Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Thalidomide plus dexamethasone as a maintenance therapy after autologous hematopoietic stem cell transplantation improves progression-free survival in multiple myeloma

Despite the good response of stem cell transplant (SCT) in the treatment of multiple myeloma (MM), most patients relapse or do not achieve complete remission, suggesting that additional treatment is needed. We assessed the impact of thalidomide in maintenance after SCT in untreated patients with MM. A hundred and eight patients (<70 years old) were randomized to receive maintenance with dexamethasone (arm A; n = 52) or dexamethasone with thalidomide (arm B; n = 56; 200 mg daily) for 12 months or until disease progression. After a median follow-up of 27 months, an intention to treat analysis showed a 2-year progression-free survival (PFS) of 30% in arm A (95% CI 2238) and 64% in arm B (95% CI 5771; P = 0.002), with median PFS of 19 months and 36 months, respectively. In patients who did not achieve at least a very good partial response, the PFS at 2 years was significantly higher when in use of thalidomide (19 vs. 59%; P = 0.002). Overall survival at 2 years was not significantly improved (70 vs. 85% in arm A and arm B, respectively; P = 0.27). The addition of thalidomide to dexamethasone as maintenance improved the PFS mainly in patients who did not respond to treatment after SCT. Am. J. Hematol. (c) 2012 Wiley Periodicals, Inc.

The Influence of Environmental Temperature and Air Humidity on the Maintenance of Sterility of Surgical Instruments Sterilized in Different Wraps

State of Sao Paulo Research Foundation (FAPESP), Brazil

Semi-supervised learning guided by the modularity measure in complex networks

Semi-supervised learning techniques have gained increasing attention in the machine learning community, as a result of two main factors: (1) the available data is exponentially increasing; (2) the task of data labeling is cumbersome and expensive, involving human experts in the process. In this paper, we propose a network-based semi-supervised learning method inspired by the modularity greedy algorithm, which was originally applied for unsupervised learning. Changes have been made in the process of modularity maximization in a way to adapt the model to propagate labels throughout the network. Furthermore, a network reduction technique is introduced, as well as an extensive analysis of its impact on the network. Computer simulations are performed for artificial and real-world databases, providing a numerical quantitative basis for the performance of the proposed method.

Cost-effectiveness of conventional and modified supervised toothbrushing in preventing caries in permanent molars among 5-year-old children

The cost-effectiveness of a modified supervised toothbrushing program was compared to a conventional program. A total of 284 five-year-old children presenting at least one permanent molar with emerged/sound occlusal surface participated. In the control group, oral health education and dental plaque dying followed by toothbrushing with fluoride dentifrice was carried outfour times per year. With the test group, children also underwent professional cross-brushing on surfaces of first permanent molar rendered by a dental assistant five times per year. Enamel/dentin caries were recorded on buccal, occlusal and lingual surfaces of permanent molars for a period of 18 months. The incidence density (ID) ratio was estimated using Poisson's regression model. The ID was 50% lower among boys in the test group (p = 0.016). The cost of the modified program was US$ 1.79 per capita. The marginal cost-effectiveness ratio among boys was US$ 6.30 per avoided carie. The modified supervised toothbrushing program was shown to be cost-effective in the case of boys.

Demographic characterization of supervised dog and cat populations in Sao Paulo city, Brazil

This study aimed to estimate the owned dog and cat populations of Sao Paulo city using a complex sample with random selection in two stages. In each administrative district, six census sectors and 20 households in each sampled sector were visited from September 2006 to September 2009, totalizing 11,272 interviews. The human: dog ratio was 4.34 and the human: cat ratio was 19.33. The dog population was 2,507,401 and the cat population, 562,965. The dog population was composted of 52.7% males, while among the cat population it was 45.1%. The proportion of sterilized females (23.4% among dogs and 46.1% among cats) was higher than males (11.4% among dogs and 31.5% among cats). The mean age of dogs was 4.99 years, and for cats, 3.53 years. The proportion of restricted (without access to the street) dogs, 64.4%, was higher than restricted cats, 42.5%. The average number of animals/household was 1.60 for dogs and 1.69 for cats. The animal ownership is associated with cultural factors, therefore the characterization of canine and feline population is essential to implement an adequate animal population management program and zoonosis control.

