Mixed transfer function neural networks for knowledge acquistition

Modeling helps to understand and predict the outcome of complex systems. Inductive modeling methodologies are beneficial for modeling the systems where the uncertainties involved in the system do not permit to obtain an accurate physical model. However inductive models, like artificial neural networks (ANNs), may suffer from a few drawbacks involving over-fitting and the difficulty to easily understand the model itself. This can result in user reluctance to accept the model or even complete rejection of the modeling results. Thus, it becomes highly desirable to make such inductive models more comprehensible and to automatically determine the model complexity to avoid over-fitting. In this paper, we propose a novel type of ANN, a mixed transfer function artificial neural network (MTFANN), which aims to improve the complexity fitting and comprehensibility of the most popular type of ANN (MLP - a Multilayer Perceptron).

Relationships between measures of fitness, physical activity, body composition and vascular function in children

Background : The prevalence of obesity and physical inactivity in Western countries has increased rapidly. Both are modifiable risk factors for cardiovascular disease. Atherosclerosis begins in childhood and endothelial dysfunction is its earliest detectable manifestation.

Methods : We assessed flow-mediated dilation (FMD) in 129 children (75 female; 10.3 + 0.3 yrs; 54 male; 10.4; 0.3 yrs). FMD was normalised for differences in the eliciting shear rate stimulus between subjects (SR_AUC). Fitness was assessed as peak oxygen uptake during an incremental treadmill exercise test (VO₂peak). Body composition was measured using a dual-energy X-ray absorptiometry (DEXA) scan. Physical activity (PA) was assessed using Actigraph accelerometers. The cohort was split into tertiles according to FMD% and also FMD% corrected for SR_AUC to gain insight into the determinants of vascular function.

Results : Across the cohort, significant correlations were observed between FMD%/SR_AUC and DEXA percentage fat (r = −0.23, p = 0.009) and percentage lean mass (r = 0.21, p = 0.008), and also with PA performed at moderate-to-high intensity (r = 0.363, p = 0.001). For children in the lowest FMD%/SR_AUC tertile, a stronger relationship with all PA measures was observed, particularly with high intensity PA (r = 0.572, P = 0.003). Regression analysis revealed that high intensity PA was the only predictor of impaired FMD%/SR_AUC.

Conclusions : These data suggest that traditional risk factors for CHD in adult populations impact upon vascular function in young people. Furthermore, it appears that individuals with impaired FMD may benefit from performing high intensity PA, whereas no relationships exist between FMD and lower intensities of PA or between PA and FMD in those subjects who possess preserved vascular function a priori.

Cognitive function in adolescents with chronic fatigue syndrome

This thesis explored cognitive function in adolescents with chronic fatigue syndrome. Counter to what has been found in adults, adolescents with CFS performed as well as their peers on demanding tests of executive function, information processing, memory and attention. The results suggest that CFS might impact differently on the developing brain. The portfolio used a case study approach to examine the effectiveness and utility of Finn's Therapeutic Assessment model in four clients.

Effective pseudonoise sequence and decoding function for imperceptibility and robustness enhancement in time-spread echo-based audio watermarking

This paper proposes an effective pseudonoise (PN) sequence and the corresponding decoding function for time-spread echo-based audio watermarking. Different from the traditional PN sequence used in time-spread echo hiding, the proposed PN sequence has two features. Firstly, the echo kernel resulting from the new PN sequence has frequency characteristics with smaller magnitudes in perceptually significant region. This leads to higher perceptual quality. Secondly, the correlation function of the new PN sequence has three times more large peaks than that of the existing PN sequence. Based on this feature, we propose a new decoding function to improve the robustness of time-spread echo-based audio watermarking. The effectiveness of the proposed PN sequence and decoding function is illustrated by theoretical analysis, simulation examples, and listening test.

