Aims Of Such Studies Research Articles

Application of Housen’s Model of Aesthetic Development in Higher Education: An Exploration of Cognitive Aspects during Art Appreciation

Studies in psychology of art appreciation have been conducted at different times since the beginning of 20th century. The aims of such studies include finding out audience experiences in viewing an artwork, whether it is more rational or emotional. However, there is an inadequate amount of evidence-based research conducted in Indonesia from which further studies can emanate. This paper aims to initiate evidence-based study on art appreciation for Indonesian population. Specifically, it investigates how the experience of art appreciation differs between Visual Art and Non-Visual Art students in an Art Psychology class of 2017/2018, at Bandung Institute of Technology (Mean Age=21.25, SD=0.66). This study draws on the actual end-of-semester exam using Housen’s model of aesthetic development. Data is analyzed using a comparative method informed by the model and scored using percentage and frequency to represent the proportion of valid corresponding responses. Main findings of this study highlight comparable experiences in art appreciation between Visual Art and Non-Visual Art students. The results correspond to the influence of exposure to art criticism and the Visual Art students’ rational approach to art appreciation. They also show that art appreciation enables students to exercise their cognitive aspects during meaning-making activities.

Evolution of callus tissue behavior during stable distraction osteogenesis.

Multiple studies have sought to characterize the mechanical behavior of callus tissue in vivo during distraction osteogenesis. The aims of such studies are to understand the mechanobiology of distraction and elucidate the complex viscoelasticity and evolution of the tissue. The former objective has direct clinical relevance to surgical technique and process control while the latter is necessary for the calibration and validation of the predictive healing models. Such models seek to reduce the researcher's dependence on animal studies and prospectively allow improved surgical planning. To date, no study has been capable of controlling the mechanical conditions sufficiently enough to decouple the distraction process from the secondary mechanical stimulation associated with the finite stiffness of the fixation constructs employed. It is the goal of this work to understand the mechanobiology of pure distraction as well as characterize viscoelastic tissue behavior under precisely defined mechanical conditions. This is achieved using a novel lateral distraction model. The structural integrity of the bone is maintained, allowing the collection of force relaxation data due to a stepwise distraction process without the superimposed influence of secondary mechanical stimulation. The average instantaneous modulus increases from approximately 2 kPa to approximately 1100 kPa while the equilibrium modulus increases from approximately 0 kPa to 200 kPa over the distraction period.

Getting to the Heart of the Matter.

Clinical proteomics involves the analysis of protein expression of disease proteomes, with the aim of solving a specific clinical problem. Discoveries made from proteomicbased studies contribute to the growing need for innovative medical diagnostics for disease detection. Taking into consideration the global health burden of cardiac disease, clinical proteomics is a valuable tool to improve risk stratification associated with this disease. In cardiovascular medicine, the identification of novel proteins, or biomarkers, that are differentially expressed in cardiac disease proteomes may enable early detection of the disease state, thereby preventing progression to disease end points. This review outlines various proteomic platforms and their technical advancements and relates these to the cardiovascular sciences. The entire protein complement of the cell, or proteome, is dynamic and changes in response to the disease state.1 Proteomic-based experiments can be used to characterize such alterations in protein expression during disease progression.2 With combined improvements in mass spectrometry (MS) technology as well as innovative molecular biology screening tools, there has been widespread growth in the characterization of cardiac disease proteomes. In fact, proteomic technology has been an important tool in the analysis of heart failure (HF),3,4 cardiac hypertrophy,5,6 and dilated cardiomyopathy.7 Several of the overarching aims of such studies include providing greater understanding of general biological mechanisms as well as identifying unique proteins that are clinically useful in the detection of cardiac disease in the early stages or potentially used as novel therapeutic targets. Clinical proteomics continues to benefit from advancements in technologies that allow for fast and consistent identification of proteins with corresponding increases in the dynamic range of proteins detectable in the disease proteome. MS-related technologies have improved in their ability to detect low-abundance proteins as well as membrane proteins and have benefited from sample preprocessing strategies that decrease the complexity of large-scale analyses. With the emergence of different methodologies for biomarker identification, the following 3 criteria must be taken into careful consideration to determine whether the protein is, in fact, clinically useful: (1) the protein must be easily measurable at a reasonable cost, (2) elevation of the protein would provide information not present in the absence of the protein, and (3) information obtained would guide the medical decisionmaking process.8 Satisfaction of these criteria sets the stage for further analysis in large patient cohort samples, the next step in biomarker validation. Over the past several decades, the field of proteomic research has grown considerably, yet central to most proteomic studies remains the identification of maximal proteins with increased specificity and sensitivity, the identification of protein complexes, and the precise mapping of posttranslational protein modifications.1 Traditionally, gel-based approaches have been used to uncover abnormal protein expression patterns with considerable success. However, some traditional gel-based approaches, such as 2D gel electrophoresis (2DE), tend to suffer from limitations largely related to comprehensive protein identifications, which can be partially addressed using gel-free techniques. With the development of increasingly powerful instruments capable of increasingly accurate analysis and greatly improved separation methods9,10 and experimental design,11 the field of proteomics continues to grow, and innovations in research and development will augment previous proteomic profiling experiments.