Improvement in ARDS experimental model installation: Low mortality rate and maintenance of hemodynamic stability

Introduction: Many experimental models using lung lavage have been developed for the study of acute respiratory distress syndrome (ARDS). The original technique has been modified by many authors, resulting in difficulties with reproducibility. There is insufficient detail on the lung injury models used, including hemodynamic stability during animal preparation and drawbacks encountered such as mortality. The authors studied the effects of the pulmonary recruitment and the use of fixed tidal volume (Vt) or fixed inspiratory pressure in the experimental ARDS model installation. Methods: Adult rabbits were submitted to repeated lung lavages with 30 ml/kg warm saline until the ARDS definition (PaO2/FiO(2) <= 100) was reached. The animals were divided into three groups, according to the technique used for mechanical ventilation: 1) fixed Vt of 10 ml/kg; 2) fixed inspiratory pressure (IP) with a tidal volume of 10 ml/kg prior to the first lung lavage; and 3) fixed Vt of 10 ml/kg with pulmonary recruitment before the first lavage. Results: The use of alveolar recruitment maneuvers, and the use of a fixed Vt or IP between the lung lavages did not change the number of lung lavages necessary to obtain the experimental model of ARDS or the hemodynamic stability of the animals during the procedure. A trend was observed toward an increased mortality rate with the recruitment maneuver and with the use of a fixed IP. Discussion: There were no differences between the three study groups, with no disadvantage in method of lung recruitment, either fixed tidal volume or fixed inspiratory pressure, regarding the number of lung lavages necessary to obtain the ARDS animal model. Furthermore, the three different procedures resulted in good hemodynamic stability of the animals, and low mortality rate. (C) 2012 Elsevier Inc. All rights reserved.

Integrating on-line process control and imperfect corrective maintenance: An economical design

Existing studies of on-line process control are concerned with economic aspects, and the parameters of the processes are optimized with respect to the average cost per item produced. However, an equally important dimension is the adoption of an efficient maintenance policy. In most cases, only the frequency of the corrective adjustment is evaluated because it is assumed that the equipment becomes "as good as new" after corrective maintenance. For this condition to be met, a sophisticated and detailed corrective adjustment system needs to be employed. The aim of this paper is to propose an integrated economic model incorporating the following two dimensions: on-line process control and a corrective maintenance program. Both performances are objects of an average cost per item minimization. Adjustments are based on the location of the measurement of a quality characteristic of interest in a three decision zone. Numerical examples are illustrated in the proposal. (c) 2012 Elsevier B.V. All rights reserved.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Mutations in CTC1, encoding conserved telomere maintenance component 1, cause Coats plus

Coats plus is a highly pleiotropic disorder particularly affecting the eye, brain, bone and gastrointestinal tract. Here, we show that Coats plus results from mutations in CTC1, encoding conserved telomere maintenance component 1, a member of the mammalian homolog of the yeast heterotrimeric CST telomeric capping complex. Consistent with the observation of shortened telomeres in an Arabidopsis CTC1 mutant and the phenotypic overlap of Coats plus with the telomeric maintenance disorders comprising dyskeratosis congenita, we observed shortened telomeres in three individuals with Coats plus and an increase in spontaneous gamma H2AX-positive cells in cell lines derived from two affected individuals. CTC1 is also a subunit of the alpha-accessory factor (AAF) complex, stimulating the activity of DNA polymerase-alpha primase, the only enzyme known to initiate DNA replication in eukaryotic cells. Thus, CTC1 may have a function in DNA metabolism that is necessary for but not specific to telomeric integrity.

