Design-based random permutation models with auxiliary information

We extend the random permutation model to obtain the best linear unbiased estimator of a finite population mean accounting for auxiliary variables under simple random sampling without replacement (SRS) or stratified SRS. The proposed method provides a systematic design-based justification for well-known results involving common estimators derived under minimal assumptions that do not require specification of a functional relationship between the response and the auxiliary variables.

Employing Distances in Design-based Spatial Estimation

In the last couple of decades we assisted to a reappraisal of spatial design-based techniques. Usually the spatial information regarding the spatial location of the individuals of a population has been used to develop efficient sampling designs. This thesis aims at offering a new technique for both inference on individual values and global population values able to employ the spatial information available before sampling at estimation level by rewriting a deterministic interpolator under a design-based framework. The achieved point estimator of the individual values is treated both in the case of finite spatial populations and continuous spatial domains, while the theory on the estimator of the population global value covers the finite population case only. A fairly broad simulation study compares the results of the point estimator with the simple random sampling without replacement estimator in predictive form and the kriging, which is the benchmark technique for inference on spatial data. The Monte Carlo experiment is carried out on populations generated according to different superpopulation methods in order to manage different aspects of the spatial structure. The simulation outcomes point out that the proposed point estimator has almost the same behaviour as the kriging predictor regardless of the parameters adopted for generating the populations, especially for low sampling fractions. Moreover, the use of the spatial information improves substantially design-based spatial inference on individual values.

Process design based on CO 2-expanded liquids as solvents

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Extracting Urban Food Potential: design-based methods for digital and bodily cartography

Sweden’s recent report on Urban Sustainable Development calls out a missing link between the urban design process and citizens. This paper investigates if engaging citizens as design agents by providing a platform for alternate participation can bridge this gap, through the transfer of spatial agency and new modes of critical cartography. To assess whether this is the case, the approaches are applied to Stockholm’s urban agriculture movement in a staged intervention. The aim of the intervention was to engage citizens in locating existing and potential places for growing food and in gathering information from these sites to inform design in urban agriculture. The design-based methodologies incorporated digital and bodily interfaces for this cartography to take place. The Urban CoMapper, a smartphone digital app, captured real-time perspectives through crowd-sourced mapping. In the bodily cartography, participant’s used their bodies to trace the site and reveal their sensorial perceptions. The data gathered from these approaches gave way to a mode of artistic research for exploring urban agriculture, along with inviting artists to be engaged in the dialogues. In sum, results showed that a combination of digital and bodily approaches was necessary for a critical cartography if we want to engage citizens holistically into the urban design process as spatial agents informing urban policy. Such methodologies formed a reflective interrogation and encouraged a new intimacy with nature, in this instance, one that can transform our urban conduct by questioning our eating habits: where we get our food from and how we eat it seasonally.

Advances in drug design based on the amino acid approach: Taurine analogues for the treatment of CNS diseases

Amino acids are well known to be an important class of compounds for the maintenance of body homeostasis and their deficit, even for the polar neuroactive aminoacids, can be controlled by supplementation. However, for the amino acid taurine (2-aminoethanesulfonic acid) this is not true. Due its special physicochemical properties, taurine is unable to cross the blood-brain barrier. In addition of injured taurine transport systems under pathological conditions, CNS supplementation of taurine is almost null. Taurine is a potent antioxidant and anti-inflammatory semi-essential amino acid extensively involved in neurological activities, acting as neurotrophic factor, binding to GABA A/glycine receptors and blocking the excitotoxicity glutamate-induced pathway leading to be a neuroprotective effect and neuromodulation. Taurine deficits have been implicated in several CNS diseases, such as Alzheimer's, Parkinson's, epilepsy and in the damage of retinal neurons. This review describes the CNS physiological functions of taurine and the development of new derivatives based on its structure useful in CNS disease treatment.&; 2012 by the authors; licensee MDPI, Basel, Switzerland.

Development of Cationic Solid Lipid Nanoparticles with Factorial Design-Based Studies for Topical Administration of Doxorubicin

Topical chemotherapy using doxorubicin, a powerful anticancer drug, can be used as an alternative with reduced systemic toxicity when treating skin cancer. The aim of the present work was to use factorial design-based studies to develop cationic solid lipid nanoparticles containing doxorubicin; further investigations into the influence of these particles on the drug's cytotoxicity and cellular uptake in B16F10 murine melanoma cells were performed. A 3(2) full factorial design was applied for two different lipid phases; one phase used stearic acid and the other used a 1:2 mixture of stearic acid and glyceryl behenate. The two factors investigated included the ratio between the lipid and the water phase and the ratio between the surfactant (poloxamer) and the co-surfactant (cetylpyridinium chloride). It was observed that the studied factors did not affect the mean diameter or the polydispersity of the obtained nanoparticles; however, they did significantly affect the zeta potential values. Optimised formulations with particle sizes ranging from 251 to 306 nm and positive zeta potentials were selected for doxorubicin incorporation. High entrapment efficiencies were achieved (97%) in formulations with higher amounts of stearic acid, suggesting that cationic charges on doxorubicin molecules may interact with the negative charges in stearic acid. Melanoma culture cell experiments showed that cationic solid lipid nanoparticles without drug were not cytotoxic to melanoma cells. The encapsulation of doxorubicin significantly increased cytotoxicity, indicating the potential of these nanoparticles for the treatment of skin cancer.

