Urinary tract infection in full-term newborn infants: risk factor analysis

OBJECTIVE: To analyze the correlation of risk factors to the occurrence of urinary tract infection in full-term newborn infants. PATIENTS AND METHODS: Retrospective study (1997) including full-term infants having a positive urine culture by bag specimen. Urine collection was based on: fever, weight loss > 10% of birth weight, nonspecific symptoms (feeding intolerance, failure to thrive, hypoactivity, debilitate suction, irritability), or renal and urinary tract malformations. In these cases, another urine culture by suprapubic bladder aspiration was collected to confirm the diagnosis. To compare and validate the risk factors in each group, the selected cases were divided into two groups: Group I - positive urine culture by bag specimen collection and negative urine culture by suprapubic aspiration, and Group II - positive urine culture by bag specimen collection and positive urine culture by suprapubic aspiration . RESULTS: Sixty one infants were studied, Group I, n = 42 (68.9%) and Group II, n = 19 (31.1%). The selected risk factors (associated infectious diseases, use of broad-spectrum antibiotics, renal and urinary tract malformations, mechanical ventilation, parenteral nutrition and intravascular catheter) were more frequent in Group II (p<0.05). Through relative risk analysis, risk factors were, in decreasing importance: parenteral nutrition, intravascular catheter, associated infectious diseases, use of broad-spectrum antibiotics, mechanical ventilation, and renal and urinary tract malformations. CONCLUSION: The results showed that parenteral nutrition, intravascular catheter, and associated infectious diseases contributed to increase the frequency of neonatal urinary tract infection, and in the presence of more than one risk factor, the occurrence of urinary tract infection rose up to 11 times.

Minimal computation structures for visual information applications based on printed electronics

In the early nineties, Mark Weiser wrote a series of seminal papers that introduced the concept of Ubiquitous Computing. According to Weiser, computers require too much attention from the user, drawing his focus from the tasks at hand. Instead of being the centre of attention, computers should be so natural that they would vanish into the human environment. Computers become not only truly pervasive but also effectively invisible and unobtrusive to the user. This requires not only for smaller, cheaper and low power consumption computers, but also for equally convenient display solutions that can be harmoniously integrated into our surroundings. With the advent of Printed Electronics, new ways to link the physical and the digital worlds became available. By combining common printing techniques such as inkjet printing with electro-optical functional inks, it is starting to be possible not only to mass-produce extremely thin, flexible and cost effective electronic circuits but also to introduce electronic functionalities into products where it was previously unavailable. Indeed, Printed Electronics is enabling the creation of novel sensing and display elements for interactive devices, free of form factor. At the same time, the rise in the availability and affordability of digital fabrication technologies, namely of 3D printers, to the average consumer is fostering a new industrial (digital) revolution and the democratisation of innovation. Nowadays, end-users are already able to custom design and manufacture on demand their own physical products, according to their own needs. In the future, they will be able to fabricate interactive digital devices with user-specific form and functionality from the comfort of their homes. This thesis explores how task-specific, low computation, interactive devices capable of presenting dynamic visual information can be created using Printed Electronics technologies, whilst following an approach based on the ideals behind Personal Fabrication. Focus is given on the use of printed electrochromic displays as a medium for delivering dynamic digital information. According to the architecture of the displays, several approaches are highlighted and categorised. Furthermore, a pictorial computation model based on extended cellular automata principles is used to programme dynamic simulation models into matrix-based electrochromic displays. Envisaged applications include the modelling of physical, chemical, biological, and environmental phenomena.

