Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.

Glia-augmented artificial neural networks: foundations and applications

Information processing in the human brain has always been considered as a source of inspiration in Artificial Intelligence; in particular, it has led researchers to develop different tools such as artificial neural networks. Recent findings in Neurophysiology provide evidence that not only neurons but also isolated and networks of astrocytes are responsible for processing information in the human brain. Artificial neural net- works (ANNs) model neuron-neuron communications. Artificial neuron-glia networks (ANGN), in addition to neuron-neuron communications, model neuron-astrocyte con- nections. In continuation of the research on ANGNs, first we propose, and evaluate a model of adaptive neuro fuzzy inference systems augmented with artificial astrocytes. Then, we propose a model of ANGNs that captures the communications of astrocytes in the brain; in this model, a network of artificial astrocytes are implemented on top of a typical neural network. The results of the implementation of both networks show that on certain combinations of parameter values specifying astrocytes and their con- nections, the new networks outperform typical neural networks. This research opens a range of possibilities for future work on designing more powerful architectures of artificial neural networks that are based on more realistic models of the human brain.

Sea organisms as a source of collagen-derived polymers for skin tissue engineering applications

Advanced therapies combating acute and chronic skin wounds are likely to be brought about using our knowledge of regenerative medicine coupled with appropriately tissue engineered skin substitutes. At the present time, there are no models of an artificial skin that completely replicate normal uninjured skin and they are usually accompanied by fibrotic reactions that result in the production of a scar. Natural biopolymers such as collagen have been a lot investigated as potential source of biomaterial for skin replacement in Tissue Engineering. Collagens are the most abundant high molecular weight proteins in both invertebrate and vertebrate organisms, including mammals, and possess mainly a structural role in connective tissues. From this, they have been elected as one of the key biological materials in tissue regeneration approaches, as skin tissue engineering. In addition, industry is constantly searching for new natural sources of collagen and upgraded methodologies for their production. The most common sources are skin and bone from bovine and porcine origin. However, these last carry high risk of bovine spongiform encephalopathy or transmissible spongiform encephalopathy and immunogenic responses. On the other hand, the increase of jellyfish has led us to consider this marine organism as potential collagen source for tissue engineering applications. In the present study, novel form of acid and pepsin soluble collagen were extracted from dried Rhopilema hispidum jellyfish species in an effort to obtain an alternative and safer collagen. We studied different methods of collagen purification (tissues and experimental procedures). The best collagen yield was obtained using pepsin extraction method (34.16 mg collagen/g of tissue). The isolated collagen was characterized by SDS-polyacrylamide gel electrophoresis and circular dichroism spectroscopy.

Degradação de paracetamol empregando tecnologia oxidativa avançada baseada em fotocatálise heterogênea usando irradiação artificial e solar

In this work, the oxidation and mineralization of paracetamol, based in an advanced oxidative process promoted by heterogeneous photocatalysis, was evaluated. The action of two photocatalysts (titanium dioxide, and a composite based on the association between titanium dioxide and zinc phthalocyanine dye) was studied. First of all, experiments in laboratory scale were performed using as radiation font a 400 W high pressure mercury lamp. The mineralization of paracetamol, promoted by both photocatalysts, was evaluated working with 4L of solution containing 10 mg L-1 of paracetamol and 100 mg L-1 of photocatalyst. To find the best experimental conditions, the influence of hydrogen peroxide concentration and pH was evaluated for the reactions. The best results for the reactions in laboratory scale was obtained using 33,00 mg L-1 of hydrogen peroxide in natural pH (6,80). Under these conditions, 100% oxidation was reached in just 40 minutes of reaction using TiO2 P25, while the mineralization was 78%. Using the composite, the mineralization was 63% in 2 hours of reaction and a oxidation of almost 100% was reached after 60 minutes. A CPC reactor (compound parabolic concentrator) was employed in the expanded work scale, using the sun as irradiation source. In this case the experiments were performed using 50 L of aqueous solution containing 10 mg L-1 of paracetamol and 100 mg L-1 of photocatalyst. The assays were done at pH 3,00 and natural pH (6,80). The used concentration of hydrogen peroxide was 33,00 mg L-1, adopted after laboratory scale studies. The reaction at pH 3,00 shows to be more advantageous, since under natural pH (6,80), the use of deionized water was necessary to prepare the solutions, probably because the deleterious action of carbonate ions, known hydroxyl radical scavengers. Using solar irradiation, the reaction mediated by the composite was more efficient when compared with the assays under laboratory scale since the composite presents the advantage of promoting a better use of visible radiation. Under these conditions, the mineralization increased from 40% to 56% under pH 3,00. At natural pH the oxidation occurred more slowly and the mineralization decreased from 56% to 50%. Thus, the use of pH 3,00 will be more interesting in real scale applications, even if it is necessary the pH correction before the discard of the treated effluent to the environment.

