Composite SaaS scaling in cloud computing using a hybrid genetic algorithm

A Software-as-a-Service or SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. Components in a composite SaaS may need to be scaled – replicated or deleted, to accommodate the user’s load. It may not be necessary to replicate all components of the SaaS, as some components can be shared by other instances. On the other hand, when the load is low, some of the instances may need to be deleted to avoid resource underutilisation. Thus, it is important to determine which components are to be scaled such that the performance of the SaaS is still maintained. Extensive research on the SaaS resource management in Cloud has not yet addressed the challenges of scaling process for composite SaaS. Therefore, a hybrid genetic algorithm is proposed in which it utilises the problem’s knowledge and explores the best combination of scaling plan for the components. Experimental results demonstrate that the proposed algorithm outperforms existing heuristic-based solutions.

Genetic technologies and the regulation of reproductive decision-making in Australia

This article provides a critical analysis of the current Australian regulatory landscape at the interface between genetics and reproductive decision- making. The authors argue that a comparative analysis with other countries and international law and a contextual examination of the way law regulates concepts such as disease and health, abnormality and normality is necessary before we can develop appropriate policy and legislative responses in this area. Specific genetic testing technologies are considered including prenatal genetic testing, preimplantation genetic diagnosis and inheritable genetic modification. An increasing number of members of the Australian community are using genetic testing technologies when they decide to have a baby. The authors argue that as concepts of disease and health vary among members of the community and the potential to test for traits other than illness increases, a new tension arises between an ethic of individual choice and a role for government in regulating reproductive decision-making.

Genetic secrets and the family

The issue of how individual patients and their doctors should act in relation to the knowledge that the patient has a genetic condition— specifically, whether the patient and/or the doctor should or must inform relevant members of the patient’s family—is a looming area of medicolegal controversy. Over the last fifteen years or so, the issue of confidentiality versus disclosure has been particularly controversial in relation to HIV/AIDS patients.1 It has been argued that medical information about genetic disease gives rise to special problems vis-à-vis blood relatives. Because genetic disease is transmitted only by way of procreation, information about genetic disease is unique in that there is a propensity (which is highly variable and depends upon a variety of factors) for the condition to be shared by members of a family who are biologically related. Thus, genetic information about an individual may reveal information about relatives of that individual which is ‘specific (that the person has or will develop a genetic disease); or predictive (that the person has an unspecified risk of developing the disease)’

Perturbing event logs to identify cost reduction opportunities: a genetic algorithm-based approach

Organisations are constantly seeking new ways to improve operational efficiencies. This research study investigates a novel way to identify potential efficiency gains in business operations by observing how they are carried out in the past and then exploring better ways of executing them by taking into account trade-offs between time, cost and resource utilisation. This paper demonstrates how they can be incorporated in the assessment of alternative process execution scenarios by making use of a cost environment. A genetic algorithm-based approach is proposed to explore and assess alternative process execution scenarios, where the objective function is represented by a comprehensive cost structure that captures different process dimensions. Experiments conducted with different variants of the genetic algorithm evaluate the approach's feasibility. The findings demonstrate that a genetic algorithm-based approach is able to make use of cost reduction as a way to identify improved execution scenarios in terms of reduced case durations and increased resource utilisation. The ultimate aim is to utilise cost-related insights gained from such improved scenarios to put forward recommendations for reducing process-related cost within organisations.

Genetic susceptibility to environmental toxicants : the interface between human and experimental studies in the development of new toxicological concepts

The growing knowledge of the genetic polymorphisms of enzymes metabolising xenobiotics in humans and their connections with individual susceptibility towards toxicants has created new and important interfaces between human epidemiology and experimental toxicology. The results of molecular epidemiological studies may provide new hypotheses and concepts, which call for experimental verification, and experimental concepts may obtain further proof by molecular epidemiological studies. If applied diligently, these possibilities may be combined to lead to new strategies of human-oriented toxicological research. This overview will present some outstanding examples for such strategies taken from the practically very important field of occupational toxicology. The main focus is placed on the effects of enzyme polymorphisms of the xenobiotic metabolism in association with the induction of bladder cancer and renal cell cancer after exposure to occupational chemicals. Also, smoking and induction of head and neck squamous cell cancer are considered.