Optimization of wastewater quality in the Sines refinery

In order to address and resolve the wastewater contamination problem of the Sines refinery with the main objective of optimizing the quality of this stream and reducing the costs charged to the refinery, a dynamic mass balance was developed nd implemented for ammonia and polar oil and grease (O&G) contamination in the wastewater circuit. The inadequate routing of sour gas from the sour water stripping unit and the kerosene caustic washing unit, were identified respectively as the major source of ammonia and polar substances present in the industrial wastewater effluent. For the O&G content, a predictive model was developed for the kerosene caustic washing unit, following the Projection to Latent Structures (PLS) approach. Comparison between analytical data for ammonia and polar O&G concentrations in refinery wastewater originating from the Dissolved Air Flotation (DAF) effluent and the model predictions of the dynamic mass balance calculations are in a very good agreement and highlights the dominant impact of the identified streams for the wastewater contamination levels. The ammonia contamination problem was solved by rerouting the sour gas through an existing clogged line with ammonia salts due to a non-insulated line section, while for the O&G a dynamic mass balance was implemented as an online tool, which allows for prevision of possible contamination situations and taking the required preventive actions, and can also serve as a basis for establishing relationships between the O&G contamination in the refinery wastewater with the properties of the refined crude oils and the process operating conditions. The PLS model developed could be of great asset in both optimizing the existing and designing new refinery wastewater treatment units or reuse schemes. In order to find a possible treatment solution for the spent caustic problem, an on-site pilot plant experiments for NaOH recovery from the refinery kerosene caustic washing unit effluent using an alkaline-resistant nanofiltration (NF) polymeric membrane were performed in order to evaluate its applicability for treating these highly alkaline and contaminated streams. For a constant operating pressure and temperature and adequate operating conditions, 99.9% of oil and grease rejection and 97.7% of chemical oxygen demand (COD) rejection were observed. No noticeable membrane fouling or flux decrease were registered until a volume concentration factor of 3. These results allow for NF permeate reuse instead of fresh caustic and for significant reduction of the wastewater contamination, which can result in savings of 1.5 M€ per year at the current prices for the largest Portuguese oil refinery. The capital investments needed for implementation of the required NF membrane system are less than 10% of those associated with the traditional wet air oxidation solution of the spent caustic problem. The operating costs are very similar, but can be less than half if reusing the NF concentrate in refinery pH control applications. The payback period was estimated to be 1.1 years. Overall, the pilot plant experimental results obtained and the process economic evaluation data indicate a very competitive solution through the proposed NF treatment process, which represents a highly promising alternative to conventional and existing spent caustic treatment units.

Immunoglobulin E-rheumatoid factor in juvenile rheumatoid arthritis

OBJECTIVES: To determine the presence of immunoglobulin E-rheumatoid factor in patients with juvenile rheumatoid arthritis and to correlate it with clinical and laboratory parameters. METHODS: A multicenter prospective study was carried out from January 1993 to January 1999 with the enrollment of 3 centers of pediatric rheumatology. Ninety-one children with juvenile rheumatoid arthritis diagnosed according to the American College of Rheumatology criteria were studied: 38 (42%) with systemic, 28 (31%) with pauciarticular, and 25 (27%) with polyarticular onset. Ages ranged from 2.1 years to 22.6 years (mean 10.5 ± 4.7), with 59 (65%) girls. The control group consisted of 45 healthy children. The detection of immunoglobulin E-rheumatoid factor was carried out utilizing an enzyme-linked immunosorbent assay. Associations of immunoglobulin E-rheumatoid factor with immunoglobulin M-rheumatoid factor (latex agglutination test), total serum immunoglobulin E, erythrocyte sedimentation rate, antinuclear antibody, and functional and radiological classes III or IV were analyzed. RESULTS: Positive immunoglobulin E-rheumatoid factor was found in 15 (16.5%) of the 91 children with juvenile rheumatoid arthritis: 7 (18.5%) with systemic, 5 (18%) with pauciarticular, and 3 (12%) with polyarticular onset. A significant correlation was observed between immunoglobulin E-rheumatoid factor and total serum immunoglobulin E in the juvenile rheumatoid arthritis patients. No correlation was found between immunoglobulin E-rheumatoid factor and positive latex agglutination slide test, erythrocyte sedimentation rate, antinuclear antibody, or the functional and radiological classes III or IV in any disease onset group. In 4 out of 45 control children (8.9%), immunoglobulin E-rheumatoid factor was positive but with no correlation with total serum immunoglobulin E levels. CONCLUSIONS: Immunoglobulin E-rheumatoid factor could be detected in 16.5% of juvenile rheumatoid arthritis patients, particularly in those with high levels of total serum immunoglobulin E, and immunoglobulin E-rheumatoid factor appears not to be associated with disease activity or severity.

