Geographic Visualization in Archaeology

Archaeologists are often considered frontrunners in employing spatial approaches within the social sciences and humanities, including geospatial technologies such as geographic information systems (GIS) that are now routinely used in archaeology. Since the late 1980s, GIS has mainly been used to support data collection and management as well as spatial analysis and modeling. While fruitful, these efforts have arguably neglected the potential contribution of advanced visualization methods to the generation of broader archaeological knowledge. This paper reviews the use of GIS in archaeology from a geographic visualization (geovisual) perspective and examines how these methods can broaden the scope of archaeological research in an era of more user-friendly cyber-infrastructures. Like most computational databases, GIS do not easily support temporal data. This limitation is particularly problematic in archaeology because processes and events are best understood in space and time. To deal with such shortcomings in existing tools, archaeologists often end up having to reduce the diversity and complexity of archaeological phenomena. Recent developments in geographic visualization begin to address some of these issues, and are pertinent in the globalized world as archaeologists amass vast new bodies of geo-referenced information and work towards integrating them with traditional archaeological data. Greater effort in developing geovisualization and geovisual analytics appropriate for archaeological data can create opportunities to visualize, navigate and assess different sources of information within the larger archaeological community, thus enhancing possibilities for collaborative research and new forms of critical inquiry

EFFECTS OF BIOAVAILABILITY OF MACRONUTRIENTS ON OVERALL CONTROL OF PLASMA GLUCOSE: A REVIEW

Macronutrients play a crucial role in management of type 2 diabetes. This is seen in their ability to modulate plasma glucose concentrations. However, the ideal proportions of macronutrients to be consumed in order to maintain ideal plasma glucose concentrations remains elusive. Therefore, this paper set out to conduct a review to investigate the relationship between macronutrients and plasma glucose concentrations from a physiological perspective. The review was conducted using papers obtained from various databases such as MEDLINE (Pubmed), Open Access Journals Elsevier, Free Medical Journals and Google Scholar. The research papers included general reviews, systemic reviews, meta-analyses, and randomized control trials that examined the effect of macronutrients on plasma glucose concentration as well as papers on mathematical models describing the relationship between macronutrient bioavailability and plasma glucose concentration. The review assessed the effect of various macronutrients on postprandial plasma glucose concentration, post-prandial plasma insulin, post-prandial glucose-dependent insulinotropic peptide plasma concentration, and post-prandial glucose-like peptide-1 plasma concentration. The results of the review showed that carbohydrates influence plasma glucose concentration in a dose dependant manner but this is dependent on their bioavailability. This bioavailability was shown to be subject to fluctuations determined by food processing techniques, food structure, and food matrix. The results also showed that some specific types of fats and proteins indirectly influence plasma glucose concentration through their effect on incretin hormones. The effect of fats and proteins on incretin hormones was through different mechanisms and pathways. In-lieu of the findings, the review concludes that the macronutrient composition of diets designed for type 2 diabetic patients should take into consideration the physiological relationship between the macronutrients and plasma glucose concentrations. In this way, diet proportions can be made in such a manner as to determine the exact amounts that will realize near normal plasma glucose concentrations for a type 2 diabetic patient

MOVE: A Multi-Level Ontology-Based Visualization and Exploration Framework for Genomic Networks

Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e.g., proteins, genes). These interactions exist among others on genomic, transcriptomic, proteomic and metabolomic levels. The levels themselves are heavily interconnected, resulting in complex networks of different interacting biological entities. Currently, various bioinformatics tools exist which are able to perform a particular analysis on a particular type of network. Unfortunately, each tool has its own disadvantages hampering it to be used consistently for different types of networks or analytical methods. This paper describes the conceptual development of an open source extensible software framework that supports visualization and exploration of highly complex genomic networks, like metabolic or gene regulatory networks. The focus is on the conceptual foundations, starting from requirements, a description of the state of the art of network visualization systems, and an analysis of their shortcomings. We describe the implementation of some initial modules of the framework and apply them to a biological test case in bacterial regulation, which shows the relevance and feasibility of the proposed approach.