cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Progressive band selection for satellite hyperspectral data compression and transmission
Creators: name: Fisher, Kevin
name: Chang, Chein-I
Publisher: name: Spie
Year: 2010

description: Efficient data transmission is an important part of satellite communication, particularly when large data volumes need to be downlinked to the Earth. One general approach to dealing with this dilemma is data compression, either lossless or lossy. For hyperspectral data, compression is specifically crucial due to its high inter-band spectral correlation, resulting from the use of hundreds of high spectral resolution bands for data collection. This paper develops a new approach, called progressive band selection (PBS), to achieve both data compression and data transmission, in the sense that data can be compressed and transmitted progressively. First, PBS prioritizes each spectral band by assigning a priority score based on its information content measured by a certain criterion. Then, bands are selected progressively according to the priority scores assigned to each spectral band. Consequently, data can be compressed and transmitted in a progressive fashion to meet the application's requirements; this task cannot be accomplished by most data compression techniques. Most importantly, PBS can be implemented in two opposite manners. One is forward progressive band selection (FPBS), which starts with a low number of bands and gradually improves data quality by including more bands progressively, based on their priority scores, until data quality is satisfactory. The other is backward progressive band selection (BPBS), which begins with a high number of spectral bands and progressively removes them in accordance with their priority scores, until data quality falls below a given tolerance level. In order to determine the lower and upper bounds on the number of bands used for FPBS and BPBS, we use a recently developed concept called virtual dimensionality (VD). We demonstrate the utility of PBS in compression and transmission for satellite communication with an experiment in land use and cover classification, which uses a dataset collected by the Hyperion instrument aboard NASA's EO-1 satellite.
Predictive Factors of HIV Testing Uptake among Pregnant Women in Nigeria- 2013 Demographic Health Survey
Creators: name: Ezeigwe, Ogochukwu
Publisher: name: Georgia State University
Year: 2020

description: INTRODUCTION: In sub-Saharan Africa countries such as Nigeria, the rate of Mother-to-child- transmission (MTCT) of HIV is notably high. Despite the availability of prenatal care services to prevent MTCT of HIV, Nigeria still records a higher rate of new pediatric HIV infections compared to other countries in the region. HIV counseling and testing during antenatal care is necessary as it serves as an entry point for Prevention of Mother-to-child-transmission (PMTCT).
AIM: This study aims to determine factors that are associated with HIV testing uptake during antenatal care (ANC) among women in Nigeria.
METHODS: Cross-sectional data from the 2013 Demographic Health Study on women aged 15-49 years (n=3410), who attended at least one ANC visit was used recruited for this study. The outcome variable was HIV testing during ANC. Predictor variables included various mothers’ level characteristics ( awareness of the mode of transmission, prevention methods of HIV, age, and educational level), demographic characteristics (place of residence, the region of residence, facility for ANC, and workers at ANC), and religious affiliation. Odds ratio from univariate and multivariate logistic regression methods were used to determine the association between the predictor variables and odds of HIV testing during ANC.
RESULTS: Over 50% of the sample were tested for HIV during ANC visits. All the demographic variables, mothers level factors, and sociocultural factors were significantly associated with increased odds of HIV testing uptake. Urban residence participants were 2 times more likely to take the test than the rural residence participants. Christians were 1.3times more likely to be tested than Muslims. Women who received care at government-owned facilities were 1.2 times more likely to be tested for HIV than women who received care at private-owned medical facilities. HIV testing tended to increase with increased levels of education. Women who were 24 - 49 years of age were more likely to be tested for HIV compared to women who were younger than 24 years of age. Compared to women who had no comprehensive knowledge of HIV transmission, women who knew about transmission during delivery (AOR =1.31; 95%CI:1.08 - 1.59), and drugs for PMTCT (AOR=2.28; 95%CI:1.89 - 2.68) were more likely to be tested for HIV during ANC. Women who were attended to by skilled workers were more likely to be tested than women attended to by unskilled workers(AOR=2.11; 95%CL:1.63 – 2.71).
CONCLUSION: In this study, factors driving HIV uptake during ANC was found to be rooted in demographic characteristics, mothers’ level characteristics, and socio-cultural factors. Thus, addressing modifiable factors such as availability of government health facilities, and skilled workers may lead to a higher uptake of HIV testing during ANC among women. This will contribute to a notable reduction in the incidence of MTCT HIV infections in Nigeria
Identifying Influential Variables in the Prediction of Type 2 Diabetes Using Machine Learning Methods
Creators: name: Chernishkin, Amanda
Publisher: name: Georgia State University
Year: 2020

