Monitorization of alveolar deposited surface area of nanoparticles and ultrafine particles in different environments

Nanotechnology is an important emerging industry with a projected annual market of around one trillion dollars by 2015. It involves the control of atoms and molecules to create new materials with a variety of useful functions. Although there are advantages on the utilization of these nano-scale materials, questions related with its impact over the environment and human health must be addressed too, so that potential risks can be limited at early stages of development. At this time, occupational health risks associated with manufacturing and use of nanoparticles are not yet clearly understood. However, workers may be exposed to nanoparticles through inhalation at levels that can greatly exceed ambient concentrations. Current workplace exposure limits are based on particle mass, but this criteria could not be adequate in this case as nanoparticles are characterized by very large surface area, which has been pointed out as the distinctive characteristic that could even turn out an inert substance into another substance exhibiting very different interactions with biological fluids and cells. Therefore, it seems that, when assessing human exposure based on the mass concentration of particles, which is widely adopted for particles over 1 μm, would not work in this particular case. In fact, nanoparticles have far more surface area for the equivalent mass of larger particles, which increases the chance they may react with body tissues. Thus, it has been claimed that surface area should be used for nanoparticle exposure and dosing. As a result, assessing exposure based on the measurement of particle surface area is of increasing interest. It is well known that lung deposition is the most efficient way for airborne particles to enter the body and cause adverse health effects. If nanoparticles can deposit in the lung and remain there, have an active surface chemistry and interact with the body, then, there is potential for exposure. It was showed that surface area plays an important role in the toxicity of nanoparticles and this is the metric that best correlates with particle-induced adverse health effects. The potential for adverse health effects seems to be directly proportional to particle surface area. The objective of the study is to identify and validate methods and tools for measuring nanoparticles during production, manipulation and use of nanomaterials.

Ecophysiology of Ruditapes decussatus

The physiological responses of the clam R. decussatus from the Ria Formosa, southern Portugal, were examined in relation to normoxia, hypoxia (11, 6, 3 and 1.2 kPa) and anoxia; acute elevation of temperature (at 20, 27 and 32 °C), and its effect on the resistance to air exposure (at 20, 28 and 35 °C); current velocity (0.6, 3, 8 17, 24 and 36 cm. s-1) and turbidity (10, 100 and 300 mg. l-1 dry weight of particulate matter), and the efficiency of this species in retaining particles of different size (at 10 and 100 mg. l-1); and to copper contamination considering both short-term acute exposure to high levels (0.1-10 mg Cu. l-1) and chronic environmental levels (0.01 mg Cu. l-1). Clearance rates, respiration rates, absorption efficiency and excretion rates were assessed through the physiological energetics in terms of the energy budget and scope for growth (SFG). Stress independent respiration rates (R) and clearance rates (CR) were observed in relation to hypoxia down to 12 kPa and 6 kPa, respectively. Anoxic rates were 3.6 % of normoxic rates. Scope for growth was greatly reduced under extreme hypoxia (14 % of SFG in normoxia). Respiration rate was temperature independent in the range 20-32 °C but the decline in clearance rate resulted in negative SFG at 32 °C. Gaping during air exposure and the maintenance of faster aerobic metabolism led to 100 % mortality in 20 hours at 35 °C, 4 days at 28 °C and 5 days at 20 °C. Low current velocities (≤ 8 cm. s-1) supported high clearance rates. Shear stresses ≥ 0.9 Pa induced sediment movement and disturbed the feeding processes resulting in decreased clearance rates (at 36 cm. s-1, is 10 % of maximum CR). The observed ability of jetting out depleted water at a different level than the one of the inhalant current results is an important adaptation of clams to the slow currents of sheltered environments. Ingestion at high seston concentrations (> 100 mg. l-1) is controled by reducing the amount filtered, lowering CR (to 30 % of CR at low seston loads) and producing pseudofeces. Observed efficient retention of particles (70-100 %) in the range 3 to 8 μm is beneficial when algal cells are diluted by fine silt particles as it is likely to occur in the clams natural environment. R. decussatus in the short term escaped the exposure to copper by valve closure and therefore acute tests are not applicable to adult clams of this species. At environmental levels chronic exposure to copper did not induce lethal effects during the exposure period (20 days), but scope for growth was reduced to c. 30 %, indicating sustained impairment of physiological functions. The sensitivity of the physiological energetics and the integrated scope for growth measurement in assessing stress effects caused by natural environmental factors was highlighted.

