Tool For Exploratory Research Research Articles

An Observational Study on Cephalometric Characteristics and Patterns Associated with the Prader–Willi Syndrome: A Structural Equation Modelling and Network Approach

Examining specific patterns of major cranio-facial alterations through cephalometric measurements in order to improve the Prader–Willi (PWS) syndrome diagnostic poses a major challenge of identifying interlinkages between numerous credentials. These interactions can be captured through probabilistic models of conditional independence between heterogeneous variables. Our research included 18 subjects (aged 4 to 28 years) genetically diagnosed with Prader–Willi syndrome and a healthy control group (matched age and sex). A morphometric and cephalometric analysis was performed upon all the subjects in order to obtain the needed specific data. We have, therefore, firstly deployed several integrated Gaussian graphical models (GGMs) to capture the positive and negative partial correlations and the intensity of the connections between numerous credentials configured to determine specific cranio-facial characteristics of patients with PWS compared to others without this genetic disorder (case-control analysis). Afterwards, we applied structural equation modelling (SEM) with latent class analysis to assess the impact of these coordinates on the prevalence of the Prader–Willi diagnostic. We found that there are latent interactions of features affected by external variables, and the interlinkages are strapping particularly between cranial base (with an important role in craniofacial disharmonies) and facial heights, as important characteristic patterns in determining the Prader–Willi diagnostic, while the overall patterns are significantly different in PWS and the control group. These results impact the field by providing an enhanced comprehensive perspective on cephalometric characteristics and specific patterns associated with Prader–Willi syndrome that can be used as benchmarks in determining the diagnostic of this rare genetic disorder. Furthermore, the two innovative exploratory research tools applied in this paper are very useful to the craniofacial field to infer the connections/dependencies between variables (particularly biological variables and genes) on cephalometric characteristics and specific patterns associated with Prader–Willi syndrome.

Wireless and battery-free platforms for collection of biosignals

Recent progress in biosensors have quantitively expanded current capabilities in exploratory research tools, diagnostics and therapeutics. This rapid pace in sensor development has been accentuated by vast improvements in data analysis methods in the form of machine learning and artificial intelligence that, together, promise fantastic opportunities in chronic sensing of biosignals to enable preventative screening, automated diagnosis, and tools for personalized treatment strategies. At the same time, the importance of widely accessible personal monitoring has become evident by recent events such as the COVID-19 pandemic. Progress in fully integrated and chronic sensing solutions is therefore increasingly important. Chronic operation, however, is not truly possible with tethered approaches or bulky, battery-powered systems that require frequent user interaction. A solution for this integration challenge is offered by wireless and battery-free platforms that enable continuous collection of biosignals. This review summarizes current approaches to realize such device architectures and discusses their building blocks. Specifically, power supplies, wireless communication methods and compatible sensing modalities in the context of most prevalent implementations in target organ systems. Additionally, we highlight examples of current embodiments that quantitively expand sensing capabilities because of their use of wireless and battery-free architectures.

“Impact of financial literacy and Risk Tolerance on Investment Decision”

Researcher has followed a widespread approach for explain the relationship between financial literacy, risk tolerance and investment decision. Recently there has been increasing interest in studying the behaviors of investors and the factors which affecting the investment decisions of investors due to a synchronized approached followed by a large number of investors. A Study has been shown that a large number of investors look after the safety of their money not higher return.[1] Investment decision is a crucial decision which is influenced by various factors as financial literacy, income level, financial soundness and various other demographic and sociological factors. The choice of investment alternative of is broadly depends upon the risk tolerance level of investors.[2] On the basis of certain conclusion, cover from precious research, the researcher in this study defines the relationship between financial literacy, risk tolerance and financial decision making of investors through exploratory research tools. For explaining this relationship researcher gives a mediation model. By using this mediation model a direct relationship between Financial Literacy and Risk Tolerance and between Financial Literacy and Investment Decision via Risk Tolerance, can be explored.