description: This study investigates three alternative machine learning methods to explore influential predictors of type 2 diabetes. It compares ridge, lasso, and elastic net regression to linear regression, and focuses on 12 outcome variables that include age, sex, race, income, education level, body mass index, waist circumference, arm circumference, hip circumference, family history, smoking status, sleep duration, high blood pressure, and high-density lipoprotein. Ridge, lasso and elastic net regression do not outperform linear regression but do assist in choosing a simpler model which could be important for improving future modeling.
Pilot Survey of Driving Behaviors Associated with Adverse Weather amongst Collegiate Students
Creators: name: Bostic, Myles
Publisher: name: Georgia State University
Year: 2020

description: Motor vehicle crashes have demonstrated to be one of the leading causes of death and unintentional injury within the United States (Center for Disease Control and Prevention (CDC), 2020). Of the 5,891,000 motor vehicle crashes that occur each year, approximately 21% of these crashes are weather-related (Federal Highway Administration (FHWA), 2020). The population most impacted by motor vehicle crashes within the United States is teens, who are three times more likely to experience crashes than adults (CDC, 2020). To better understand driving behaviors used by early adults, the current study examined defensive driving behaviors implemented by collegiate students to prevent motor vehicle collisions. The purpose of the study was to investigate the driving behaviors of college students during adverse weather conditions. Undergraduate students were recruited, and participants anonymously recorded their responses to questions assessing their driving behavior. The results suggested that students avoid driving in the car in adverse weather (e.g., fog, rain, or ice), but they do not avoid driving during night conditions. Implications of the results are that adverse weather conditions are likely to be avoided by GSUSPH students and all motor vehicle drivers, thus encouraging the public health community to continue designing and implementing developed road strategies to promote driver safety.
Low-bit rate exploitation-based lossy hyperspectral image compression
Creators: name: Chang, Chein-I
name: Ramakrishna, Bharath
name: Wang, Jing
name: Plaza, Antonio J.
Publisher: name: Spie
Year: 2010

description: Hyperspectral image compression has become increasingly important in data exploitation because of enormous data volumes and high redundancy provided by hundreds of contiguous spectral channels. Since a hyperspectral image can be viewed as a 3-dimensional (3D) image cube, many efforts have been devoted to extending 2D image compression techniques to perform 3D image compression on hyperspectral image cubes. Unfortunately, some major issues generally encountered in hyperspectral data exploitation at low or very low-bit rate compression, for example, subpixels and mixed pixels which do not occur in traditional pure pixel-based image compression are often overlooked in such a 2D-to-3D compression. Accordingly, a direct application of 2D-to-3D compression techniques to hyperspectral image cubes without taking precaution may result in significant loss of crucial spectral information provided by subtle substances such as small objects, anomalies during low bit-rate lossy compression. This paper takes a rather different view by investigating lossy hyperspectral compression from a perspective of exploring spectral information, referred to as exploitation-based lossy compression and further develops spectral/spatial hyperspectral image compression to effectively preserve crucial and vital spectral information of objects which are generally missed by commonly used mean-squared error (MSE) or signal-to-noise ratio (SNR)-based compression techniques when lossy compression is performed at low bit rates. In order to demonstrate advantages of the proposed spectral/spatial compression approach applications of subpixel target detection and mixed pixel analysis are used for experiments for performance evaluation.
Analysis of Seasonal Influenza Virologic and Hospitalization Trends among Children in the United States from 2010-2019
Creators: name: Mandel, Samantha
Publisher: name: Georgia State University
Year: 2020