Mosaic image of the artificial light produced by Berlin on the night of September 11, 2010 observed from an altitude of 10,000 ft

Aerial observations of light pollution can fill an important gap between ground based surveys and nighttime satellite data. Terrestrially bound surveys are labor intensive and are generally limited to a small spatial extent, and while existing satellite data cover the whole world, they are limited to coarse resolution. This paper describes the production of a high resolution (1 m) mosaic image of the city of Berlin, Germany at night. The dataset is spatially analyzed to identify themajor sources of light pollution in the city based on urban land use data. An area-independent 'brightness factor' is introduced that allows direct comparison of the light emission from differently sized land use classes, and the percentage area with values above average brightness is calculated for each class. Using this methodology, lighting associated with streets has been found to be the dominant source of zenith directed light pollution (31.6%), although other land use classes have much higher average brightness. These results are compared with other urban light pollution quantification studies. The minimum resolution required for an analysis of this type is found to be near 10 m. Future applications of high resolution datasets such as this one could include: studies of the efficacy of light pollution mitigation measures, improved light pollution simulations, economic and energy use, the relationship between artificial light and ecological parameters (e.g. circadian rhythm, fitness, mate selection, species distributions, migration barriers and seasonal behavior), or the management of nightscapes. To encourage further scientific inquiry, the mosaic data is freely available at Pangaea.

Flow Regime Identification Methodology with Mcnp-X Code And Artificial Neural Network

This paper presents flow regimes identification methodology in multiphase system in annular, stratified and homogeneous oil-water-gas regimes. The principle is based on recognition of the pulse height distributions (PHD) from gamma-ray with supervised artificial neural network (ANN) systems. The detection geometry simulation comprises of two NaI(Tl) detectors and a dual-energy gamma-ray source. The measurement of scattered radiation enables the dual modality densitometry (DMD) measurement principle to be explored. Its basic principle is to combine the measurement of scattered and transmitted radiation in order to acquire information about the different flow regimes. The PHDs obtained by the detectors were used as input to ANN. The data sets required for training and testing the ANN were generated by the MCNP-X code from static and ideal theoretical models of multiphase systems. The ANN correctly identified the three different flow regimes for all data set evaluated. The results presented show that PHDs examined by ANN may be applied in the successfully flow regime identification.

Artificial Neural Network and Neutron Aplication in a Volume Fraction Calculation in Annular and Stratified Multiphase System

Multiphase flows, type oil–water-gas are very common among different industrial activities, such as chemical industries and petroleum extraction, and its measurements show some difficulties to be taken. Precisely determining the volume fraction of each one of the elements that composes a multiphase flow is very important in chemical plants and petroleum industries. This work presents a methodology able to determine volume fraction on Annular and Stratified multiphase flow system with the use of neutrons and artificial intelligence, using the principles of transmission/scattering of fast neutrons from a 241Am-Be source and measurements of point flow that are influenced by variations of volume fractions. The proposed geometries used on the mathematical model was used to obtain a data set where the thicknesses referred of each material had been changed in order to obtain volume fraction of each phase providing 119 compositions that were used in the simulation with MCNP-X –computer code based on Monte Carlo Method that simulates the radiation transport. An artificial neural network (ANN) was trained with data obtained using the MCNP-X, and used to correlate such measurements with the respective real fractions. The ANN was able to correlate the data obtained on the simulation with MCNP-X with the volume fractions of the multiphase flows (oil-water-gas), both in the pattern of annular flow as stratified, resulting in a average relative error (%) for each production set of: annular (air= 3.85; water = 4.31; oil=1.08); stratified (air=3.10, water 2.01, oil = 1.45). The method demonstrated good efficiency in the determination of each material that composes the phases, thus demonstrating the feasibility of the technique.

Caffeine As An Indicator Of Estrogenic Activity In Source Water.

Caffeine has already been used as an indicator of anthropogenic impacts, especially the ones related to the disposal of sewage in water bodies. In this work, the presence of caffeine has been correlated with the estrogenic activity of water samples measured using the BLYES assay. After testing 96 surface water samples, it was concluded that caffeine can be used to prioritize samples to be tested for estrogenic activity in water quality programs evaluating emerging contaminants with endocrine disruptor activity.

Artificial Gait In Complete Spinal Cord Injured Subjects: How To Assess Clinical Performance.

Objective Adapt the 6 minutes walking test (6MWT) to artificial gait in complete spinal cord injured (SCI) patients aided by neuromuscular electrical stimulation. Method Nine male individuals with paraplegia (AIS A) participated in this study. Lesion levels varied between T4 and T12 and time post injured from 4 to 13 years. Patients performed 6MWT 1 and 6MWT 2. They used neuromuscular electrical stimulation, and were aided by a walker. The differences between two 6MWT were assessed by using a paired t test. Multiple r-squared was also calculated. Results The 6MWT 1 and 6MWT 2 were not statistically different for heart rate, distance, mean speed and blood pressure. Multiple r-squared (r2 = 0.96) explained 96% of the variation in the distance walked. Conclusion The use of 6MWT in artificial gait towards assessing exercise walking capacity is reproducible and easy to apply. It can be used to assess SCI artificial gait clinical performance.