The Effect of Using Art Activities in Improving Artistic Talent of Kindergarten Children

The current research aims at designing a program based on using artistic activities and identifying its effect on improving the artistic talent of kindergarten children. The researcher utilized the experimental research methodology with the semi-experimental design of one group through conducting pre/post measurements. The research community was children enrolled in kindergartens of El-Minia Governorate, the academic year 2018/2019; whose ages ranged between 5-6 years old. The researcher selected the research sample randomly from one kindergarten. The exploratory research tool (Raven for successive Matrices) was applied to identify artistically talented children. Based on the results obtained, the sample was selected according to the highest quadrant in the Raven test which consisted of (32) children. For data collection, the researcher used Raven's Colored Sequence Arrays Test (to measure intelligence), artistic talent test for children (Prepared by the researcher) and the artistic activities program for kindergarten children (prepared by the researcher). The most significant results of the current research revealed the positive effect of the program based on artistic activities on developing artistic talent among kindergarten children as a training and rehabilitation approach.

Toward a “Text as Data” Approach in the History and Methodology of Economics: An Application to Adam Smith’s Classics

The fields of the history and methodology of economics have recently experienced a quantitative turn. Among the quantitative tools and methods recently used, text mining has received less attention. In this article, we apply a “text as data” approach to the study of Adam Smith’s The Wealth of Nations and The Theory of Moral Sentiments. We first study these two classics through the lenses of readability and lexical richness indicators and sentiment analysis. We then determine the most relevant words and topics in the two books and, as case studies, we examine the specific topics of opulence, poverty, prosperity, sympathy, tax, war, wealth, and woman. Our results confirm some of the well-known differences between the two books (thus supporting the argument that text mining is a powerful and generally reliable tool for exploratory research on unknown documents), but also provide new insights about them.

Exploring teachers’ perceptions of implementation factors in a yoga intervention: a qualitative study

ABSTRACT The study of yoga offers much to the field of education. Yoga consists of postures, breathing activities and relaxation techniques geared toward promoting self-regulation. Several yoga interventions for preschoolers have demonstrated significant gains on self-regulation outcomes. Although these benefits are promising, there are limited qualitative studies investigating the perspectives of key stakeholders, such as teachers. Using a grounded theory research design, the author analyzed eight focus groups and six interviews with nine teachers who participated in an 8-week yoga intervention. This study investigated (1) the application of grounded theory as an exploratory research tool, which elucidated teachers’ observations of key implementation factors for effectiveness, such as adaptations of the intervention, classroom spacing and components of yoga lessons, (2) teachers’ observations of students’ internalizations of the yoga skills and (3) teachers’ reflections on how the yoga influenced their attitudes toward students. Guidelines to inform future research on classroom-based yoga programs are discussed.

How geoengineering scenarios frame assumptions and create expectations

Geoengineering could remake environments and societies, and early governance can help to steer the development of technologies towards sustainable outcomes. In the absence of observational data, geoengineering research and discussions are increasingly informed by scenarios, which provide heuristic tools for ‘envisioning’ potential futures. Although designed for specific research goals, scenarios can have broader implications by influencing expectations about the societal role that emerging geoengineering technologies can play. Yet the design of geoengineering scenarios has gone largely unscrutinized. This study is a meta-analysis in which we evaluate geoengineering scenarios from the literature to identify emerging expectations and assess these in the context of sustainability science. We find that geoengineering scenarios can be classified into three types based on purpose and use: for scientific knowledge-building; as ‘structured conversation’ starters; or as exploratory research tools. The first category dominates the literature; these scenarios stem from physical science disciplines where scientific tradition dictates simplification and standardization, both of which may provide misleading images of the future and therefore hinder robust decision-making. In contrast, scenarios used as exploratory tools depict not one single image of why and how geoengineering might evolve, but many. Analysis of these exploratory scenarios reveal expectations that a geoengineered future may hinge on at least four key elements—the potential for a universal geoengineering agreement, public perceptions of geoengineering, technical controllability, and the severity of climate impacts. These elements were not studied in the scientific knowledge-building scenarios, suggesting the need for an additional category of scenarios. Aligning with concepts of sustainability science, new geoengineering scenario exercises would merge participatory practices of exploratory scenarios with deterministic practices of technical scientific scenarios.