description: Background: Each year, millions of children get sick with seasonal flu, thousands of children are hospitalized, and some children die from flu. While the U.S. has a comprehensive influenza surveillance system reporting on current flu activity, and the Centers for Disease Control and Prevention (CDC) publishes weekly updates on their website (FluView), there is a lack of literature analyzing trends among the virus types causing flu and flu-related hospitalizations among children over multiple flu seasons. This study aimed to identify tends over time (2010-2019) in the proportion of children with lab-confirmed flu and hospitalized for flu, along with the proportion of virus types children are infected with.
Methods: A secondary data analysis was conducted using the existing U.S. national influenza surveillance data assembled and provided by the CDC. The study included children in the United States with lab-confirmed flu or with flu-associated hospitalization during the 2010-2011 flu season through the 2018-2019 flu season. Data from hospitalization surveillance and virologic surveillance were analyzed across all 9 flu seasons.
Results: Trends in the proportion of seasonal flu and flu-related hospitalizations among children showed a significant decrease over time (2010-2019). Additionally, trends in the proportion of flu A(H3N2) virus among children showed a significant decrease over time. While this study revealed a strong, positive relationship between the proportion of flu and flu-related hospitalizations among young children (0-4 yr) and older children (5-24 yr), a strong, negative relationship was observed between the proportion of flu and flu-related hospitalizations among children (0-4 yr) and older adults (65+).

Conclusion: A significant decrease in proportion of flu and flu hospitalizations among children was observed over time, revealing a trend of decreased burden of flu among children compared to other age groups. A significant relationship was observed between children and older adults, revealing that as trends of flu among children decreased, trends increased among older adults. Trends in seasonal flu and flu-related complications have important implications for flu prevention and control efforts.
Real-Time Simplex Growing Algorithms for Hyperspectral Endmember Extraction
Creators: name: Chang, Chein-I
name: Wu, Chao-Cheng
name: Lo, Chien-Shun
name: Chang, Mann-Li
Publisher: name: IEEE
Year: 2009
Subjects: Algorithm design and analysis
Chaos
Computational complexity
Councils
Data mining
Endmember extraction algorithm (EEA)
Error analysis
Hyperspectral imaging
Least squares methods
p -Pass automatic target generation process (ATGP)–simplex growing algorithm (SGA)
p-Pass Maximin-SGA
p-Pass Minimax-SGA
p-Pass real-time (RT) SGA (RT SGA)
p-Pass unsupervised fully constrained least squares (UFCLS)-SGA
Remote sensing
Support vector machines

description: The simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) and shown to be a promising endmember extraction technique. This paper further extends the SGA to a versatile real-time (RT) processing algorithm, referred to as RT SGA, which can effectively address the following four major issues arising in the practical implementation for N-FINDR: (1) use of random initial endmembers which causes inconsistent final results; (2) high computational complexity which results from an exhaustive search for finding all endmembers simultaneously; (3) requirement of dimensionality reduction because of large data volumes; and (4) lack of RT capability. In addition to the aforementioned advantages, the proposed RT SGA can also be implemented by various criteria in endmember extraction other than the maximum simplex volume.
The Effects of Adverse Childhood Experiences on Later Sexual Violence Perpetration Among Male College Students: A Moderated Mediation Model
Creators: name: Khader, Saja
Publisher: name: Georgia State University
Year: 2020

description: Sexual violence (SV) is a significant public health problem in the United States, specifically among undergraduate college students. Experiencing adverse childhood experiences or ACEs is also a significant public health problem and may act as a potential risk factor for perpetrating SV later in life. This study investigated whether ACEs was associated with an increased likelihood of SV perpetration, and whether several other risk factors for SV perpetration (hypermasculinity, hostility towards women, and binge drinking) acted as mediators between the relation between ACEs and later SV perpetration in adulthood. This study also tested whether perceptions of social norms moderated these relationships in male undergraduate students. Secondary data was drawn from the Freshman of Georgia study (FoG), a longitudinal CDC-funded study. A total of 1,144 male college freshmen enrolled at one of 30 participating colleges and universities in Georgia were included in this study via online survey completion. Statistical analyses were performed using SAS 9.4 software through SAS Studio University Edition. Three separate moderated mediation analyses were conducted via Hayes PROCESS macro model 14. Results showed that hypermasculinity and binge drinking mediated the relationship between ACEs and later SV perpetration, and also that perception of social norms was a significant moderator. These findings contribute to the growing body of literature surrounding SV perpetration and provide further understanding of the ACEs – SV perpetration relationship among male college students. SV prevention and education programming for this population should target the modifiable SV perpetration risk factors of hypermasculinity, binge drinking, and perceptions of social norms.
ШАХСНИ ҲУҚУҚБУЗАРЛИКЛАРДАН ЖАБРЛАНИШИГА ОЛИБ КЕЛУВЧИ ОМИЛЛАРНИНГ ИЛМИЙ ВА ҚИЁСИЙ ТАҲЛИЛИ
Creators: name: Bulturboyev, Farrux
Publisher: name: Zenodo
Year: 2024