Gene-Environment Interaction

With the advent of increasingly accessible technologies for typing genetic variation, studies of gene-environment (G×E) interactions have proliferated in psychological research. Among the aims of such studies are testing developmental hypotheses and models of the etiology of behavioral disorders, defining boundaries of genetic and environmental influences, and identifying individuals most susceptible to risk exposures or most amenable to preventive and therapeutic interventions. This research also coincides with the emergence of unanticipated difficulties in detecting genetic variants of direct association with behavioral traits and disorders, which may be obscured if genetic effects are expressed only in predisposing environments. In this essay we consider these and other rationales for positing G×E interactions, review conceptual models meant to inform G×E interpretations from a psychological perspective, discuss points of common critique to which G×E research is vulnerable, and address the role of the environment in G×E interactions.

Clinical Proteomics

Clinical proteomics involves the analysis of protein expression of disease proteomes, with the aim of solving a specific clinical problem. Discoveries made from proteomicbased studies contribute to the growing need for innovative medical diagnostics for disease detection. Taking into consideration the global health burden of cardiac disease, clinical proteomics is a valuable tool to improve risk stratification associated with this disease. In cardiovascular medicine, the identification of novel proteins, or biomarkers, that are differentially expressed in cardiac disease proteomes may enable early detection of the disease state, thereby preventing progression to disease end points. This review outlines various proteomic platforms and their technical advancements and relates these to the cardiovascular sciences. The entire protein complement of the cell, or proteome, is dynamic and changes in response to the disease state. 1 Proteomic-based experiments can be used to characterize such alterations in protein expression during disease progression. 2 With combined improvements in mass spectrometry (MS) technology as well as innovative molecular biology screening tools, there has been widespread growth in the characterization of cardiac disease proteomes. In fact, proteomic technology has been an important tool in the analysis of heart failure (HF), 3,4 cardiac hypertrophy, 5,6 and dilated cardiomyopathy.7 Several of the overarching aims of such studies include providing greater understanding of general biological mechanisms as well as identifying unique proteins that are clinically useful in the detection of cardiac disease in the early stages or potentially used as novel therapeutic targets. Clinical proteomics continues to benefit from advancements in technologies that allow for fast and consistent identification of proteins with corresponding increases in the dynamic range of proteins detectable in the disease proteome. MS-related technologies have improved in their ability to detect low-abundance proteins as well as membrane proteins and have benefited from sample preprocessing strategies that decrease the complexity of large-scale analyses. With the emergence of different methodologies for biomarker identification, the following 3 criteria must be taken into careful consideration to determine whether the protein is, in fact,

Developing EPIC markers for chalcidoid Hymenoptera from EST and genomic data

Increasing numbers of phylogeographic studies make comparative inferences about the histories of co-distributed species. Although the aims of such studies are best achieved by jointly analysing sequences from multiple loci in a model-based framework, such data currently exist for few nonmodel systems. We used existing genomic data and expressed sequence tags (ESTs) for Hymenoptera and other insects to design intron-crossing primers for 40 loci, mainly ribosomal proteins, for chalcidoid parasitoids. Amplification success was scored on a range of taxa associated with two natural communities; oak galls and figs. Taxa were chosen at increasing distance from Nasonia, which was used for primer design, (i) within Pteromalids, (ii) within Chalcidoidea (Eupelmidae, Eulophidae, Eurytomidae, Ormyridae, Torymidae) and (iii) for a selection of distantly related gall and fig wasps (Cynipidae, Agaonidae). To assess the utility of these loci for phylogeographic and population genetic studies, we compared genetic diversity between Western Palaearctic refugia for two species. Our results show that it is feasible to design a large number of exon-primed-intron-crossing (EPIC) loci that may be informative about phylogeographic history within species but amplify across a large taxonomic range.

