer coefficient depends. This study shows how, under certain conditions, a heat transfer correlation from direct physics-based modeling can be equivalent to typical engineering heat transfer correlations without making the same apriori assumptions. Another huge factor that raises doubts on the validity of the heat-transfer correlations is the opacity associated with the application of flow regime maps for internal condensing flows. It is well known that flow regimes influence heat transfer rates strongly. However, several heat transfer correlations ignore flow regimes entirely and present a single heat transfer correlation for all flow regimes. This is believed to be inaccurate since one would expect significant differences in the heat transfer correlations for different flow regimes. Several other studies present a heat transfer correlation for a particular flow regime - however, they ignore the method by which extents of the flow regime is established. This thesis provides a definitive answer (in the context of stratified/annular flows) to: (i) whether a heat transfer correlation can always be independent of the thermal boundary condition and represented as a function of vapor quality, and (ii) whether a heat transfer correlation can be independently obtained for a flow regime without knowing the flow regime boundary (even if the flow regime boundary is represented through a separate and independent correlation). To obtain the results required to arrive at an answer to these questions, this study uses two numerical simulation tools - the approximate but highly efficient Quasi-1D simulation tool and the exact but more expensive 2D Steady Simulation tool. Using these tools and the approximate values of flow regime transitions, a deeper understanding of the current state of knowledge in flow regime maps and heat transfer correlations in shear-driven internal condensing flows is obtained. The ideas presented here can be extended for other flow regimes of shear-driven flows as well. Analogous correlations can also be obtained for internal condensers in the gravity-driven and mixed-driven configuration.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

FY2010 Annual Report Research, Intelligent Transportation Systems, and Technology Transfer Activities, October 18, 2011

Transportation research makes a difference for Iowans and the nation. Implementation of cost effective research projects contributes to a transportation network that is safer, more efficient, and longer lasting. Working in cooperation with our partners from universities, industry, other states, and FHWA, as well as participation in the Transportation Research Board (TRB), provides benefits for every facet of the DOT. This allows us to serve our communities and the traveling public more effectively. Pooled fund projects allow leveraging of funds for higher returns on investments. In 2010, Iowa led fifteen active pooled fund studies, participated in twenty-two others, and was wrapping-up, reconciling, and closing out an additional 6 Iowa Led pooled fund studies. In addition, non-pooled fund SPR projects included approximately 20 continued, 9 new, and over a dozen reoccurring initiatives such as the technical transfer/training program. Additional research is managed and conducted by the Office of Traffic and Safety and other departments in the Iowa DOT.

When a Change in Level of Care Results in a Transfer Between Programs

This project was chosen to investigate the criteria, process, procedures and policies in place for transferring patients of the Charleston Dorchester Mental Health Center between programs due to a change in their level of care in efforts to make the process more consistent and prevent or reduce gaps in care for patients.

Deep learning based style transfer for low altitude aerial imagery

Unmanned Aerial Vehicle (UAVs) equipped with cameras have been fast deployed to a wide range of applications, such as smart cities, agriculture or search and rescue applications. Even though UAV datasets exist, the amount of open and quality UAV datasets is limited. So far, we want to overcome this lack of high quality annotation data by developing a simulation framework for a parametric generation of synthetic data. The framework accepts input via a serializable format. The input specifies which environment preset is used, the objects to be placed in the environment along with their position and orientation as well as additional information such as object color and size. The result is an environment that is able to produce UAV typical data: RGB image from the UAVs camera, altitude, roll, pitch and yawn of the UAV. Beyond the image generation process, we improve the resulting image data photorealism by using Synthetic-To-Real transfer learning methods. Transfer learning focuses on storing knowledge gained while solving one problem and applying it to a different - although related - problem. This approach has been widely researched in other affine fields and results demonstrate it to be an interesing area to investigate. Since simulated images are easy to create and synthetic-to-real translation has shown good quality results, we are able to generate pseudo-realistic images. Furthermore, object labels are inherently given, so we are capable of extending the already existing UAV datasets with realistic quality images and high resolution meta-data. During the development of this thesis we have been able to produce a result of 68.4% on UAVid. This can be considered a new state-of-art result on this dataset.