description: Ушбу мақолада шахсни ҳуқуқбузарликлардан жабрланишига олиб келувчи омилларнинг илмий ва қиёсий таҳлили тўғрисида фикр юритилган ва ушбу фаолиятга оид кўплаб тушунчаларга таъриф берилган.
A Review of Unsupervised Spectral Target Analysis for Hyperspectral Imagery
Creators: name: Chang, Chein-I
name: Jiao, Xiaoli
name: Wu, Chao-Cheng
name: Du, Yingzi
name: Chang, Mann-Li
Publisher: name: Springer
Year: 2010

description: One of great challenges in unsupervised hyperspectral target analysis is how to obtain desired knowledge in an unsupervised means directly from the data for image analysis. This paper provides a review of unsupervised target analysis by first addressing two fundamental issues, "what are material substances of interest, referred to as targets?" and "how can these targets be extracted from the data?" and then further developing least squares (LS)-based unsupervised algorithms for finding spectral targets for analysis. In order to validate and substantiate the proposed unsupervised hyperspectral target analysis, three applications in endmember extraction, target detection and linear spectral unmixing are considered where custom-designed synthetic images and real image scenes are used to conduct experiments.
Adaptive Inverse Hyperbolic Tangent Algorithm for Dynamic Contrast Adjustment in Displaying Scenes
Creators: name: Yu, Cheng-Yi
name: Ouyang, Yen-Chieh
name: Wang, Chuin-Mu
name: Chang, Chein-I
Publisher: name: Springer
Year: 2010

description: Contrast has a great influence on the quality of an image in human visual perception. A poorly illuminated environment can significantly affect the contrast ratio, producing an unexpected image. This paper proposes an Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm to improve the display quality and contrast of a scene. Because digital cameras must maintain the shadow in a middle range of luminance that includes a main object such as a face, a gamma function is generally used for this purpose. However, this function has a severe weakness in that it decreases highlight contrast. To mitigate this problem, contrast enhancement algorithms have been designed to adjust contrast to tune human visual perception. The proposed AIHT determines the contrast levels of an original image as well as parameter space for different contrast types so that not only the original histogram shape features can be preserved, but also the contrast can be enhanced effectively. Experimental results show that the proposed algorithm is capable of enhancing the global contrast of the original image adaptively while extruding the details of objects simultaneously.
TrajGPT: Controlled Synthetic Trajectory Generation Using a Multitask Transformer-Based Spatiotemporal Model
Creators: name: Hsu, Shang-Ling
name: Tung, Emmanuel
name: Krumm, John
name: Shahabi, Cyrus
name: Shafique, Khurram
Publisher: name: arXiv
Year: 2024
Subjects: subject: Machine Learning (cs.LG)
subject: FOS: Computer and information sciences
subject: I.6.5; I.2.6; G.3