Exploring Curvilinearity Through Fractional Polynomials in Management Research

Imprecise theories do not give enough guidelines for empirical analyses. A paradigmatic shift from linear to curvilinear relationships is necessary to advance management theories. Within the framework of the abductive generation of theories, the authors present a data exploratory technique for the identification of functional relationships between variables. Originating in medical research, the method uses fractional polynomials to test for alternative curvilinear relationships. It is a compromise between nonparametric curve fitting and conventional polynomials. The multivariable fractional polynomial (MFP) technique is a good tool for exploratory research when theoretical knowledge is nonspecific and thus very useful in phenomena discovery. The authors conduct simulations to demonstrate MFP’s performance in various scenarios. The technique’s major benefit is the uncovering of nontraditional shapes that cannot be modeled by logarithmic or quadratic functions. While MFP is not suitable for small samples, there does not seem to be a downside of overfitting the data as the fitted curves are very close to the true ones. The authors call for a routine application of the procedure in exploratory studies involving medium to large sample sizes.

Phase Classification by Mean Shift Clustering of Multispectral Materials Images

A mean-shift clustering (MSC) algorithm is introduced as a valuable alternative to perform materials phase classification from multispectral images. As opposed to other multivariate statistical techniques, such as factor analysis or principal component analysis (PCA), clustering techniques directly assign a class label to each pixel, so that their outputs are phase segmented images, i.e., there is no need for an additional segmentation algorithm. On the other hand, as compared to other clustering procedures and classification methods, such as segmentation by thresholding of multiple spectral components, MSC has the advantages of not requiring previous knowledge of the number of data clusters and not assuming any shape for these clusters, i.e., neither the number nor the composition of the phases must be previously known. This makes MSC a particularly useful tool for exploratory research, assisting phase identification of unknown samples. Visualization and interpretation of the results are also simplified, since the information content of the output image does not depend on the particular choice of the content of the color channels.We applied MSC to the analysis of two sets of X-ray maps acquired in scanning electron microscopes equipped with energy-dispersive detection systems. Our results indicate that MSC is capable of detecting additional phases, not clearly identified through PCA or multiple thresholding, with a very low empirical reject rate.

Beyond consensus: an alternative use of Delphi enquiry in hospitality research

PurposeThis paper's aim is to critically review the use of Delphi techniques in qualitative research for utilising “expert” opinions and to explore through a detailed example how Policy Delphi can be used by hospitality researchers as an alternative to the more widely used Normative Delphi.Design/methodology/approachThe paper reflects on the research methodology of a project that explored organisational crisis signals detection using Policy Delphi with a criterion sample comprising 16 senior hotel executives involved in crisis management.FindingsThe main methodological concerns regarding Delphi are the definition of consensus, the expertise of the panel, its lack of scientific rigour, and – due to its lack of uniformity – reliability and validity of findings. Policy Delphi by default addresses the first since it does not seek consensus and can, through its design and execution, address the remaining concerns.Research limitations/implicationsCarefully designed Policy Delphi can offer a powerful research tool for exploratory research in hospitality, particularly for development of policies and strategies within an organisation. Unlike Normative Delphi, it is not intended as a decision making tool, but rather as a tool to generate options and suggest alternative courses of action for consideration.Originality/valueThe paper presents a valuable research tool that has evaded the attention of many hospitality researchers offering an illustrative example of its use in exploratory research to deliver credible, transferable and confirmable findings.