Efficacy of graded activity versus supervised exercises in patients with chronic non-specific low back pain: protocol of a randomised controlled trial

Abstract Background Low back pain is a relevant public health problem, being an important cause of work absenteeism worldwide, as well as affecting the quality of life of sufferers and their individual functional performances. Supervised active physical routines and of cognitive-behavioral therapies are recommended for the treatment of chronic Low back pain, although evidence to support the effectiveness of different techniques is missing. Accordingly, the aim of this study is to contrast the effectiveness of two types of exercises, graded activity or supervised, in decreasing symptoms of chronic low back pain. Methods/design Sample will consist of 66 patients, blindly allocated into one of two groups: 1) Graded activity which, based on an operant approach, will use time-contingent methods aiming to increase participants’ activity levels; 2) Supervised exercise, where participants will be trained for strengthening, stretching, and motor control targeting different muscle groups. Interventions will last one hour, and will happen twice a week for 6 weeks. Outcomes (pain, disability, quality of life, global perceived effect, return to work, physical activity, physical capacity, and kinesiophobia) will be assessed at baseline, at treatment end, and three and six months after treatment end. Data collection will be conducted by an investigator blinded to treatment allocation. Discussion This project describes the randomisation method that will be used to compare the effectiveness of two different treatments for chronic low back pain: graded activity and supervised exercises. Since optimal approach for patients with chronic back pain have yet not been defined based on evidence, good quality studies on the subject are necessary. Trial registration NCT01719276

Model-based reuse for crosscutting frameworks: assessing reuse and maintenance effort

Abstract Background Over the last years, a number of researchers have investigated how to improve the reuse of crosscutting concerns. New possibilities have emerged with the advent of aspect-oriented programming, and many frameworks were designed considering the abstractions provided by this new paradigm. We call this type of framework Crosscutting Frameworks (CF), as it usually encapsulates a generic and abstract design of one crosscutting concern. However, most of the proposed CFs employ white-box strategies in their reuse process, requiring two mainly technical skills: (i) knowing syntax details of the programming language employed to build the framework and (ii) being aware of the architectural details of the CF and its internal nomenclature. Also, another problem is that the reuse process can only be initiated as soon as the development process reaches the implementation phase, preventing it from starting earlier. Method In order to solve these problems, we present in this paper a model-based approach for reusing CFs which shields application engineers from technical details, letting him/her concentrate on what the framework really needs from the application under development. To support our approach, two models are proposed: the Reuse Requirements Model (RRM) and the Reuse Model (RM). The former must be used to describe the framework structure and the later is in charge of supporting the reuse process. As soon as the application engineer has filled in the RM, the reuse code can be automatically generated. Results We also present here the result of two comparative experiments using two versions of a Persistence CF: the original one, whose reuse process is based on writing code, and the new one, which is model-based. The first experiment evaluated the productivity during the reuse process, and the second one evaluated the effort of maintaining applications developed with both CF versions. The results show the improvement of 97% in the productivity; however little difference was perceived regarding the effort for maintaining the required application. Conclusion By using the approach herein presented, it was possible to conclude the following: (i) it is possible to automate the instantiation of CFs, and (ii) the productivity of developers are improved as long as they use a model-based instantiation approach.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

Supervised classification of basaltic aggregate particles based on texture properties

The strength and durability of materials produced from aggregates (e.g., concrete bricks, concrete, and ballast) are critically affected by the weathering of the particles, which is closely related to their mineral composition. It is possible to infer the degree of weathering from visual features derived from the surface of the aggregates. By using sound pattern recognition methods, this study shows that the characterization of the visual texture of particles, performed by using texture-related features of gray scale images, allows the effective differentiation between weathered and nonweathered aggregates. The selection of the most discriminative features is also performed by taking into account a feature ranking method. The evaluation of the methodology in the presence of noise suggests that it can be used in stone quarries for automatic detection of weathered materials.