description: Human mobility modeling from GPS-trajectories and synthetic trajectory generation are crucial for various applications, such as urban planning, disaster management and epidemiology. Both of these tasks often require filling gaps in a partially specified sequence of visits - a new problem that we call "controlled" synthetic trajectory generation. Existing methods for next-location prediction or synthetic trajectory generation cannot solve this problem as they lack the mechanisms needed to constrain the generated sequences of visits. Moreover, existing approaches (1) frequently treat space and time as independent factors, an assumption that fails to hold true in real-world scenarios, and (2) suffer from challenges in accuracy of temporal prediction as they fail to deal with mixed distributions and the inter-relationships of different modes with latent variables (e.g., day-of-the-week). These limitations become even more pronounced when the task involves filling gaps within sequences instead of solely predicting the next visit.
 We introduce TrajGPT, a transformer-based, multi-task, joint spatiotemporal generative model to address these issues. Taking inspiration from large language models, TrajGPT poses the problem of controlled trajectory generation as that of text infilling in natural language. TrajGPT integrates the spatial and temporal models in a transformer architecture through a Bayesian probability model that ensures that the gaps in a visit sequence are filled in a spatiotemporally consistent manner. Our experiments on public and private datasets demonstrate that TrajGPT not only excels in controlled synthetic visit generation but also outperforms competing models in next-location prediction tasks - Relatively, TrajGPT achieves a 26-fold improvement in temporal accuracy while retaining more than 98% of spatial accuracy on average.
description: 10 pages, 3 figures, 32nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2024)
The Risk of Autism Spectrum Disorder (ASD) in Preterm and Low Birth Weight Infants
Creators: name: Sanchez-Alvarez, Sonia
Publisher: name: Georgia State University
Year: 2020

description: INTRODUCTION: Autism Spectrum Disorder (ASD) is characterized by challenges in the areas of repetitive behaviors, social skills, and speech and nonverbal communications. According to the Centers for Disease Control and Prevention (CDC), 1 in 54 children (8 years old) in the United States have ASD.
AIM: This study aimed to investigate and examine the association between both gestational age & low birth weight (LBW) and autism spectrum disorder (ASD).
METHODS: This study used secondary data from the National Survey of Children’s Health (NSCH), a cross-sectional survey that examines the emotional and physical health of children in the United States from birth to 17 years of age, for the years 2016-2018. Logistic regression models were used to examine any effects that may be due to prematurity and low birth weight on ASD outcomes. The two ASD outcomes considered were whether caretakers had a health care provider who “Ever Told” them their child has an ASD or whether their child “Currently” has an ASD diagnosis.
RESULTS: Univariate models showed that both LBW and gestational ages are associated with increased odds of ASD, ever or current diagnosis. When birth weight and gestational age were conjointly considered, there was only a moderate association between preterm birth and ASD. In multivariate models with relevant covariates (e.g., controlling for presence of developmental delays; health insurance) prematurity continued to be associated with ever or current ASD status, but birth weight was not.
DISCUSSION: The study fits in with previous literature that have reported consistent associations between preterm birth and ASD, but mixed findings between birth weight and ASD. Most studies do not include both gestational age and birth weight in their analyses. These results may be used to inform future prenatal care research aimed at understanding ASD’s etiology.
Quantitative analysis in clinical applications of brain MRI using independent component analysis coupled with support vector machine
Creators: name: Chai, Jyh-Wen
name: Chi-Chang Chen, Clayton
name: Chiang, Chih-Ming
name: Ho, Yung-Jen
name: Chen, Hsian-Min
name: Ouyang, Yen-Chieh
name: Yang, Ching-Wen
name: Lee, San-Kan
name: Chang, Chein-I
Publisher: name: Wiley
Year: 2010
Subjects: brain MRI
independent component analysis (ICA)
quantitative analysis
support vector machine (SVM)

description: Purpose: To effectively perform quantification of brain normal tissues and pathologies simultaneously, independent component analysis (ICA) coupled with support vector machine (SVM) is investigated and evaluated for effective volumetric measurements of normal and lesion tissues using multispectral MR images. Materials and Methods: Synthetic and real MR data of normal brain and white matter lesion (WML) data were used to evaluate the accuracy and reproducibility of gray matter (GM), white matter (WM), and WML volume measurements by using the proposed ICA+SVM method to analyze three sets of MR images, T1-weighted, T2-weighted, and proton density/fluid-attenuated inversion recovery images. Results: The Tanimoto indexes of GM/WM classification in the normal synthetic data calculated by the ICA+SVM method were 0.82/0.89 for data with 0% noise level. As for clinical MR data experiments, the ICA+SVM method clearly extracted the normal tissues and white matter hyperintensity lesions from the MR images, with low intra- and inter-operator coefficient of variations. Conclusion: The experiments conducted provide evidence that the ICA+SVM method has shown promise and potential in applications to classification of normal and pathological tissues in brain MRI. J. Magn. Reson. Imaging 2010;32:24–34. © 2010 Wiley-Liss, Inc.
Changes Over Time in Awareness of Hepatitis C Infection in the United States 2007-2018
Creators: name: Mezzo, Jennifer
Publisher: name: Georgia State University
Year: 2021

