scholarly journals Advancing Cave Detection Using Terrain Analysis and Thermal Imagery

2021 ◽  
Vol 13 (18) ◽  
pp. 3578
Author(s):  
J. Judson Wynne ◽  
Jeff Jenness ◽  
Derek L. Sonderegger ◽  
Timothy N. Titus ◽  
Murzy D. Jhabvala ◽  
...  
Keyword(s):  
Mojave Desert ◽  
Analytical Techniques ◽  
Future Research ◽  
Terrain Analysis ◽  
Lasso Regression ◽  
Thermal Imagery ◽  
Cave Entrance ◽  
The Difference ◽  
Selection Operator ◽  
Cave Detection

Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter “unenhanced thermal”) as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn— slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday— slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference— TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.

scholarly journals Biomarkers Associated with Physical Resilience After Hip Fracture

2020 ◽  
Vol 75 (10) ◽  
pp. e166-e172
Author(s):  
Daniel C Parker ◽  
Cathleen Colόn-Emeric ◽  
Janet L Huebner ◽  
Ching-Heng Chou ◽  
Virginia Byers Kraus ◽  
...  
Keyword(s):  
Older Adults ◽  
Hip Fracture ◽  
Canonical Correlation ◽  
Molecular Mechanisms ◽  
Principal Component ◽  
Lasso Regression ◽  
Circulating Micrornas ◽  
The Difference ◽  
Selection Operator ◽  
Better Than

Abstract Background Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture—the expected recovery differential (ERD)—that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture. Methods In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture. Results Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p. Conclusions We identified a set of biomarkers that explained 27% of the variance in ERD—a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors.

scholarly journals Circulating IL-13 Is Associated with De Novo Development of HCC in HCV-Infected Patients Responding to Direct-Acting Antivirals

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3820
Author(s):  
Zuzana Macek Jílková ◽  
Arnaud Seigneurin ◽  
Celine Coppard ◽  
Laurissa Ouaguia ◽  
Caroline Aspord ◽  
...  
Keyword(s):  
De Novo ◽  
Serum Levels ◽  
Lasso Regression ◽  
Direct Acting Antivirals ◽  
Immune Mediators ◽  
Luminex Technology ◽  
The Difference ◽  
Selection Operator ◽  
Direct Acting ◽  
Subsequent Time Point

Direct-acting antivirals (DAAs) are highly effective in targeting hepatitis C virus (HCV) infections, but the incidence of HCV-related hepatocellular carcinoma (HCC) remains still high. In this study, we investigated a cohort of HCV-infected patients treated with DAAs who were followed up for 4 years after sustained virological response (SVR) achievement. Patients who developed de novo HCC following DAA treatment were compared to matched controls who did not develop HCC. These control patients were selected based on DAA treatment, sex, age, fibrosis status, and platelet counts. We evaluated serum levels of 30 immune mediators before, during, at the end of, and three months after DAA treatment using Luminex technology. We identified the immune factors associated with de novo HCC occurrence following DAA treatment. Specifically, interleukin (IL)-4 and IL-13 levels were significantly higher before start of the DAA treatment in the serum of patients who later developed HCC than in controls and stayed higher at each subsequent time point. Least absolute shrinkage and selection operator (LASSO) regression revealed IL-13 as the only strong factor associated with HCC development in this cohort of HCV patients. The difference was observed already at baseline of DAA treatment, which confirms the existence of a specific immune profile in these patients who later develop HCC.

Comparative Effects of High-Tech Visual Scene Displays and Low-Tech Isolated Picture Symbols on Engagement From Students With Multiple Disabilities

2019 ◽  
Vol 50 (4) ◽  
pp. 693-702 ◽  
Author(s):  
Christine Holyfield ◽  
Sydney Brooks ◽  
Allison Schluterman
Keyword(s):  
Language Learning ◽  
Augmentative And Alternative Communication ◽  
Visual Analysis ◽  
Multiple Disabilities ◽  
Visual Scene ◽  
Future Research ◽  
High Tech ◽  
Single Subject ◽  
Wide Range ◽  
The Difference