Subclinical psychotic experiences in healthy young adults : associations with stress and genetic predisposition

Stress has been identified as a common trigger for psychosis. Dopamine pathways are suggested to be affected by chronic and severe stress and to play an important role in psychosis. This pilot study investigates the potential relationship of stress and psychosis in subclinical psychotic experiences. It was hypothesized that single-nucleotide polymorphisms (SNPs) previously found to be associated with psychiatric disorders would be associated with both stress and subclinical psychotic experiences. University students (N=182) were genotyped for 17 SNPs across 11 genes. Higher stress reporting was associated with rs4680 COMT, rs13211507 HLA region, and rs13107325 SLC39A8. Reports of higher subclinical psychotic experiences were associated with DRD2 SNPs rs17601612 and rs658986 and an AKT1 SNP rs2494732. Replication studies are recommended to further pursue this line of research for identification of markers of psychosis for early diagnosis and intervention.

Use of genetic decompositions to scaffold the development of a structurally sequenced curriculum for mathematics acceleration

The authors have collaboratively used a graphical language to describe their shared knowledge of a small domain of mathematics, which has in turn scaffolded their re-development of a related curriculum for mathematics acceleration. This collaborative use of the graphical language is reported as a simple descriptive case study. This leads to an evaluation of the graphical language’s usefulness as a tool to support the articulation of the structure of mathematics knowledge. In turn, implications are drawn for how the graphical language may be utilised as the detail of the curriculum is further elaborated and communicated to teachers.

The future for genetic studies in reproduction

Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies(GWAS) have revolutionized gene discovery forcommontraits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases.GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

Molecular genetic investigation of mitochondrial dysfunction in relation to migraine susceptibility

The aim of this research was to assess the role of genetic variation in mitochondrial function and how this relates to migraine pathophysiology. Using our unique Norfolk Island population, a custom in-house next generation sequencing methodology was developed. This data for the first time showed that there is a molecular genetic link between mitochondrial dysfunction and migraine susceptibility. This work has provided the foundation for further studies aimed at utilising the identified markers in improved migraine diagnostic and therapeutic strategies.

A new approach to kimberlite facies terminology using a revised general approach to the nomenclature of all volcanic rocks and deposits: Descriptive to genetic

Although kimberlite pipes/bodies are usually the remains of volcanic vents, in-vent deposits, and subvolcanic intrusions, the terminology used for kimberlite rocks has largely developed independently of that used in mainstream volcanology. Existing kimberlite terminology is not descriptive and includes terms that are rarely used, used differently, and even not used at all in mainstream volcanology. In addition, kimberlite bodies are altered to varying degrees, making application of genetic terminology difficult because original components and depositional textures are commonly masked by alteration. This paper recommends an approach to the terminology for kimberlite rocks that is consistent with usage for other volcanic successions. In modern terrains the eruption and emplacement origins of deposits can often be readily deduced, but this is often not the case for old, variably altered and deformed rock successions. A staged approach is required whereby descriptive terminology is developed first, followed by application of genetic terminology once all features, including the effects of alteration on original texture and depositional features, together with contact relationships and setting, have been evaluated. Because many volcanic successions consist of both primary volcanic deposits as well as volcanic sediments, terminology must account for both possibilities.

Genetic and environmental influences on neuroimaging phenotypes: A meta-analytical perspective on twin imaging studies

Because brain structure and function are affected in neurological and psychiatric disorders, it is important to disentangle the sources of variation in these phenotypes. Over the past 15 years, twin studies have found evidence for both genetic and environmental influences on neuroimaging phenotypes, but considerable variation across studies makes it difficult to draw clear conclusions about the relative magnitude of these influences. Here we performed the first meta-analysis of structural MRI data from 48 studies on >1,250 twin pairs, and diffusion tensor imaging data from 10 studies on 444 twin pairs. The proportion of total variance accounted for by genes (A), shared environment (C), and unshared environment (E), was calculated by averaging A, C, and E estimates across studies from independent twin cohorts and weighting by sample size. The results indicated that additive genetic estimates were significantly different from zero for all metaanalyzed phenotypes, with the exception of fractional anisotropy (FA) of the callosal splenium, and cortical thickness (CT) of the uncus, left parahippocampal gyrus, and insula. For many phenotypes there was also a significant influence of C. We now have good estimates of heritability for many regional and lobar CT measures, in addition to the global volumes. Confidence intervals are wide and number of individuals small for many of the other phenotypes. In conclusion, while our meta-analysis shows that imaging measures are strongly influenced by genes, and that novel phenotypes such as CT measures, FA measures, and brain activation measures look especially promising, replication across independent samples and demographic groups is necessary.

