A Modified Real-Coded Genetic Algorithm Considering with Fitness-based Variability

A genetic algorithm (GA) is a search algorithm based on the mechanism of natural genetics. In various GAs, a real-coded GA (RCGA) employing individuals represented by real valued-genes has been proposed to solve the optimization problem in the continuous searching space. However, the conventional RCGA yields ineffective searches due to insufficient genetic diversity in the selection process. In this paper, we propose a modified RCGA with variability operator maintaining the genetic diversity of the population. In the proposed method, a variability term is newly added to the individuals selected by the ordinary selection. The degree of the variability is decided considering the fitness value of the individual. The searching performance of the proposed method is better than the conventional methods. The effectiveness and the validity of the proposed method are verified by applying it to optimization problems of continuous benchmark functions and signal sources localization

Mitigating Voter Attribute Bias for Fair Opinion Aggregation

The aggregation of multiple opinions plays a crucial role in decision-making, such as in hiring and loan review, and in labeling data for supervised learning. Although majority voting and existing opinion aggregation models are effective for simple tasks, they are inappropriate for tasks without objectively true labels in which disagreements may occur. In particular, when voter attributes such as gender or race introduce bias into opinions, the aggregation results may vary depending on the composition of voter attributes. A balanced group of voters is desirable for fair aggregation results but may be difficult to prepare. In this study, we consider methods to achieve fair opinion aggregation based on voter attributes and evaluate the fairness of the aggregated results. To this end, we consider an approach that combines opinion aggregation models such as majority voting and the Dawid and Skene model (D&S model) with fairness options such as sample weighting. To evaluate the fairness of opinion aggregation, probabilistic soft labels are preferred over discrete class labels. First, we address the problem of soft label estimation without considering voter attributes and identify some issues with the D&S model. To address these limitations, we propose a new Soft D&S model with improved accuracy in estimating soft labels. Moreover, we evaluated the fairness of an opinion aggregation model, including Soft D&S, in combination with different fairness options using synthetic and semi-synthetic data. The experimental results suggest that the combination of Soft D&S and data splitting as a fairness option is effective for dense data, whereas weighted majority voting is effective for sparse data. These findings should prove particularly valuable in supporting decision-making by human and machine-learning models with balanced opinion aggregation

Rapid preparation of mutated influenza hemagglutinins for influenza virus pandemic prevention

Influenza viruses have periodically caused pandemic due to frequent mutation of viral proteins. Influenza viruses have two major membrane glycoproteins: hemagglutinin (HA) and neuraminidase (NA). Hemagglutinin plays a crucial role in viral entry, while NA is involved in the process of a viral escape. In terms of developing antiviral drugs, HA is a more important target than NA in the prevention of pandemic, since HA is likely to change the host specificity of a virus by acquiring mutations, thereby to increase the risk of pandemic. To characterize mutated HA functions, current approaches require immobilization of purified HA on plastic wells and carriers. These troublesome methods make it difficult to respond to emerging mutations. In order to address this problem, a yeast cell surface engineering approach was investigated. Using this technology, human HAs derived from various H1N1 subtypes were successfully and rapidly displayed on the yeast cell surface. The yeast-displayed HAs exhibited similar abilities to native influenza virus HAs. Using this system, human HAs with 190E and 225G mutations were shown to exhibit altered recognition specificities from human to avian erythrocytes. This system furthermore allowed direct measurement of HA binding abilities without protein purification and immobilization. Coupled with the ease of genetic manipulation, this system allows the simple and comprehensive construction of mutant protein libraries on yeast cell surface, thereby contributing to influenza virus pandemic prevention

Unsaturated slopes behavior under antecedent intermittent rainfall patterns: centrifuge and numerical study

Antecedent rainfall is a prime factor for rainfall-induced landslides on unsaturated slopes. The effects of the intermittent behavior of antecedent rainfall on landslide initiation are uncertain. The work described here had the objective of showing the influence of antecedent intermittent rainfall patterns to predict landslide initiation. Soil slope models prepared from silty sand were tested in centrifuge model testing. At first, soil slopes experienced different antecedent rainfall patterns, namely, uniform gap, decreasing gap, and increasing gap, before they were exposed to continuous rainfall until the failure was initiated. The seepage and deformation behaviors of instrumented slopes were evaluated and back-analyzed with soil–water–air coupled hydromechanical finite element analysis using calibrated material parameters and suitable boundary conditions. The evolution of porewater pressure, displacements, and deviatoric strains was found to provide comparable responses. The analysis of incremental velocity clearly showed that times for landslide initiation follow the order of decreasing gap, uniform gap, and increasing gap antecedent rainfall patterns. The study identified that not only cumulative rainfall, but also antecedent intermittent rainfall patterns have a significant effect as a triggering agent and suggested incorporating it as a parameter for landslide early warning mechanisms

A novel A792D mutation in the CSF1R gene causes hereditary diffuse leukoencephalopathy with axonal spheroids characterized by slow progression

Hereditary diffuse leukoencephalopathy with spheroids (HDLS) is an autosomal dominant white matter disease that causes adult-onset cognitive impairment. The clinical manifestations are a variable combination of personality and behavioral changes, cognitive decline, parkinsonism, spasticity, and epilepsy. In 2012, mutations in the gene encoding colony stimulating factor 1 receptor (CSF1R) were identified as the cause of HDLS. As the numbers of reported mutations are limited, the understanding of whole pathogenesis needs accumulation of disease-causing mutations with detailed clinical descriptions. We describe a Japanese family with autosomal dominant adult-onset cognitive impairment and characteristic white matter lesions. Genetic testing revealed a novel p.A792D mutation in the tyrosine kinase domain of CSF1R in two affected family members. The symptom profile of the present cases mostly matched the previously reported cases, with the notable exceptions of late-onset and long disease duration

Our Stolen Sustainability Unsafe Eden Contaminated by Environmental Hormones

When we speak of sustainable development in the context of modern society, what does it actually mean? Here we would like to address the issue of environmental contamination and explore the conditions required to move toward human coexistence and symbiosis with the natural environment. Studying the effect of ‘environmental hormones’ and endocrine disruptors on the ecosystem, Theo Colborn confirmed the risk of ‘brain contamination’ through the food chain and ‘bio-accumulation’. The contamination of the ecosphere by environmental hormones - an issue which no modern human can avoid - is a ‘negative legacy’ contrasting with the economic wealth brought by modern rationality. In this article, we consider the role of the environmental ethics which societies and individuals will be required to practice in the near future and examines the role of ‘environmental management’ as a preventive policy carrying the morality of the modern organization