Gobe: an interactive, web-based tool for comparative genomic visualization

Gobe is a web-based tool for viewing comparative genomic data. It supports viewing multiple genomic regions simultaneously. Its simple text format and flash-based rendering make it an interactive, exploratory research tool. Gobe can be used without installation through our web service, or downloaded and customized with stylesheets and javascript callback functions. Gobe is a flash application that runs in all modern web-browsers. The full source-code, including that for the online web application is available under the MIT license at: http://github.com/brentp/gobe. Sample applications are hosted at http://try-gobe.appspot.com/ and http://synteny.cnr.berkeley.edu/gobe-app/.

Empathy Development in Teacher Candidates

Using a grounded theory research design, the author examined 180 reflective essays of teacher candidates who participated in a ‘Learning Process Project,’ in which they were asked to synthesize and document their discoveries about the learning process over the course of a completely new learning experience as naive learners. This study explored (1) the use of grounded theory as a systematic and exploratory research tool, (2) the transformative insights of the teacher candidates as they discovered the impact of the naive learner perspective on their teaching philosophies, and (3) the role of the naive learner perspective in effective refinement of teaching and learning ability. Further discussion in this study examined the potential of the ‘Learning Process Project’ to assist post secondary instructors as mentors in supporting empathic teacher candidates who will in turn support and mentor the children in their care.

The Sense and Nonsense of Exponential Models in Clinical Research

Exponential models are very popular for the assessment of clinical research. Nature is unpredictable and exponential models may be adequate for simple organisms but less so for human beings. Theobjective was to review the potential advantages and limitations of this approach. The following models were reviewed: Cox proportional hazard regression, Markow modeling, polynomial regression for Laplace transformed multi-exponential models, and logistic regression. Real and hypothesized data were used as examples.In conclusion, the advantages include: the possibility to conveniently study subgroup effects, otherwise called confounders; the possibility to derive pharmacokinetic parameters; andthe possibility to make long-term predictions from observational data. Limitations include: the exponential models may not fit the data well enough; they may give rise to some serious misinterpretations of the data; most of the statistical software for exponential models assumes that confounders are homogeneous, while, in reality, this is virtually never true; and the exponential models are a major simplification for the description of research data in human beings. We underline that exponential modeling, although a very interesting tool for exploratory research, is not adequately reliable for confirmational research. It is to be hoped that this paper will help investigators to more cautiously interpret the results of their exponential data analysis.

Problems in regression modeling of randomized clinical trials

Data modeling can be applied to improving the precision of clinical studies and multiple regression modeling is increasingly used for this purpose. To assess the uncertainties and risks of misinterpretations commonly encountered in regression analyses and rarely communicated in research papers. Regression analyses add uncertainties to the data in the form of subjective judgments and uncertainty about the appropriate transformation of the data. Additional flaws include; the assumption that baseline characteristics are independent of treatment efficacies; the loss of sensitivity of testing if the models do not fit the data well enough; the risk that clinical phenomena like toxicity effects and complete remissions go unobserved; the risk of clinically unrealistic results if multiple variables are included. Regression analyses, although a very good tool for exploratory research, are not sufficiently reliable for randomized clinical trials.

Dendroecological applications in air pollution and environmental chemistry: research needs