Les gènes modificateurs dans la mucoviscidose

Cystic fibrosis is the most common lethal autosomal recessive disease among the Caucasian population. It is caused by defects in the CFTR gene (Cystic Fibrosis Transmembrane Conductance Regulator). Although over 1600 disease-causing mutations in the CFTR gene have been described, the highly variable disease phenotype in cystic fibrosis cannot be explained on the basis of this gene alone. Both the environment and other non-CFTR genes are likely to be important. The increased understanding of pathophysiological processes in the cystic fibrosis lung has led to several studies on genes in these pathways. One of the major aims of such studies is to produce targets for novel drug developments.

Modifier genes in cystic fibrosis

Although over 1,000 disease-causing mutations in the CFTR gene have been described, the highly variable disease phenotype in cystic fibrosis (CF) cannot be explained on the basis of this gene alone. Both the environment and other non-CFTR genes are likely to be important. The increased understanding of pathophysiological processes in the CF lung has led to several studies on genes in these pathways, including those involved in host defense, mucin production, and airway responsiveness. Additionally, candidate modifiers of the gastrointestinal manifestations of CF have been explored. One of the major aims of such studies is to produce targets for novel drug developments. This review will summarize the field to date and discuss some of the methodological issues important in the design and interpretation of such studies.

The Role of the Robustness/Ruggedness and Inertia Studies in Research and Development of Analytical Processes

The knowledge of the robustness/ruggedness of analytical processes is an essential feature in the analytical validation. The definitions and the different aims of such studies are given. A dual general procedure for checking robustness/ruggedness in both intrinsic and extrinsic validation is presented and the different steps are discussed. The denomination of “inertia study” is introduced to designate this methodology in extrinsic validation and precision and trueness tests are proposed inside the inertia study. Several experimental designs, depending on the goal of robustness/ruggedness study and the type of variables (quantitative or qualitative) are considered.

1. Energy costs: a review of methods

Forecasts of energy shortages were already stimulating analyses of patterns or energy consumption before the quadrupling of oil prices and the interruption in supplies. These recent events have made such studies urgent. In this article — the first in a series on energy budgets — Dr Chapman examines the problems in constructing energy costs, the aims of such studies and the methods used. These are illustrated by examples of energy costs which indicate the care required in interpreting and using published results.

A New Analytical Derivation of Kernels in the Resonating Group Method for Composite-Particle Scattering and Molecule-Like Structures: Derivation from Kernels in the Generator Coordinate Method and Application to 16O +

Exchange kernels in the resonating group method are derived analytically from those in the generator coordinate method without any use of inverse operators of Gauss transforma­ tion. The whole kernels of 160+a system with Coulomb interaction are given, divided into various exchange mechanisms. Derivation in the cases where two interacting nuclei have different oscillator parameters and where other channels are included is also presented. § I. Introduction The cluster structure and molecular aspect in nuclei have been studied ex­ tensively in terms of interaction between composite particles. 1l Recently, many attempts based on phenomenological and microscopic approaches have been made with the progress of experiments on composite-particle scattering and cluster transfer reactions. 2l It must be one of the main aims of such studies to investi­ gate the microscopic mechanism of interaction between composite nuclei by em­ ploying the many-body Hamiltonian and taking into account the Pauli principle exactly. The resonating group method3l (RGM) ·is very powerful to this aim. For instance, on the basis of the RGM a deep understanding was obtained concern­ ing the origin of the repulsive core of phenomenological a-a potential as a model representation of the existence of almost energy-independent behaviour of the nodal point.'l Saito 5l showed that the behaviour is understood as a result of or­ thogonality of the relative wave function to forbidden states and proposed an orthogonality condition model which describes the inner part of interaction be­ tween composite particles with the orthogonality condition and the outer part with a direct potential. This approximated model has obtained successful results for a-a scattering 5l' 6l and for a-decay widths of 160 +a system.7l Although the RGM approach is very powerful in extracting physical understandings from it­ self, its application to a system heavier than a+ a has been generally regarded as very much difficult.