Design-based stereology to quantify structural properties of artificial and natural snow using thin sections

The quantification of the structural properties of snow is traditionally based on model-based stereology. Model-based stereology requires assumptions about the shape of the investigated structure. Here, we show how the density, specific surface area, and grain boundary area can be measured using a design-based method, where no assumptions about structural properties are necessary. The stereological results were also compared to X-ray tomography to control the accuracy of the method. The specific surface area calculated with the stereological method was 19.8 ± 12.3% smaller than with X-ray tomography. For the density, the stereological method gave results that were 11.7 ± 12.1% larger than X-ray tomography. The statistical analysis of the estimates confirmed that the stereological method and the sampling used are accurate. This stereological method was successfully tested on artificially produced ice beads but also on several snow types. Combining stereology and polarisation microscopy provides a good estimate of grain boundary areas in ice beads and in natural snow, with some limitatio

Design-based stereology: Planning, volumetry and sampling are crucial steps for a successful study

Quantitative data obtained by means of design-based stereology can add valuable information to studies performed on a diversity of organs, in particular when correlated to functional/physiological and biochemical data. Design-based stereology is based on a sound statistical background and can be used to generate accurate data which are in line with principles of good laboratory practice. In addition, by adjusting the study design an appropriate precision can be achieved to find relevant differences between groups. For the success of the stereological assessment detailed planning is necessary. In this review we focus on common pitfalls encountered during stereological assessment. An exemplary workflow is included, and based on authentic examples, we illustrate a number of sampling principles which can be implemented to obtain properly sampled tissue blocks for various purposes.

Provisos for classic linear oscillator design methods. New linear oscillator design based on the NDF/RRT

In this paper, the classic oscillator design methods are reviewed, and their strengths and weaknesses are shown. Provisos for avoiding the misuse of classic methods are also proposed. If the required provisos are satisfied, the solutions provided by the classic methods (oscillator start-up linear approximation) will be correct. The provisos verification needs to use the NDF (Network Determinant Function). The use of the NDF or the most suitable RRT (Return Relation Transponse), which is directly related to the NDF, as a tool to analyze oscillators leads to a new oscillator design method. The RRT is the "true" loop-gain of oscillators. The use of the new method is demonstrated with examples. Finally, a comparison of NDF/RRT results with the HB (Harmonic Balance) simulation and practical implementation measurements prove the universal use of the new methods.

Self-Organizing Architectural design based on Morphogenetic Programming.

In this paper, we present our research into self-organizing building algorithms. This idea of self-organization of animal/plants behaviour interests researchers to explore the mechanisms required for this emergent phenomena and try to apply them in other domains. We were able to implement a typical construction algorithm in a 3D simulation environment and reproduce the results of previous research in the area. LSystems, morphogenetic programming and wasp nest building are explained in order to understand self-organizing models. We proposed Grammatical swarm as a good tool to optimize building structures.

A Dialogue between Treatment Integrity Research and Design-Based Implementation Research

Thesis (Master's)--University of Washington, 2016-06

Socio-Historical Factors Mediating Collaborative Teaching and Learning: A Design-Based Investigation and Intervention

Thesis (Ph.D.)--University of Washington, 2016-06

Developing of Distributed Virtual Laboratories for Smart Sensor System Design Based on Multi-Dimensional Access Method

In the article it is considered preconditions and main principles of creation of virtual laboratories for computer-aided design, as tools for interdisciplinary researches. Virtual laboratory, what are offered, is worth to be used on the stage of the requirements specification or EFT-stage, because it gives the possibility of fast estimating of the project realization, certain characteristics and, as a result, expected benefit of its applications. Using of these technologies already increase automation level of design stages of new devices for different purposes. Proposed computer technology gives possibility to specialists from such scientific fields, as chemistry, biology, biochemistry, physics etc, to check possibility of device creating on the basis of developed sensors. It lets to reduce terms and costs of designing of computer devices and systems on the early stages of designing, for example on the stage of requirements specification or EFT-stage. An important feature of this project is using the advanced multi-dimensional access method for organizing the information base of the Virtual laboratory.

Small-area estimation with spatial similarity

A class of composite estimators of small area quantities that exploit spatial (distancerelated)similarity is derived. It is based on a distribution-free model for the areas, but theestimators are aimed to have optimal design-based properties. Composition is applied alsoto estimate some of the global parameters on which the small area estimators depend.It is shown that the commonly adopted assumption of random effects is not necessaryfor exploiting the similarity of the districts (borrowing strength across the districts). Themethods are applied in the estimation of the mean household sizes and the proportions ofsingle-member households in the counties (comarcas) of Catalonia. The simplest version ofthe estimators is more efficient than the established alternatives, even though the extentof spatial similarity is quite modest.