Mapping genetic influences on ventricular structure in twins

Despite substantial progress in measuring the anatomical and functional variability of the human brain, little is known about the genetic and environmental causes of these variations. Here we developed an automated system to visualize genetic and environmental effects on brain structure in large brain MRI databases. We applied our multi-template segmentation approach termed "Multi-Atlas Fluid Image Alignment" to fluidly propagate hand-labeled parameterized surface meshes, labeling the lateral ventricles, in 3D volumetric MRI scans of 76 identical (monozygotic, MZ) twins (38 pairs; mean age = 24.6 (SD = 1.7)); and 56 same-sex fraternal (dizygotic, DZ) twins (28 pairs; mean age = 23.0 (SD = 1.8)), scanned as part of a 5-year research study that will eventually study over 1000 subjects. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps, derived from path analysis, revealed patterns of heritability, and their significance, in 3D. Path coefficients for the 'ACE' model that best fitted the data indicated significant contributions from genetic factors (A = 7.3%), common environment (C = 38.9%) and unique environment (E = 53.8%) to lateral ventricular volume. Earlier-maturing occipital horn regions may also be more genetically influenced than later-maturing frontal regions. Maps visualized spatially-varying profiles of environmental versus genetic influences. The approach shows promise for automatically measuring gene-environment effects in large image databases.

Genetic evidence for natural hybridization between Red Snow Crab (Chionoecetes japonicus) and Snow Crab (Chionoecetes opilio) in Korea

Both red snow crab (Chionoecetes japonicus Rathbun, 1932) and snow crab (Chionoecetes opilio Fabricius, 1788) are commercially important species in Korea. The geographical ranges of the two species overlap in the East Sea, where both species are fished commercially. Morphological identification of the two species and putative hybrids can be difficult because of their overlapping morphological characteristics. The presence of putative hybrids can affect the total allowable catch (TAC) of C. japonicus and C. opilio, and causes problems managing C. japonicus and C. opilio wild resources. To date, however, no natural hybridization has been reported between C. japonicus and C. opilio, despite their overlapping distributions along the coast of the East Sea. In this study, the internal transcribed spacer (ITS) region of major ribosomal RNA genes from the nuclear genome and the cytochrome oxidase I (CO I) gene from the mitochondrial genome were sequenced to determine whether natural hybridization occurs between the two species. Our results revealed that all putative hybrids identified using morphological traits had two distinct types of ITS sequences corresponding to those of both parental species. Mitochondrial CO I gene sequencing showed that all putative hybrids had sequences identical to C. japonicus. A genotyping assay based on single nucleotide polymorphisms in the ITS1 region and the CO I gene produced the most efficient and accurate identification of all hybrid individuals. Molecular data clearly demonstrate that natural hybridization does occur between C. japonicus and C. opilio, but only with C. japonicus as the maternal parent.

Using genetic algorithm in profile-based assignment of applications to virtual machines for greener data centers

The increase in data center dependent services has made energy optimization of data centers one of the most exigent challenges in today's Information Age. The necessity of green and energy-efficient measures is very high for reducing carbon footprint and exorbitant energy costs. However, inefficient application management of data centers results in high energy consumption and low resource utilization efficiency. Unfortunately, in most cases, deploying an energy-efficient application management solution inevitably degrades the resource utilization efficiency of the data centers. To address this problem, a Penalty-based Genetic Algorithm (GA) is presented in this paper to solve a defined profile-based application assignment problem whilst maintaining a trade-off between the power consumption performance and resource utilization performance. Case studies show that the penalty-based GA is highly scalable and provides 16% to 32% better solutions than a greedy algorithm.