Cardiac structure and function in young endurance athletes and nonathletes

The purpose of this study was to examine, in male adolescents, the effects of long-term endurance training on cardiac structure and function, by adopting a cross-sectional comparison with a nonathletic control group. A total of 13 endurance-trained (EX) and seven untrained (CON) male adolescents (mean ± SE, age = 15.3 ± 0.3 and 15.2 ± 0.28 yrs, respectively) underwent echocardiography at rest to determine left ventricular enddiastolic dimension (LVD_d), left ventricular end-systolic dimension (LVD_s), left ventricular posterior wall thickness (LVPW), stroke volume (SV), and cardiac output (CO). On separate days, incremental exercise tests were conducted on a cycle ergometer to measure peak oxygen uptake (VO_2max) and anaerobic power. VO_2max was greater in the endurance group (54.4 ± 1.8 mL min^–1 kg^–1) than in the control group (45.8 ± 1.6 mL min^–1 kg^–1; p < 0.05). Mean exercise time was longer in EX (12.9 ± 0.7 min) than CON (10.4 ± 0.8 min; p < 0.05). No significant differences were noted between the two groups in resting heart rate, maximal heart rate, LVD_d, LVD_s, LVPW, SV, SV indexed, CO, and CO indexed, or in the anaerobic strength. These data provide evidence that endurance-trained adolescent males develop superior exercise performance before the cardiac remodeling that is evident in trained adult athletes.

Semantic and layered protein function prediction from PPI networks

Background The past few years have seen a rapid development in novel high-throughput technologies that have created large-scale data on protein-protein interactions (PPI) across human and most model species. This data is commonly represented as networks, with nodes representing proteins and edges representing the PPIs. A fundamental challenge to bioinformatics is how to interpret this wealth of data to elucidate the interaction of patterns and the biological characteristics of the proteins. One significant purpose of this interpretation is to predict unknown protein functions. Although many approaches have been proposed in recent years, the challenge still remains how to reasonably and precisely measure the functional similarities between proteins to improve the prediction effectiveness.

Results We used a Semantic and Layered Protein Function Prediction (SLPFP) framework to more effectively predict unknown protein functions at different functional levels. The framework relies on a new protein similarity measurement and a clustering-based protein function prediction algorithm. The new protein similarity measurement incorporates the topological structure of the PPI network, as well as the protein's semantic information in terms of known protein functions at different functional layers. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed framework in predicting unknown protein functions.

Conclusion The proposed framework has a higher prediction accuracy compared with other similar approaches. The prediction results are stable even for a large number of proteins. Furthermore, the framework is able to predict unknown functions at different functional layers within the Munich Information Center for Protein Sequence (MIPS) hierarchical functional scheme. The experimental results demonstrated that the new protein similarity measurement reflects more reasonably and precisely relationships between proteins.

Marsupial milk : identifying signals for regulating mammary function and development of the young

The role of milk in providing nutrition for the young is well established. However, it is becoming apparent that milk has a more comprehensive role in programming and regulating growth and development of the suckled young, and an autocrine impact on the mammary gland so that it functions appropriately during the lactation cycle. This central role of milk is best studied in animal models, such as marsupials that have evolved a different lactation strategy to eutherians and allow researchers to more easily identify regulatory mechanisms that are not as readily apparent in eutherian species. For example, the tammar wallaby (Macropus eugenii) has evolved with a unique reproductive strategy of a short gestation, birth of an altricial young and a relatively long lactation during which the mother progressively changes the composition of the major, and many of the minor components of milk. Thus, in contrast to eutherians, there is a far greater investment in development of the young during lactation and it is likely that many of the signals that regulate development of eutherian embryos in utero are delivered by the milk. This requires the co-ordinated development and function of the mammary gland. Inappropriate timing of these signalling events in mammals may result in either limited or abnormal development of the young, and potentially a higher incidence of mature onset disease. The tammar is emerging as an attractive model to better understand the role of milk factors in these processes.

Classification of malware based on string and function feature selection

Anti-malware software producers are continually challenged to identify and counter new malware as it is released into the wild. A dramatic increase in malware production in recent years has rendered the conventional method of manually determining a signature for each new malware sample untenable. This paper presents a scalable, automated approach for detecting and classifying malware by using pattern recognition algorithms and statistical methods at various stages of the malware analysis life cycle. Our framework combines the static features of function length and printable string information extracted from malware samples into a single test which gives classification results better than those achieved by using either feature individually. In our testing we input feature information from close to 1400 unpacked malware samples to a number of different classification algorithms. Using k-fold cross validation on the malware, which includes Trojans and viruses, along with 151 clean files, we achieve an overall classification accuracy of over 98%.

