Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Previsão de estabilidade de óleos vegetais através da rede de inteligência artificial

Redes Neurais Artificiais são técnicas computacionais que se utilizam de um modelo matemático capaz de adquirir conhecimentos pela experiência; esse comportamento inteligente da rede provém das interações entre unidades de processamento, denominadas de neurônios artificiais. O objetivo deste trabalho foi criar uma rede neural capaz de prever a estabilidade de óleos vegetais, a partir de dados de suas composições químicas, visando um modelo para a previsão da shelf-life de óleos vegetais, tendo como parâmetros apenas dados de suas composições químicas. Os primeiros passos do processo de desenvolvimento da rede consistiram na coleta de dados relativos ao problema e sua separação em um conjunto de treinamento e outro de testes. Estes conjuntos apresentaram como variáveis dados de composição química, que incluíram os valores totais em ácidos graxos, fenóis, tocoferóis e a composição individual em ácidos graxos. O passo seguinte foi a execução do treinamento, onde o padrão de entrada apresentado à rede como parâmetro de estabilidade foi o índice de peróxido, determinado experimentalmente por um período de 16 dias de armazenagem na ausência de luz, a 65ºC. Após o treinamento foi testada a capacidade de previsão adquirida pela rede, em função do parâmetro de estabilidade adotado, mas com um novo grupo de óleos. Seguindo o teste, foi determinada a correlação linear entre os valores de estabilidade previstos pela rede e aqueles determinados experimentalmente. Com os resultados obtidos, pode-se confirmar a viabilidade de previsão da estabilidade de óleos vegetais pela rede neural, a partir de dados de sua composição química, utilizando como parâmetro de estabilidade o índice de peróxido.

An artificial neural network model for prediction of quality characteristics of apples during convective dehydration

In this study, the effects of hot-air drying conditions on color, water holding capacity, and total phenolic content of dried apple were investigated using artificial neural network as an intelligent modeling system. After that, a genetic algorithm was used to optimize the drying conditions. Apples were dried at different temperatures (40, 60, and 80 °C) and at three air flow-rates (0.5, 1, and 1.5 m/s). Applying the leave-one-out cross validation methodology, simulated and experimental data were in good agreement presenting an error < 2.4 %. Quality index optimal values were found at 62.9 °C and 1.0 m/s using genetic algorithm.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.

Inteligência artificial e teoria de resolução de problemas

Este artigo é uma tentativa de delinear as principais características da pesquisa numa nova área de estudos a chamada Inteligência Artificial (AI). Os itens 1 e 2 constituem um rápido histórico da AI e seus pressupostos básicos. O item 3 trata da teoria de resolução de problemas, desenvolvida por A. Newell e H. Simon. O item 4 procura mostrar a relevância da AI para a Filosofia, em especial para a filosofia da Mente e para a Teoria do Conhecimento.

Robots, intencionalidade e inteligência artificial

O artigo aborda problemas filosóficos relativos à natureza da intencionalidade e da representação mental. A primeira parte apresenta um breve histórico dos problemas, percorrendo rapidamente alguns episódios da filosofia clássica e da filosofia contemporânea. A segunda parte examina o Chinese Room Argument (Argumento do Quarto do Chinês) formulado por J. Searle. A terceira parte desenvolve alguns argumentos visando mostrar a inadequação do modelo funcionalista de mente na construção de robots. A conclusão (quarta parte) aponta algumas alternativas ao modelo funcionalista tradicional, como, por exemplo, o conexionismo.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.

