Computed tomography of a benign mesenchymoma of soft tissue.
Computed tomography of a benign mesenchymoma in a 7-year-old boy demonstrated bone and fat intermingled with nonspecific soft tissue.
Child↗
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Computed tomography in soft tissue disorders of the lower extremities.
Computed Tomography (CT) constitutes an important new imaging modality in the evaluation of soft tissue tumors. They are detectable by CT because their density is different from that of muscles and because they cause displacement of normal structures. CT was found to be useful in demonstrating the true extent of lesions in the soft tissue of the lower extremities of 24 patients as confirmed by examination of the surgically removed tumors. CT was also able to define the lesions' relation to and involvement with the surrounding tissue. We were not able to distinguish between benign and malignant lesions by CT. Generally, the specific attenuation values were not helpful in differentiation between various types of tumors. However, in cases of tumors such as lipomas, cysts and neurofibromas it may be of some use.
Adolescent↗
[EPIC-SOFT a European computer program for 24-hour dietary protocols].
Within the EPIC study (European Prospective Investigation into Cancer and Nutrition) a calibration approach is applied to compare dietary data obtained by food frequency questionnaires from 9 European countries. A software for 24-h recalls was developed as the calibration instrument by the International Agency for Research on Cancer (IARC) in collaboration with all national EPIC centers. This computer program, called EPIC-SOFT, is an interview-based dietary assessment instrument that allows one to obtain a very detailed description and quantification of foods, recipes, and supplements consumed in the course of the preceding day. Probing questions and entering consumed foods in chronological order support the respondent's memory. The standardized structure prescribes--on the food group level--possibilities of description and quantification of food items to choose from. Quantification of consumed foods is supported by the EPIC-SOFT picture book that comprises colored photographs of foods in different portion sizes. The software provides an automatic coding of food items and recipe ingredients as well as calculation of nutrient intake. EPIC-SOFT is characterized by the obtained standardization of dietary data within Europe, a large number of available foods and recipes, and a very detailed description of consumed foods. Currently, EPIC-SOFT is one of the few dietary instruments providing comparable nutritional data within Europe.
Calibration↗
[Computed tomography of soft tissue tumors of the hand and the forearm].
Computed tomography was carried out in 32 patients with clinically equivocal soft-tissue lesions of the hand (24 times) and forearm (8 times). The CT scans were performed with the patients in standard positions; thin slices and zoom technique were used. All soft-tissue tumors were correctly diagnosed with regard to localization, size and infiltration of the surrounding tissue. The histological diagnosis was correct in tendon-sheath proliferations, deposits caused by metabolic disorders, epithelial and ganglion cysts, hemangiomas, lipomas and in one schwannoma. A malignancy was suspected and was proven to be correct in two cases. False-positive diagnoses of a malignant soft-tissue tumor were made in one case of an aggressive fibromatosis, in a rapidly progressive, ossifying myositis, and three times in the presence of postoperative scar tissue following the resection of a sarcoma. Finally, a case of proliferative myositis regarded as semimalignant was underrated by CT. The hand surgeon considered CT diagnostics to be very helpful in planning operations in an anatomically complex organ such as the hand.
Adolescent↗
Detecting computer-induced errors in remote-sensing JPEG compression algorithms.
The JPEG image compression standard is very sensitive to errors. Even though it contains error resilience features, it cannot easily cope with induced errors from computer soft faults prevalent in remote-sensing applications. Hence, new fault tolerance detection methods are developed to sense the soft errors in major parts of the system while also protecting data across the boundaries where data flow from one subsystem to the other. The design goal is to guarantee no compressed or decompressed data contain computer-induced errors without detection. Detection methods are expressed at the algorithm level so that a wide range of hardware and software implementation techniques can be covered by the fault tolerance procedures while still maintaining the JPEG output format. The major subsystems to be addressed are the discrete cosine transform, quantizer, entropy coding, and packet assembly. Each error detection method is determined by the data representations within the subsystem or across the boundaries. They vary from real number parities in the DCT to bit-level residue codes in the quantizer, cyclic redundancy check parities for entropy coding, and packet assembly. The simulation results verify detection performances even across boundaries while also examining roundoff noise effects in detecting computer-induced errors in processing steps.