Purpose Augmentative and alternative communication (AAC) is an intervention approach that can promote communication and language in children with multiple disabilities who are beginning communicators. While a wide range of AAC technologies are available, little is known about the comparative effects of specific technology options. Given that engagement can be low for beginning communicators with multiple disabilities, the current study provides initial information about the comparative effects of 2 AAC technology options—high-tech visual scene displays (VSDs) and low-tech isolated picture symbols—on engagement. Method Three elementary-age beginning communicators with multiple disabilities participated. The study used a single-subject, alternating treatment design with each technology serving as a condition. Participants interacted with their school speech-language pathologists using each of the 2 technologies across 5 sessions in a block randomized order. Results According to visual analysis and nonoverlap of all pairs calculations, all 3 participants demonstrated more engagement with the high-tech VSDs than the low-tech isolated picture symbols as measured by their seconds of gaze toward each technology option. Despite the difference in engagement observed, there was no clear difference across the 2 conditions in engagement toward the communication partner or use of the AAC. Conclusions Clinicians can consider measuring engagement when evaluating AAC technology options for children with multiple disabilities and should consider evaluating high-tech VSDs as 1 technology option for them. Future research must explore the extent to which differences in engagement to particular AAC technologies result in differences in communication and language learning over time as might be expected.

A Historical Data based Ensemble System for Efficient Stock Price Prediction

2019 ◽  
Vol 12 ◽  
Author(s):  
Vijay Kumar Dwivedi ◽  
Manoj Madhava Gore
Keyword(s):  
Stock Price ◽  
Prediction Models ◽  
Historical Data ◽  
Stock Exchange ◽  
Primary Objective ◽  
Lasso Regression ◽  
Stock Price Prediction ◽  
Price Prediction ◽  
Consistent Manner ◽  
Selection Operator

Background: Stock price prediction is a challenging task. The social, economic, political, and various other factors cause frequent abrupt changes in the stock price. This article proposes a historical data-based ensemble system to predict the closing stock price with higher accuracy and consistency over the existing stock price prediction systems. Objective: The primary objective of this article is to predict the closing price of a stock for the next trading in more accurate and consistent manner over the existing methods employed for the stock price prediction. Method: The proposed system combines various machine learning-based prediction models employing least absolute shrinkage and selection operator (LASSO) regression regularization technique to enhance the accuracy of stock price prediction system as compared to any one of the base prediction models. Results: The analysis of results for all the eleven stocks (listed under Information Technology sector on the Bombay Stock Exchange, India) reveals that the proposed system performs best (on all defined metrics of the proposed system) for training datasets and test datasets comprising of all the stocks considered in the proposed system. Conclusion: The proposed ensemble model consistently predicts stock price with a high degree of accuracy over the existing methods used for the prediction.

A Short Review on Structural Equation Modeling: Applications and Future Research Directions

2015 ◽  
Vol 4 (3) ◽  
Author(s):  
Surajit Bag
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
First Generation ◽  
Analytical Techniques ◽  
Short Review ◽  
Equation Modeling ◽  
Future Research ◽  
Multivariate Techniques ◽  
Statistical Efficiency ◽  
Future Research Directions

The application of multivariate techniques is mainly to expand the researchers explanatory ability and statistical efficiency. The first generation analytical techniques share a common limitation i.e. each technique can examine only a single relationship at a time. Structural Equation Modeling, an extension of several multivariate techniques is the technique popularly used today can examine a series of dependence relationships simultaneously. The purpose of this study is to provide a short review on Structural Equation Modeling (SEM) being used in social sciences research. A comprehensive literature review of article appearing in top journals is conducted in order to identify how often SEM theory is used. Also the key SEM steps have been provided offering potential researchers with a theoretical supported systematic approach that simplify the multiple options with performing SEM.

scholarly journals Using a Process Approach to Pandemic Planning: A Case Study

2021 ◽  
Vol 11 (9) ◽  
pp. 4121
Author(s):  
Hana Tomaskova ◽  
Erfan Babaee Tirkolaee
Keyword(s):  
Process Model ◽  
Process Mining ◽  
Process Approach ◽  
Research Topic ◽  
Future Research ◽  
Critical Situation ◽  
Pandemic Planning ◽  
The Difference ◽  
Smart Technologies