The need for artificial tears in glaucoma patients: a comparative, retrospective study

PURPOSE: To evaluate the need for artificial tears by glaucoma patients under topical hypotensive treatment and to identify risk factors associated with it. METHODS: The charts of 175 glaucoma patients under medical treatment and 175 age-matched controls were reviewed. Age, gender, use of artificial tears, number of glaucoma medications used, and duration of treatment were recorded. RESULTS: Significantly more glaucoma patients (n=92; 52.6%) used artificial tears compared to age-matched controls (n=31; 17.7%) (p<0.001). Significantly more females (n=81; 39%) than males (n=42; 28.9%) used artificial tears (p=0.036). When the whole population was analyzed, female gender (OR=1.63) and the presence of glaucoma (OR= 5.14) were risk factors for the use of artificial tears (p<0.05). When the glaucoma population was analyzed, female gender (OR=2.57), number of medications >2 (OR=1.92), and duration of treatment >5 years (OR=2.93) were risk factors for the use of artificial tears (p<0.05). CONCLUSIONS: Topical treatment with antiglaucoma medication is a risk factor for the use of artificial tears. Female gender and long-term treatment of glaucoma with two or more medications were aggravating factors for the need for artificial tears.

Pulp tissue from primary teeth: new source of stem cells

SHED (stem cells from human exfoliated deciduous teeth) represent a population of postnatal stem cells capable of extensive proliferation and multipotential differentiation. Primary teeth may be an ideal source of postnatal stem cells to regenerate tooth structures and bone, and possibly to treat neural tissue injury or degenerative diseases. SHED are highly proliferative cells derived from an accessible tissue source, and therefore hold potential for providing enough cells for clinical applications. In this review, we describe the current knowledge about dental pulp stem cells and discuss tissue engineering approaches that use SHED to replace irreversibly inflamed or necrotic pulps with a healthy and functionally competent tissue that is capable of forming new dentin.

Validation of an experimental polyurethane model for biomechanical studies on implant-supported prosthesis: compression tests

OBJECTIVES: The complexity and heterogeneity of human bone, as well as ethical issues, most always hinder the performance of clinical trials. Thus, in vitro studies become an important source of information for the understanding of biomechanical events on implant-supported prostheses, although study results cannot be considered reliable unless validation studies are conducted. The purpose of this work was to validate an artificial experimental model based on its modulus of elasticity, to simulate the performance of human bone in vivo in biomechanical studies of implant-supported prostheses. MATERIAL AND METHODS: In this study, fast-curing polyurethane (F16 polyurethane, Axson) was used to build 40 specimens that were divided into five groups. The following reagent ratios (part A/part B) were used: Group A (0.5/1.0), Group B (0.8/1.0), Group C (1.0/1.0), Group D (1.2/1.0), and Group E (1.5/1.0). A universal testing machine (Kratos model K - 2000 MP) was used to measure modulus of elasticity values by compression. RESULTS: Mean modulus of elasticity values were: Group A - 389.72 MPa, Group B - 529.19 MPa, Group C - 571.11 MPa, Group D - 470.35 MPa, Group E - 437.36 MPa. CONCLUSION: The best mechanical characteristics and modulus of elasticity value comparable to that of human trabecular bone were obtained when A/B ratio was 1:1.

Abrasion wear resistance of different artificial teeth opposed to metal and composite antagonists

One of the most important properties of artificial teeth is the abrasion wear resistance, which is determinant in the maintenance of the rehabilitation's occlusal pattern. OBJECTIVES: This in vitro study aims to evaluate the abrasion wear resistance of 7 brands of artificial teeth opposed to two types of antagonists. MATERIAL AND METHODS: Seven groups were prepared with 12 specimens each (BIOLUX & BL, TRILUX & TR, BLUE DENT & BD, BIOCLER & BC, POSTARIS & PO, ORTHOSIT & OR, GNATHOSTAR & GN), opposed to metallic (M & nickel-chromium alloy), and to composite antagonists (C & Solidex indirect composite). A mechanical loading device was used (240 cycles/min, 4 Hz speed, 10 mm antagonist course). Initial and final contours of each specimen were registered with aid of a profile projector (20x magnification). The linear difference between the two profiles was measured and the registered values were subjected to ANOVA and Tukey's test. RESULTS: Regarding the antagonists, only OR (M = 10.45 ± 1.42 µm and C = 2.77 ± 0.69 µm) and BC (M = 6.70 ± 1.37 µm and C = 4.48 ± 0.80 µm) presented statistically significant differences (p < 0.05). Best results were obtained with PO (C = 2.33 ± 0.91 µm and M = 1.78 ± 0.42 µm), followed by BL (C = 3.70 ± 1.32 µm and M = 3.70 ± 0.61 µm), statistically similar for both antagonists (p>0.05). Greater result variance was obtained with OR, which presented the worse results opposed to Ni-Cr (10.45 ± 1.42 µm), and results similar to the best ones against composite (2.77 ± 0.69 µm). CONCLUSIONS: Within the limitations of this study, it may be concluded that the antagonist material is a factor of major importance to be considered in the choice of the artificial teeth to be used in the prosthesis.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.