A relationship between photosynthesis and translocation in plants stressed by ionizing radiation

Since previous investigations have shown that low levels of ionizing radiation can induce a reduction in the rates of apparent photosynthesis and in the magnitude of photoassimilated l4C exported out of a leaf, the present studies were designed and conducted to determine the relationship, if any, between the radiation effects on these two physiological processes. The experiments were particularly designed to determine if the radiation-induced reduction in export is the result of the reduction in photosynthesis and hence availability of materials for translocation or the result of a reduction in the amount of energy available for the vein loading process. This study has shown that the radiation-induced reduction in l4C export out of a leaf is likely related to a loss of energy available for the vein loading process rather than a reduction in the supply of materials available for export due to reduced C02 uptake. The process of photophosphorylation was shown to be reduced by exposure to radiation to an extent similar to the reduction in the export of l4C which was also observed. Both of these processes returned to their pre-irradiation rates 120 minutes following radiatruon exposure. The rate of photosynthetic C02 uptake was also reduced by radiation exposur~ howeve~ this process did not return to the control level nor was the extent of reduction as large as observed for photophosphorylation and photoassimilate export. The observed relationship between the reductions of export and photoph~sphorylation pointed to the utilization of photosynthetically produced ATP in the vein loading process. The radiation-induced reduction in the export of l4C was observed at the highest light intensity used in this study which would also imply the involvement of the photophosphorylation process as an energy seurce for vein loading. The lack of radiation-induced reduction in export at low light intensities was interpreted as being due to the utilization of respiratory derived ATP, a process known to be insensitive to radiation at the levels used in this study, as the energy source for the vein loading process. Studies using plants not stressed by radiation showed that there was an increase in export of 14C with higher light intensities. In summary, the data has been interpreted as showing that at high light intensities the ATP, produced by photophosphorylation, is available for use in the vein loading process. The site of ATP utilization could not be determined from the data obtained in this study but possible sites have been indicated from the work done by other physiologists and are discussed in the thesis.

The performance and strategies of adolescents in learning to read artificial words /

The present study explored processing strategies used by individuals when they begin to read c;l script. Stimuli were artificial words created from symbols and based on an alphabetic system. The words were.presented to Grade Nine and Ten students, with variations included in the difficulty of orthography and word familiarity, and then scores were recorded on the mean number of trials for defined learning variables. Qualitative findings revealed that subjects 1 earned parts of the visual a'nd auditory features of words prior to hooking up the visual stimulus to the word's name. Performance measures-which appear to affect the rate of learning were as follows: auditory short-term memory, auditory delayed short-term memory, visual delayed short- term memory, and word attack or decod~ng skills. Qualitative data emerging in verbal reports by the subjects revealed that strategies they pefceived to use were, graphic, phonetic decoding and word .reading.

Distribution of excitation energy in photosynthesis: a study of heat loss, photo chemical activity and fluorescence emission in intact calls of cyanobacterium.

Photosynthetic state transitions were investigated in the cyanobacterium Synechococcus sp. PCC 6301 by studying fluorescence emission, heat loss, and PS I activity in intact cells brought to state 1 and state 2. 77K fluorescence emission spectra were modelled with a sum of 6 components corresponding to PBS, PS II, and PS I emissions. The modelled data showed a large decrease in PS II fluorescence accompanied with a small increase in the PS I fluorescence upon transition to state 2 for excitation wavelengths absorbed by both PBS and ChI ll.. The fluorescence changes seen with ChI .a. excitations do not support the predictions of the mobile PBS model of state transition in PBS-containing organisms. Measurements of heat loss from intact cells in the two states were similar for both ChI it. and PBS excitations over three orders of magnitude of laser flash intensity. This suggests that the PBS does not become decoupled from PS II in state 2 as proposed by the PBS detachment model of state transition in PBS-containing organisms. PS I activity measurements done on intact cells showed no difference in the two states, in contrast with the predictions of all of the existing models of state transitions. Based on these results a model for state transition In PBScontaining organisms is proposed, with a PS II photoprotectory function.

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied.

The Fast Regulation of Photosynthesis in Diatoms: an inquiry into the physiological and physical origins of non-photochemical chlorophyll fluorescence quenching.