description: INTRODUCTION:  An estimated 115 million people worldwide and 2.4-3.5 million people in the United States are infected with Hepatitis C infection. The majority of these individuals are unaware of their infection due to the asymptomatic nature of the disease and are therefore at greater risk for advanced-staged complications such as cirrhosis or liver cancer.
AIM: This study aimed to measure changes over time in awareness of hepatitis C infection among a housed, non-institutionalized representative sample within the United States.

METHODS: National Health and Examination Survey (NHANES) data spanning years 2007 – 2018 were compiled into one dataset. After eligibility restrictions were applied the final dataset contained N=387 respondents. Bivariate and multivariate logistic regression models were conducted to explore the associations between our independent variables and awareness of HCV infection as well as to assess possible confounders and mediators of the relationship between time (primary exposure variable) and awareness of HCV infection (outcome variable). Bivariate linear regression was used to estimate linear trends to estimate linear trends in awareness of HCV infection over time. We also assessed the percent of those aware of their HCV infection to clearly define the outcome variable.
RESULTS:  Awareness of one’s  HCV infection increased from 24.53% in the 2007-2008 survey cycle to 63.48% in the 2017-2018 survey cycle (? for trend 0.09, p<0.0001). The odds of reporting a positive HCV diagnosis in the second survey period (2013-2018) was 3.71 times the odds in the first time period (p <0.0001).
CONCLUSION: Diagnosed hepatitis C is increasing, however, remains suboptimal in the US. Recent efforts may have contributed to these increases, bringing us closer to achieving DHHS and WHO goals of viral hepatitis elimination.
Association between Adult Alcohol Misuse, Adult Mental Health, and Firearm Storage Practices in Households with Children: Findings from the Behavioral Risk Factor Surveillance System (BRFSS)
Creators: name: Shelby, Daniel
Publisher: name: Georgia State University
Year: 2021

description: Firearm violence in the United States is a substantial health concern and improper storage within the home is a prominent risk factor for suicide, homicide, and unintentional injury. Studies have examined the negative influence of adult alcohol misuse on firearm storage in households with children, but none have included adult mental health problems. The purpose of this study was to describe the prevalence of various forms of firearm storage in households with children in California, Idaho, Kansas, Oregon, Texas, and Utah and analyze how adult alcohol misuse and adult mental health problems relate to how firearms are stored. Data from the 2017 Behavioral Risk Factor Surveillance System (BRFSS) were analyzed. Only households with children were included in this study (n=12,489). Predictor variables included adult alcohol misuse and adult mental health. The outcome variables were presence of firearms in the household and subsequent firearm storage method categorized as unloaded, loaded and locked, and loaded and unlocked. Weighted prevalence estimates and 95% confidence intervals of sociodemographic and predictor variables were calculated for all respondents for each firearm storage category. Weighted relative risks and 95% confidence intervals of sociodemographic variables by the predictor variables were calculated for all respondents for each firearm storage category using multivariable logistic regression. Overall, 33.8% of respondents reported owning at least one firearm. Among firearm owners, 27% (n = 1,105) stored their firearms loaded and 11% (n = 463) stored firearms both loaded and unlocked. Firearm owners reported higher alcohol misuse (25.6%) and higher mental health problems (26.5%) than non-firearm owning respondents (16.9% and 20.4%, respectively). Alcohol misuse was associated with greater risk of owning a firearm (aRR = 1.2 [1.02, 1.41]) and greater risk of storing a firearm loaded and unlocked (aRR = 1.67 [1.2, 2.34]). Mental health problems were associated with a greater risk of owning a firearm (aRR = 1.22 [1.04, 1.42]). Firearms are common in households with children and a significant minority are stored improperly. Adult alcohol misuse was associated with the least safe method of firearm storage. Effective prevention approaches addressing firearm storage must be developed and disseminated, especially programs that target adults experiencing alcohol problems and other significant risk factors for firearm violence.
Supplementary document for Soliton trapping and orthogonal Raman scattering in a birefringent photonic crystal fiber - 5957109.pdf
Creators: name: Stefanska, Karolina
name: Majchrowska, Sylwia
name: Gemza, Karolina
name: Sobon, Grzegorz
name: Sotor, Jaroslaw
name: Mergo, Pawel
name: Tarnowski, Karol
name: Martynkien, Tadeusz
Publisher: name: Optica Publishing Group
Year: 2025
Subjects: Uncategorized