The purpose of this article was to demonstrate the difference between a pandemic plan’s textual prescription and its effective processing using graphical notation. Before creating a case study of the Business Process Model and Notation (BPMN) of the Czech Republic’s pandemic plan, we conducted a systematic review of the process approach in pandemic planning and a document analysis of relevant public documents. The authors emphasized the opacity of hundreds of pages of text records in an explanatory case study and demonstrated the effectiveness of the process approach in reengineering and improving the response to such a critical situation. A potential extension to the automation and involvement of SMART technologies or process optimization through process mining techniques is presented as a future research topic.

scholarly journals Rethinking SME default prediction: a systematic literature review and future perspectives

2021 ◽  
Author(s):  
Francesco Ciampi ◽  
Alessandro Giannozzi ◽  
Giacomo Marzi ◽  
Edward I. Altman
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Global Financial Crisis ◽  
Analytical Techniques ◽  
Future Research ◽  
Finance Management ◽  
Default Prediction ◽  
Emerging Issues ◽  
Medium Enterprise ◽  
Modern Analytical

AbstractOver the last dozen years, the topic of small and medium enterprise (SME) default prediction has developed into a relevant research domain that has grown for important reasons exponentially across multiple disciplines, including finance, management, accounting, and statistics. Motivated by the enormous toll on SMEs caused by the 2007–2009 global financial crisis as well as the recent COVID-19 crisis and the consequent need to develop new SME default predictors, this paper provides a systematic literature review, based on a statistical, bibliometric analysis, of over 100 peer-reviewed articles published on SME default prediction modelling over a 34-year period, 1986 to 2019. We identified, analysed and reviewed five streams of research and suggest a set of future research avenues to help scholars and practitioners address the new challenges and emerging issues in a changing economic environment. The research agenda proposes some new innovative approaches to capture and exploit new data sources using modern analytical techniques, like artificial intelligence, machine learning, and macro-data inputs, with the aim of providing enhanced predictive results.

scholarly journals Visualizing molecular structures and shapes: a comparison of virtual reality, computer simulation, and traditional modeling

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Corina E. Brown ◽  
Ben Whaley ◽  
Richard M. Hyslop
Keyword(s):  
Virtual Reality ◽  
Chemistry Education ◽  
Research Question ◽  
Molecular Geometry ◽  
Molecular Structures ◽  
Future Research ◽  
Chemistry Students ◽  
Positive Attitudes ◽  
The Difference ◽  
Students Attitudes

AbstractThe purpose of this study was to compare the effectiveness of three methods used to assist in teaching molecular geometry to college chemistry students. A pre- and post-test quasi-experiment was used to collect data about students’ performance in a given chemistry exercise. One research question was intended to evaluate and compare the effectiveness of the three methods in assisting students to understand the topic and carry out the exercise correctly, and a second research question addressed students’ attitudes towards the use of Virtual Reality (VR) in chemistry education. Results show a positive attitude towards the use of VR as an assisting tool to aid in understanding chemistry concepts. While the difference among the three methods was not significant, the results show that the VR brought more enthusiasm and positive attitudes toward the topic of molecular geometry among the students. Educational implications and recommendations for future research are presented as well.

scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

scholarly journals A Survey of Function Analysis and Applied Dynamic Equations on Hybrid Time Scales

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 450
Author(s):  
Chao Wang ◽  
Ravi P. Agarwal
Keyword(s):  
Time Scales ◽  
Function Analysis ◽  
Dynamical Behavior ◽  
Research Field ◽  
Dynamic Equations ◽  
Future Research ◽  
Dynamical Models ◽  
Time Scale Calculus ◽  
The Difference

As an effective tool to unify discrete and continuous analysis, time scale calculus have been widely applied to study dynamic systems in both theoretical and practical aspects. In addition to such a classical role of unification, the dynamic equations on time scales have their own unique features which the difference and differential equations do not possess and these advantages have been highlighted in describing some complicated dynamical behavior in the hybrid time process. In this review article, we conduct a survey of abstract analysis and applied dynamic equations on hybrid time scales, some recent main results and the related developments on hybrid time scales will be reported and the future research related to this research field is discussed. The results presented in this article can be extended and generalized to study both pure mathematical analysis and real applications such as mathematical physics, biological dynamical models and neural networks, etc.

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