Diatoms are renowned for their robust ability to perform NPQ (Non-Photochemical Quenching of chlorophyll fluorescence) as a dissipative response to heightened light stress on photosystem II, plausibly explaining their dominance over other algal groups in turbulent light environs. Their NPQ mechanism has been principally attributed to a xanthophyll cycle involving the lumenal pH regulated reversible de-epoxidation of diadinoxanthin. The principal goal of this dissertation is to reveal the physiological and physical origins and consequences of the NPQ response in diatoms during short-term transitions to excessive irradiation. The investigation involves diatom species from different originating light environs to highlight the diversity of diatom NPQ and to facilitate the detection of core mechanisms common among the diatoms as a group. A chiefly spectroscopic approach was used to investigate NPQ in diatom cells. Prime methodologies include: the real time monitoring of PSII excitation and de-excitation pathways via PAM fluorometry and pigment interconversion via transient absorbance measurements, the collection of cryogenic absorbance spectra to measure pigment energy levels, and the collection of cryogenic fluorescence spectra and room temperature picosecond time resolved fluorescence decay spectra to study excitation energy transfer and dissipation. Chemical inhibitors that target the trans-thylakoid pH gradient, the enzyme responsible for diadinoxanthin de-epoxidation, and photosynthetic electron flow were additionally used to experimentally manipulate the NPQ response. Multifaceted analyses of the NPQ responses from two previously un-photosynthetically characterised species, Nitzschia curvilineata and Navicula sp., were used to identify an excitation pressure relief ‘strategy’ for each species. Three key areas of NPQ were examined: (i) the NPQ activation/deactivation processes, (ii) how NPQ affects the collection, dissipation, and usage of absorbed light energy, and (iii) the interdependence of NPQ and photosynthetic electron flow. It was found that Nitzschia cells regulate excitation pressure via performing a high amplitude, reversible antenna based quenching which is dependent on the de-epoxidation of diadinoxanthin. In Navicula cells excitation pressure could be effectively regulated solely within the PSII reaction centre, whilst antenna based, diadinoxanthin de-epoxidation dependent quenching was implicated to be used as a supplemental, long-lasting source of excitation energy dissipation. These strategies for excitation balance were discussed in the context of resource partitioning under these species’ originating light climates. A more detailed investigation of the NPQ response in Nitzschia was used to develop a comprehensive model describing the mechanism for antenna centred non-photochemical quenching in this species. The experimental evidence was strongly supportive of a mechanism whereby: an acidic lumen triggers the diadinoxanthin de-epoxidation and protonation mediated aggregation of light harvesting complexes leading to the formation of quencher chlorophyll a-chlorophyll a dimers with short-lived excited states; quenching relaxes when a rise in lumen pH triggers the dispersal of light harvesting complex aggregates via deprotonation events and the input of diadinoxanthin. This model may also be applicable for describing antenna based NPQ in other diatom species.

Optimizing Computational Frameworks to Study the Influence of the Protein Environment on the Individual Site Energies of Chromophores in Photosystem II of Photosynthesis

Photosynthesis is a process in which electromagnetic radiation is converted into chemical energy. Photosystems capture photons with chromophores and transfer their energy to reaction centers using chromophores as a medium. In the reaction center, the excitation energy is used to perform chemical reactions. Knowledge of chromophore site energies is crucial to the understanding of excitation energy transfer pathways in photosystems and the ability to compute the site energies in a fast and accurate manner is mandatory for investigating how protein dynamics ef-fect the site energies and ultimately energy pathways with time. In this work we developed two software frameworks designed to optimize the calculations of chro-mophore site energies within a protein environment. The first is for performing quantum mechanical energy optimizations on molecules and the second is for com-puting site energies of chromophores in a fast and accurate manner using the polar-izability embedding method. The two frameworks allow for the fast and accurate calculation of chromophore site energies within proteins, ultimately allowing for the effect of protein dynamics on energy pathways to be studied. We use these frame-works to compute the site energies of the eight chromophores in the reaction center of photosystem II (PSII) using a 1.9 Å resolution x-ray structure of photosystem II. We compare our results to conflicting experimental data obtained from both isolat-ed intact PSII core preparations and the minimal reaction center preparation of PSII, and find our work more supportive of the former.