Algorithms↗
An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps.
The radiation therapy decision-making is a complex process that has to take into consideration a variety of interrelated functions. Many fuzzy factors that must be considered in the calculation of the appropriate dose increase the complexity of the decision-making problem. A novel approach introduces fuzzy cognitive maps (FCMs) as the computational modeling method, which tackles the complexity and allows the analysis and simulation of the clinical radiation procedure. Specifically this approach is used to determine the success of radiation therapy process estimating the final dose delivered to the target volume, based on the soft computing technique of FCMs. Furthermore a two-level integrated hierarchical structure is proposed to supervise and evaluate the radiotherapy process prior to treatment execution. The supervisor determines the treatment variables of cancer therapy and the acceptance level of final radiation dose to the target volume. Two clinical case studies are used to test the proposed methodology and evaluate the simulation results. The usefulness of this two-level hierarchical structure discussed and future research directions are suggested for the clinical use of this methodology.
Algorithms↗
[Morphological types of the glandular epithelium nuclei from benign and malignant mammary gland diseases].
The morphometric parameters of the nuclear-nucleolar apparatus of benign and malignant mammary cells were investigated by computer-aided morphometry of cytological specimen stained by a 50% silver nitrate solution. On the basis of a static analysis of measurement results a computer soft was created to classify the nuclei. The soft, with respect to an analysis of the discriminative functions and to a variety of formally logical limitations, subdivides the nuclei into 6 morphotypes with variations "a" and "b", which correspond to certain clinical and morphological variants of breast diseases. From the practical viewpoint, the subdivision of nuclei into the 3rd and 4th morphotypes is most interesting because it can provide the clinical cytology expert with extra information for the differential diagnostics of proliferative and malignant transformations in the mammary glands as well as for the definition of dysplasia stages and for the determination of tumor-cell malignancy degree.
Breast Diseases↗
Algorithms for the computer modelling of mechanical interactions with soft tissue.
The computer modelling of soft tissue has applications in the simulation of surgical procedures, product design, and in CAD generally as well as in motion pictures. We begin by reviewing computer modelling techniques in a range of applications. Algorithms are described to predict where surfaces interact mechanically, aiming as far as possible to use geometric modelling methods available within high level CAD systems. After an initial 2-Dimensional evaluation, 3-dimensional surfaces were used throughout. A model was developed to predict the region of impact of two surfaces in an environment of many surface patches. We report the results of this modelling and the application of refinement algorithms to reduce the computation requirements. We then go on to discuss the applicability of this work in the modelling of the deformation behaviour of soft tissues.
Algorithms↗
Scenarios, past, present and future.
A key point in considering strategic planning is that it is not forecasting. The future is unpredictable and is not a product of the past. This low opinion of forecasting has gained in influence recently. But such an approach creates a dilemma for the strategic planner. He needs to take into account potential future forces--but he can only do this with inadequate means. Forecasting methods, however, can suggest trends and it is possible to reduce the number of possible futures to a manageable number. This is, in effect, creating scenarios. The concept of using alternative scenarios in planning was popularized some 20 years back. The proviso was made that they should not be interpreted as forecasts. The methods have proved highly flexible and include the consensus technique, the iteration-through-synopsis technique, and the cross-impact method. Various studies using one or more of these have been implemented, perhaps the best known being by Meadows and by Mesarovic. These have been based on the so-called 'hard' method, using computers. 'Soft' methods are based more on the mind and use psychology and sociology, the most familiar being the Delphi method. A somewhat more sophisticated version is Cross-Impact Analysis.
Forecasting↗
Rough set-based hybrid fuzzy-neural controller design for industrial wastewater treatment.