Summary During the past two decades, dendrochronology has evolved in new dimensions that have helped address both the extent and causes of impacts of regional scale environmental pollution on the productivity and function of forest ecosystems. Initial focus on the magnitude and timing of alterations of baseline growth levels of individual forest trees has now broadened to include characterization of the geographic extent of effects, their distribution among species, and their relationship to soils and biogeochemical cycles. Increasingly dendrochronology has benefitted from and contributed to improved understanding of the physiological and biogeochemical basis of air pollution effects on forest ecological processes. In addition, the need to consider levels and types of remedial action has raised concerns about the relative roles of anthropogenic and natural causative factors. The subdisciplines of dendroecology and dendrochemistry have evolved in response to those needs. Such applications have extended the field from its initial primary focus on historical growth and climatic reconstruction to an emerging role as an exploratory research tool with the potential to address basic questions about the roles of air pollution in modifying relationships between the amount, timing, distribution, and quality of tree growth and biogeochemical and atmospheric processes. In this paper we focus on two regional scale air quality issues, acidic deposition and tropospheric ozone, as stressors. We evaluate past success, current limitations, and future potential of dendrochronology as an investigative tool for both quantifying and understanding the effects of these stressors on forests. Important issues related to the use of dendrochemistry to evaluate effects of acidic deposition include the role of natural vs anthropogenic processes in cation mobilization in soils; biological and geochemical significance of increases in potentially phytotoxic metals and depletion of essential base cations in stem wood; and quantitative vs qualitative interpretation of patterns of element changes in wood related to metal mobility and species differences in accumulation. Shifts in root growth, function, and distribution and increased sensitivity of tree growth to temperature stress are important indicators that cation depletion can alter forest function and the dendroclimatic signal. Critical challenges in evaluating forest responses to ozone, include defining the relative roles of episodic and chronic exposures in seasonal and annual growth cycles, and the quantifying impacts of ozone on the water relations of trees and stands. Here high-resolution measures of diurnal growth and water use patterns have the potential to identify critical features of both pollutant exposure and plant response. These insights should enhance our analytical capabilities in examining annual-scale measures of growth and provide needed understanding of changes in relationships of growth to climate. We conclude that dendrochronology, when coupled with mechanistic understanding of underlying ecological processes influencing growth, has been, and will continue to be, a valuable monitoring and investigative tool for exploring relationships between trees and their growing environment. We expect this role to become even more important in the future as better ways are sought to evaluate and predict forest growth and function in a changing global environment.

Recombinant Listeria strains producing the nontoxic L-chain of botulinum neurotoxin A in a soluble form

Fragments of Clostridium botulinum neurotoxin A (BoNT/A) gene ( botA) were expressed in Listeria monocytogenes ATCC10527 to produce the L-chain of the toxin in a soluble form. A shuttle vector pAT19 (Em R) was used to make plasmid pAT-RL containing a botA gene fragment placed under C. botulinum ntnH-gene promoter control. The plasmid also contained a C. botulinum botR/A gene, a positive transcriptional regulator of botA. The cytoplasmic fraction of the L. monocytogenes (pAT-RL) strain was found to contain up to 3 mg/L of a soluble protein of expected size and immunologically positive towards BoNT antibodies. This is the first evidence of heterologous botA gene expression producing a soluble safe derivative of botulinum neurotoxin A needed as a molecular tool for exploratory research in neurosciences as well as a basis for raising protective immunity in humans.

Role of IT as an Enabler of Supply Chain Management

Indian firms have realised that adopting supply chain as a strategic competitive advantage tool has early payoffs. Information technology has played an important role among the firms that have been successful. They realised the importance of state-of-the-art information technology in linking supply with demand to achieve competitive advantage. Why do firms still fail to capitalise on the use of information technology? What inhibits this seamless flow of information across the supply chain? What are the lessons that can be drawn from those firms that have been able to use Information Technology successfully to add value and create sustainable value chain? This paper attempts to answer the above questions. It is an attempt to understand the role of Information Technology in supply chain management. We have reviewed the literature in order to understand how IT can effectively help supply chain become a strategic tool. With the help of exploratory research tools we have tried to find out how IT can be effectively utilised as a supply chain enabler. Our research findings are that aligning IT application to overall business strategy, managing processes rather than functions, developing cross functional teams, strategic alliance with suppliers and distributors, etc., create the right kind of organisational architecture, which help IT become a strategic competitive advantage tool.

The Use of Geographical Information Systems as an Exploratory Research Tool in Anthropology

The Use of Geographical Information Systems as an Exploratory Research Tool in Anthropology

The Use of Geographical Information Systems as an Exploratory Research Tool in Anthropology

The Use of Geographical Information Systems as an Exploratory Research Tool in Anthropology