Development of procedures for the simulation of atmospheric flows over complex terrain, using OpenFOAM

The main purpose of this work was the development of procedures for the simulation of atmospheric ows over complex terrain, using OpenFOAM. For this aim, tools and procedures were developed apart from this code for the preprocessing and data extraction, which were thereafter applied in the simulation of a real case. For the generation of the computational domain, a systematic method able to translate the terrain elevation model to a native OpenFOAM format (blockMeshDict) was developed. The outcome was a structured mesh, in which the user has the ability to de ne the number of control volumes and its dimensions. With this procedure, the di culties of case set up and the high computation computational e ort reported in literature associated to the use of snappyHexMesh, the OpenFOAM resource explored until then for the accomplishment of this task, were considered to be overwhelmed. Developed procedures for the generation of boundary conditions allowed for the automatic creation of idealized inlet vertical pro les, de nition of wall functions boundary conditions and the calculation of internal eld rst guesses for the iterative solution process, having as input experimental data supplied by the user. The applicability of the generated boundary conditions was limited to the simulation of turbulent, steady-state, incompressible and neutrally strati ed atmospheric ows, always recurring to RaNS (Reynolds-averaged Navier-Stokes) models. For the modelling of terrain roughness, the developed procedure allowed to the user the de nition of idealized conditions, like an uniform aerodynamic roughness length or making its value variable as a function of topography characteristic values, or the using of real site data, and it was complemented by the development of techniques for the visual inspection of generated roughness maps. The absence and the non inclusion of a forest canopy model limited the applicability of this procedure to low aerodynamic roughness lengths. The developed tools and procedures were then applied in the simulation of a neutrally strati ed atmospheric ow over the Askervein hill. In the performed simulations was evaluated the solution sensibility to di erent convection schemes, mesh dimensions, ground roughness and formulations of the k - ε and k - ω models. When compared to experimental data, calculated values showed a good agreement of speed-up in hill top and lee side, with a relative error of less than 10% at a height of 10 m above ground level. Turbulent kinetic energy was considered to be well simulated in the hill windward and hill top, and grossly predicted in the lee side, where a zone of ow separation was also identi ed. Despite the need of more work to evaluate the importance of the downstream recirculation zone in the quality of gathered results, the agreement between the calculated and experimental values and the OpenFOAM sensibility to the tested parameters were considered to be generally in line with the simulations presented in the reviewed bibliographic sources.

Invited review: Models for the optimization of regional wastewater treatment systems

European Journal of Operational Research, nº 73 (1994)

Development of new methodologies in sample treatment for proteomics workflow based on enzymatic probe sonication technology and mass spectrometry

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia, for the degree of Doctor of Philosophy in Biochemistry

Robot Manipulator Systems: Analysis and Control

Manipulator systems are rather complex and highly nonlinear which makes difficult their analysis and control. Classic system theory is veil known, however it is inadequate in the presence of strong nonlinear dynamics. Nonlinear controllers produce good results [1] and work has been done e. g. relating the manipulator nonlinear dynamics with frequency response [2–5]. Nevertheless, given the complexity of the problem, systematic methods which permit to draw conclusions about stability, imperfect modelling effects, compensation requirements, etc. are still lacking. In section 2 we start by analysing the variation of the poles and zeros of the descriptive transfer functions of a robot manipulator in order to motivate the development of more robust (and computationally efficient) control algorithms. Based on this analysis a new multirate controller which is an improvement of the well known “computed torque controller” [6] is announced in section 3. Some research in this area was done by Neuman [7,8] showing tbat better robustness is possible if the basic controller structure is modified. The present study stems from those ideas, and attempts to give a systematic treatment, which results in easy to use standard engineering tools. Finally, in section 4 conclusions are presented.

Nurses' training on dealing with alcohol and drug abuse: a question of necessity

The purpose of this article is to present a brief review on the need for changes in nurses' undergraduate education concerning alcohol and drugs. Specialized literature makes it clear that nurses have difficulties giving care to psychoactive substance users as part of their functions in the various health care sites. This may be associated with a deficiency in formal education. In the face of the social importance concerning these related questions in the scope of research, care, and education, we made an attempt at deepening the study on this theme, which could contribute to changes in practice, care, and undergraduate nursing education.

Modulation of the secretome of hBMSCs by tailoring the macromolecular gradient in hydrogels to generate tissue-to-tissue interfaces