Recent advances in control engineering suggest that hybrid control strategies, integrating some ideas and paradigms existing in different soft computing techniques, such as fuzzy logic, genetic algorithms, rough set theory, and neural networks, may provide improved control performance in wastewater treatment processes. This paper presents an innovative hybrid control algorithm leading to integrate the distinct aspects of indiscernibility capability of rough set theory and search capability of genetic algorithms with conventional neural-fuzzy controller design. The methodology proposed in this study employs a three-stage analysis that is designed in series for generating a representative state function, searching for a set of multi-objective control strategies, and performing a rough set-based autotuning for the neural-fuzzy logic controller to make it applicable for controlling an industrial wastewater treatment process. Research findings in the case study clearly indicate that the use of rough set theory to aid in the neural-fuzzy logic controller design can produce relatively better plant performance in terms of operating cost, control stability, and response time simultaneously, which is effective at least in the selected industrial wastewater treatment plant. Such a methodology is anticipated to be capable of dealing with many other types of process control problems in waste treatment processes by making only minor modifications.
Artificial Intelligence↗
Neural networks in astronomy.
In the last decade, the use of neural networks (NN) and of other soft computing methods has begun to spread also in the astronomical community which, due to the required accuracy of the measurements, is usually reluctant to use automatic tools to perform even the most common tasks of data reduction and data mining. The federation of heterogeneous large astronomical databases which is foreseen in the framework of the astrophysical virtual observatory and national virtual observatory projects, is, however, posing unprecedented data mining and visualization problems which will find a rather natural and user friendly answer in artificial intelligence tools based on NNs, fuzzy sets or genetic algorithms. This review is aimed to both astronomers (who often have little knowledge of the methodological background) and computer scientists (who often know little about potentially interesting applications), and therefore will be structured as follows: after giving a short introduction to the subject, we shall summarize the methodological background and focus our attention on some of the most interesting fields of application, namely: object extraction and classification, time series analysis, noise identification, and data mining. Most of the original work described in the paper has been performed in the framework of the AstroNeural collaboration (Napoli-Salerno).
Astronomy↗
Energy saving in a wastewater treatment process: an application of fuzzy logic control.
Many uncertain factors affect the operation of Wastewater Treatment Plants. Due to the complexity of biological wastewater treatment processes, classical methods show significant difficulties when trying to control them automatically. Consequently soft computing techniques and, specifically, fuzzy logic appears to be a good candidate for controlling these ill-defined, time-varying and non-linear systems. This paper describes the development and implementation of a Fuzzy Logic Controller to regulate the aeration in the Taradell Wastewater Treatment Plant. The main goal of this control process is to save energy without decreasing the quality of the effluent discharged. The fuzzy controller integrates the information coming from two different signals: the Dissolved Oxygen and Oxidation-Reduction Potential values. The simulation results proved that fuzzy logic is a good tool for controlling the aeration of the wastewater treatment plant. The results obtained show that energy savings of more than 10% can be achieved using aeration fuzzy control and at the same time still keeping the good removal levels.
Conservation of Energy Resources↗
On the intersubject generalization ability in extracting kinematic information from afferent nervous signals.
In the recent past, many efforts have been carried out in order to evaluate the feasibility of implementing closed-loop controlled neuroprostheses based on the processing of sensory electroneurographic (ENG) signals. The success of these techniques mostly relies on the development of processing algorithms capable of extracting the necessary kinematic information from these signals. Soft-computing algorithms can be very useful when dealing with the complexity of the neuromuscular system because of their generalization ability and model-free structure. In this paper, these techniques were used to extract angular position information from the ENG signals recorded from muscle afferents in animal model using cuff electrodes. Specifically, a genetic algorithm-based dynamic nonsingleton fuzzy logic system (named GA-DNSFLS) was developed and tested on different types of angular trajectories (characterized by small or large angular excursions). In particular, two different Takagi-Sugeno-Kang (TSK)-like structures were used in the consequent part of the neuro-fuzzy model in order to verify which one could improve the generalization abilities (intrasubject and intersubject). The results showed that the GA-DNSFLS was able to reconstruct the trajectories giving interesting results in terms of correlation between the actual and the predicted trajectories for small excursion movements during intrasubject and intersubject tests. Particularly, one of the TSK models showed better results in terms of intersubject generalization. The simulations conducted with the large excursion movements led in some cases to interesting results but further experiments are necessary in order to analyze this point more in deep.