Adrenocortical tumors: results of treatment and study of Weiss's score as a prognostic factor

PURPOSE: The differential diagnosis between benign and malignant adrenal cortical tumors circumscribed to the gland is controversial. One hundred and seven patients with adrenal cortex tumors (excluding those with primary hyperaldosteronism) were studied to assess the 5-year survival rate of adults, children, patients stratified by pathological stage, and patients stratified according to Weiss's score of <3 or >3. METHODS: The patients were evaluated both clinically and biochemically. One hundred and five patients underwent surgery and were classified pathologically as stages I, II, III, or IV. The tumors were weighed, measured, and classified according to Weiss's criteria and divided into 2 groups: <3 and >3. RESULTS: After 5 years, the survival rate was 77.5% for the whole group, 74.61% for the adults, 84.3% for the children, 100% for stage I, 83.9% for stage II, 33% for stage III, and 11.7% for stage IV groups. Additionally, after 5 years, 100% of the patients with tumors with Weiss's score <3 were alive compared to 61.65% of those with Weiss's score >3. The average weights of the tumors of score <3 and >3 were 23.38 g ± 41.36 g and 376.3 ± 538.76 g, respectively, which is a statistically significant difference. The average sizes of tumors of Weiss's score <3 and >3 were 3.67 ± 2.2 cm and 9.64 ± 5.8 cm, respectively, which is also a statistically significant difference. CONCLUSIONS: Weiss's score may be a good prognostic factor for tumors of the adrenal cortex. Additionally, there was a statistically significant difference between the average weight and size of tumors with benign behavior (Weiss's score <3) and those with malignant behavior (Weiss's score >3).

Understanding multi-asset factor models: Factor exposure interpretation

Field lab: Business project

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Dynamic group formation in mobile computer supported collaborative learning environment

Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

High strain rate constitutive modeling forhistorical structures subjected to blast loading

Doctoral Thesis Civil Engineering

Measurements of the nuclear modification factor for jets in Pb+Pb collisions at sNN =2.76TeV with the ATLAS detector

Measurements of inclusive jet production are performed in pp and Pb+Pb collisions at sNN−−−√=2.76 TeV with the ATLAS detector at the LHC, corresponding to integrated luminosities of 4.0 pb−1 and 0.14 nb−1 , respectively. The jets are identified with the anti-kt algorithm with R=0.4, and the spectra are measured over the kinematic range of jet transverse momentum 32factor, RAA, is evaluated and jets are found to be suppressed by approximately a factor of two in central collisions compared to pp collisions. The RAA shows a slight increase with pT and no significant variation with rapidity.

Jute/polypropylene composites: Effect of enzymatic modification on thermo-mechanical and dynamic mechanical properties

In this study, a high-performance composite was prepared from jute fabrics and polypropylene (PP). In order to improve the compatibility of the polar fibers and the non-polar matrix, alkyl gallates with different hydrophobic groups were enzymatically grafted onto jute fabric by laccase to increase the surface hydrophobicity of the fiber. The grafting products were characterized by FTIR. The results of contact angle and wetting time showed that the hydrophobicity of the jute fabrics was improved after the surface modification. The effect of the enzymatic graft modification on the properties of the jute/PP composites was evaluated. Results showed that after the modification, tensile and dynamic mechanical properties of composites improved, and water absorption and thickness swelling clearly decreased. However, tensile properties drastically decreased after a long period of water immersion. The thermal behavior of the composites was evaluated by TGA/DTG. The fiber-matrix morphology in the modified jute/PP composites was confirmed by SEM analysis of the tensile fractured specimens.

Dynamic piezoelectric stimulation enhances osteogenic differentiation of human adipose stem cells

This work reports on the influence of the substrate polarization of electroactive β-PVDF on human adipose stem cells (hASCs) differentiation under static and dynamic conditions. hASCs were cultured on different β-PVDF surfaces (non-poled and “poled -”) adsorbed with fibronectin and osteogenic differentiation was determined using a quantitative alkaline phosphatase assay. “Poled -” β-PVDF samples promote higher osteogenic differentiation, which is even higher under dynamic conditions. It is thus demonstrated that electroactive membranes can provide the necessary electromechanical stimuli for the differentiation of specific cells and therefore will support the design of suitable tissue engineering strategies, such as bone tissue engineering.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

A firefly dynamic penalty approach for solving engineering design problems

Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

Mechanical ventilation for the treatment of severe excessive dynamic airway collapse

[Excerpt] We read with interest the case report by Ismael et al1 describing a patient with Sjo¨gren’s syndrome and cystic lung disease who could not be weaned from a ventilator due to severe central excessive dynamic airway collapse (EDAC) of the lower part of the trachea and proximal bronchi. EDAC corresponds to the expiratory bulging of the tracheobronchial wall without known airway structural abnormalities, leading to a decrease of at least 50% in internal diameter.2 It is a rare and underdiagnosed entity, commonly confused with other respiratory diseases such as asthma and COPD. Although noninvasive procedures such as cervicothoracic computed tomography scan on inspiration and expiration may suggest the disorder, the accepted standard method for diagnosis is bronchoscopy.3-7 (...).