Tissue-to-tissue interfaces are commonly present in all tissues exhibiting structural, biological and chemical gradients serving a wide range of physiological functions. These interfaces are responsible for mediation of load transfer between two adjacent tissues. They are also important structures in sustaining the cellular communications to retain tissueâ s functional integration and homeostasis. [1] All cells have the capacity to sense and respond to physical and chemical stimulus and when cultured in three-dimensional (3D) environments they tend to perform their function better than in two-dimensional (2D) environments. Spatial and temporal 3D gradient hydrogels better resemble the natural environment of cells in mimicking their extracellular matrix. [2] In this study we hypothesize that differential functional properties can be engineered by modulation of macromolecule gradients in a cell seeded threedimensional hydrogel system. Specifically, differential paracrine secretory profiles can be engineered using human Bone Marrow Stem Cells (hBMSCâ s). Hence, the specific objectives of this study are to: assemble the macromolecular gradient hydrogels to evaluate the suitablity for hBMSCâ s encapsulation by cellular viability and biofunctionality by assessing the paracrine secretion of hBMSCâ s over time. The gradient hydrogels solutions were prepared by blend of macromolecules in one solution such as hyaluronic (HA) acid and collagen (Col) at different ratios. The gradient hydrogels were fabricated into cylindrical silicon moulds with higher ratio solutions assembled at the bottom of the mould and adding the two solutions consecutively on top of each other. The labelling of the macromolecules was performed to confirm the gradient through fluorescence microscopy. Additionally, AFM was conducted to assess the gradient hydrogels stiffness. Gradient hydrogels characterization was performed by HA and Col degradation assay, degree of crosslinking and stability. hBMSCâ s at P3 were encapsulated into each batch solution at 106 cells/ml solution and gradient hydrogels were produced as previously described. The hBMSCâ s were observed under confocal microscopy to assess viability by Live/Dead® staining. Cellular behaviour concerning proliferation and matrix deposition was also performed. Secretory cytokine measurement for pro-inflammatory and angiogenesis factors was carried out using ELISA. At genomic level, qPCR was carried out. The 3D gradient hydrogels platform made of different macromolecules showed to be a suitable environment for hBMSCâ s. The hBMSCâ s gradient hydrogels supported high cell survival and exhibited biofunctionality. Besides, the 3D gradient hydrogels demonstrated differentially secretion of pro-inflammatory and angiogenic factors by the encapsulated hBMSCâ s. References: 1. Mikos, AG. et al., Engineering complex tissues. Tissue Engineering 12,3307, 2006 2. Phillips, JE. et al., Proc Natl Acad Sci USA, 26:12170-5, 2008

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.

Cognitive processes affect the gait of subjects with Parkinson’s and Alzheimer’s disease in dual tasks

Objective To investigate the relation between gait parameters and cognitive impairments in subjects with Parkinson’s disease (PD) and Alzheimer’s disease (AD) during the performance of dual tasks. Methods This was a cross-sectional study involving 126 subjects divided into three groups: Parkinson group (n = 43), Alzheimer group (n = 38), and control group (n = 45). The subjects were evaluated using the Timed Up and Go test administered with motor and cognitive distracters. Gait analyses consisted of cadence and speed measurements, with cognitive functions being assessed by the Brief Cognitive Screening Battery and the Clock Drawing Test. Statistical procedures included mixed-design analyses of variance to observe the gait patterns between groups and tasks and the linear regression model to investigate the influence of cognitive functions in this process. A 5% significant level was adopted. Results Regarding the subjects’ speed, the data show a significant difference between group vs task interaction (p = 0.009), with worse performance of subjects with PD in motor dual task and of subjects with AD in cognitive dual task. With respect to cadence, no statistical differences was seen between group vs task interaction (p = 0.105), showing low interference of the clinical conditions on such parameter. The linear regression model showed that up to 45.79%, of the variance in gait can be explained by the interference of cognitive processes. Conclusion Dual task activities affect gait pattern in subjects with PD and AD. Differences between groups reflect peculiarities of each disease and show a direct interference of cognitive processes on complex tasks.

Elicited bid functions in (a)symmetric first-price auctions

We report on a series of experiments that examine bidding behavior in first-price sealed bid auctions with symmetric and asymmetric bidders. To study the extent of strategic behavior, we use an experimental design that elicits bidders' complete bid functions in each round (auction) of the experiment. In the aggregate, behavior is consistent with the basic equilibrium predictions for risk neutral or homogenous risk averse bidders (extent of bid shading, average seller's revenues and deviations from equilibrium). However, when we look at the extent of best reply behavior and the shape of bid functions, we find that individual behavior is not in line with the received equilibrium models, although it exhibits strategic sophistication.

Increasing quasiconcave production and utility functions with diminishing returns to scale

In microeconomic analysis functions with diminishing returns to scale (DRS) have frequently been employed. Various properties of increasing quasiconcave aggregator functions with DRS are derived. Furthermore duality in the classical sense as well as of a new type is studied for such aggregator functions in production and consumer theory. In particular representation theorems for direct and indirect aggregator functions are obtained. These involve only small sets of generator functions. The study is carried out in the contemporary framework of abstract convexity and abstract concavity.

The Cuntz semigroup, the Elliott conjecture, and dimension functions on C*-Algebras

We prove that the Cuntz semigroup is recovered functorially from the Elliott invariant for a large class of C¤-algebras. In particular, our results apply to the largest class of simple C¤-algebras for which K-theoretic classification can be hoped for. This work has three significant consequences. First, it provides new conceptual insight into Elliott's classification program, proving that the usual form of the Elliott conjecture is equivalent, among Z-stable algebras, to a conjecture which is in general substantially weaker and for which there are no known counterexamples. Second and third, it resolves, for the class of algebras above, two conjectures of Blackadar and Handelman concerning the basic structure of dimension functions on C¤-algebras. We also prove in passing that the Kuntz-Pedersen semigroup is recovered functorially from the Elliott invariant for all simple unital C¤-algebras of interest.