Action Potentials↗
Optical generation of fuzzy-based rules.
In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.
Journal Article↗
[Clone of a novel liver cancer associated gene and analysis of the secondary structures of the predicted protein].
OBJECTIVE: To clone a novel liver cancer associated gene, and to explore the molecular basis of liver cancer genesis. METHODS: Using mRNA differential display polymerase chain reaction (DDPCR) and screening the human placenta cDNA library, we got a full-length cDNA of the gene. We prepared and purified the GST fusion protein and the special polyclonal antibody, engaged in the Western blot and immunohistochemical staining analysis, and analyzed the second structures and predicted the function of the protein by the computer soft. RESULTS: We have got a full-length cDNA of the liver cancer associated gene and identified that the full-length cDNA of the gene could be expressed in 293 eukaryocytes by Western blot assay. We localized the target protein in cytoplasm using the immunohistochemical staining methods, and found two SH3 binding domains and several protein kinase phosphorylation sites by analyzing the second structures. CONCLUSIONS: We have got a novel full-length cDNA of human liver cancer associated gene.
Amino Acid Sequence↗
An intelligent controller for automated operation of sequencing batch reactors.
In this paper the results are presented of original research into the automatic and "intelligent" detection of breakpoints in Dissolved Oxygen (DO) profiles. The research has been based on a large body of data collected from laboratory SBRs operating on synthetic wastewater. Two different approaches were followed to identify the endpoints. The paper analyses and evaluates the results of automatic detection on the basis of geometric features in the DO profiles. This was followed by classification of the detected breakpoints using different soft computing techniques based on Neural Network (NN), Fuzzy Neural Network (FuNN) and Evolving Fuzzy Neural Network (EfuNN) software systems for breakpoint classification. A high rate of successful detection and classification was obtained with up to 96% of the decisions made correctly. In order to overcome the limitations of this system to adapt to dynamically changing process conditions, an intelligent control model was developed by a combination between an Evolving Fuzzy Neural Net (EfuNN) combined with a logic decision unit. This system has the ability to "learn on-the-fly" and adjust its response pattern in order to maintain a high rate of successful breakpoint detection under varying changing process conditions. This software system has been sucessfully embedded on a small programmable controller for integration into larger process control systems for the operation of SBR plants.
Automation↗
[Secondary cataract and IOL type and the shape of its optic part].
Although cortical remains are purged from the capsule sac by special techniques and better IOL models are used for implantation, opacification of the posterior capsule (OPC) persists to be one of the most frequent complications in modern cataract surgery. The frequency rate of OPC depends on used evaluation criteria. A total of 165 eyes were examined after cataract extraction for OPC. Four types of IOL were used; they are hydrophobic acryl three-part IOL (AcrySof MAZOVA, n = 46), hydrophobic acryl all-in-one IOL (ArySofSA30AL, n = 38) and silicone three-part (CeeOn911A, Pharmacia, n = 42). OPC were evaluated by EPCO 2000 computer soft. When IOL with the straight edge of the optic axis were in use (both silicone and acryl ones), there was registered, in 1 year after surgery (p < or = 0.05) a reliably lower frequency and intensity of OPC versus IOL with the curved edge of the optic axis. The shaped curvature in the posterior capsule encompassing tightly the IOL edge prevented further migration of lens cells. The IOL material (hydrophobic acryl or silicone) is of no importance for the OPC development. There was no reduction in visual acuity and no laser capsulotomy was made in any of the groups of patients.
Aged↗
[The use of voicing test in phoniatrics].
A study was made of the voicing-test efficacy in clinical practice. The study group consisted of 11 patients with different laryngeal diseases, the control group comprised 40 healthy subjects. Two parameters were estimated with a special computer soft: fraction of locally unvoiced pitch frames (FLUPF) and degree of voice breaks (DVB). Jitter, shimmer and signal to noise ratio were estimated as control. It is shown that the presence of locally unvoiced pitched frames is abnormal. The FLUPF test proved more precise than DVB test and, therefore, is preferential. Thus, the FLUPF test is clinically significant and can be used in clinical practice in line with parameters of acoustic analysis.
Female↗