Psychological and interpersonal dimensions of sexual function and dysfunction

Introduction. There are limited outcome data on the etiology and efficacy of psychological interventions for male and female sexual dysfunction as well as the role of innovative combined treatment paradigms.
Aim. This study aimed to highlight the salient psychological and interpersonal issues contributing to sexual health and dysfunction, to offer an etiological model for understanding the evolution and maintenance of sexual symptoms, and to offer recommendations for clinical management and research.
Methods. This study reviewed the current literature on the psychological and interpersonal issues contributing to male and female sexual dysfunction.
Main Outcome Measure. This study provides expert opinion based on a comprehensive review of the medical and psychological literature, widespread internal committee discussion, public presentation, and debate.
Results. Medical and psychological therapies for sexual dysfunctions should address the intricate biopsychosocial influences of the patient, the partner, and the couple. The biopsychosocial model provides an integrated paradigm for understanding and treating sexual dysfunction.
Conclusions. There is need for collaboration between healthcare practitioners from different disciplines in the evaluation, treatment, and education issues surrounding sexual dysfunction. In many cases, neither psychotherapy alone nor medical intervention alone is sufficient for the lasting resolution of sexual problems. The assessment of male, female, and couples’ sexual dysfunction should ideally include inquiry about predisposing, precipitating, maintaining, and contextual factors. Research is needed to identify efficacious combined and/or integrated treatments for sexual dysfunction.

Exhaled air temperature as a function of ambient temperature in flying and resting ducks

Exhaled air temperature (T exh) has a paramount effect on respiratory water loss during flight. For migratory birds, low T exh potentially reduces water loss and increases flight range. However, only three studies provide empirical data on T exh during flight. The aim of this study was to record T exh of birds during rest and flight at a range of controlled ambient temperatures (T amb). One wigeon and two teal flew a total of 20 times in a wind tunnel at T amb ranging from 1° to 24°C. T exh during flight did not differ between the two species and was strongly correlated with T amb (T exh=1.036 T amb + 13.426; R²=0.58). In addition, body temperature had a weak positive effect on T exh. At a given T amb, T exh was about 5°C higher during flight than at rest.

Independent and combined effects of exercise and vitamin D on muscle morphology, function and falls in the elderly

Regular exercise, particularly progressive resistance training (PRT), is recognized as one of the most effective strategies to prevent age-related muscle loss (sarcopenia), but its effects on muscle function are mixed. However, emerging data indicates that high velocity PRT (fast concentric muscle contractions) is more effective for improving functional outcomes than traditional PRT. In terms of falls prevention, high-challenging balance training programs appear to be most effective. There is also compelling evidence that supplemental vitamin D is an effective therapeutic option for falls prevention. The findings from a recent meta-analysis revealed that supplemental vitamin D at a dose of at least 700–1,000 IU/d or an achieved serum 25(OH)D level of at least 60 nmol/L was associated with reduced falls risk among older individuals. Based on these findings, it is possible that the combination of exercise and vitamin D could have a synergistic effect on muscle morphology and function, particularly since both interventions have been shown to have beneficial effects on type II “fast twitch” muscle fibers and systemic inflammation, which have both been linked to losses in muscle mass and function. Unfortunately however, the findings from the limited number of factorial 2 × 2 design RCTs indicate that additional vitamin D does not enhance the effects of exercise on measures of muscle morphology, function or falls risk. However, none of these trials were adequately powered to detect a “synergistic” effect between the two treatment strategies, but it is likely that if an exercise-by-vitamin D interaction does exist, it may be limited to situations when vitamin D deficiency/insufficiency is corrected. Further targeted research in “high risk” groups is still needed to address this question, and evaluate whether there is a threshold level of serum 25(OH)D to maximize the effects of exercise on muscle and falls risk.

Computational exploration of the biological basis of Black-Scholes expected utility function

It has often been argued that there exists an underlying biological basis of utility functions. Taking this line of argument a step further in this paper, we have aimed to computationally demonstrate the biological basis of the Black-Scholes functional form as applied to classical option pricing and hedging theory. The evolutionary optimality of the classical Black-Scholes function has been computationally established by means of a haploid genetic algorithm model. The objective was to minimize the dynamic hedging error for a portfolio of assets that is built to replicate the payoff from a European multi-asset option. The functional form that is seen to evolve over successive generations which best attains this optimization objective is the classical Black-Scholes function extended to a multiasset scenario.