description: Supplemental document 1
Learning management of social studies to develop social responsibility on learners
Creators: name: Phinla, Wipada
name: Phinla, Wipapan
Publisher: name: figshare
Year: 2025
Subjects: classificationCode: 390102
subject: Curriculum and pedagogy theory and development

description: The influence of the 21st century technology plays an important role in determining human behavior to the extent of instilling materialism and consumerism in mankind. Such behaviors will only lead to the behavior that deviates from the social norms, causing social disorder and lack of moral and ethical responsibility in performing duty for oneself and forothers in society. Therefore, it is the essential task of social studies teachers in instilling and enhancing the good qualities in the learners by way of providing diverse approaches in learning management for learners. Students are encouraged to practice on their own by following the procedures: 1) Interest in Accountability;2) Endorsement Accountability 3) In Quest of Accountability 4) Exhibition of Accountability and 5) Inference of Accountability, in order for the learners to behave in a socially responsible manner.
Konso
Creators: name: Pitek, Emily
Publisher: name: Database of Religious History (DRH)
Year: 2018

description: “The Konso are comprised of three groups [regions] living in southern Ethiopia—the Garati, the Takadi, and the Turo…”(eHRAF World Cultures: Konso Culture Summary). The regions are each comprised of several semi-autonomous towns that possess a cultural unity based on allegiance to one of the great regional poqalla (religious/civil leaders), sacred drum cycles, and an age-grade system (Hallpike, 2008:88). The Konso do not have an official organized religion or political system, but share a set of common ideas, rituals, and conventions. For the Konso, religion and society are the intertwined assumptions, beliefs, and practices of life.
Nutritional Status and Anthropometric Data Quality of US-bound Refugees, October 2018- September 2019
Creators: name: Hailu, Kibrten
Publisher: name: Georgia State University
Year: 2021

description: INTRODUCTION:  According to The World Health Organization, malnutrition refers to deficiencies, excesses, or imbalances in an individual’s nutrient intake. Refugees are at a higher risk for all forms of malnutrition. According to the WHO, report on global burden of malnutrition, in 2019 the rates of malnutrition included 21.3% of stunting, 6.9% of wasting and 5.6% of overweight in children under 5 globally.
AIM: To describe the nutritional status and anthropometric data quality of US-bound refugee children arriving from the top 10 processing countries. Recommendations to overseas partners may be made to improve anthropometric data quality thus improving prevalence estimates.
METHODS: We used data from the CDC’s Electronic Disease Notification (EDN) System. The study population includes all refugees from the top ten processing countries that arrived in the U.S. during fiscal year 2019. The refugees included in this analysis are <18 years old. The mean z-scores and estimated prevalence of acute and chronic malnutrition were calculated per country in this analysis. Data quality was assessed through the assessment of number of missing data, percentage of flagged data, digit preference score and standard deviation.
RESULTS:  Overall, the majority of refugees were Congolese (54.2%) and Burmese (18.2%). The percentage of missing data and biologically implausible values were low, yet standard deviations were high in some countries. Prevalence estimates for wasting and stunting were generally considered medium risk according to WHO thresholds.
DISCUSSION: Findings revealed areas where data quality can be improved through intervention with trainings. Further studies over longer periods of time and stratified by refugee setting (camp vs urban) can provide the program with a better understanding of malnutrition in US-bound refugees.
Understanding Alcohol Marketing and Youth Alcohol Consumption in Kampala, Uganda
Creators: name: Dunklin, Samuel
Publisher: name: Georgia State University
Year: 2021

description: Introduction: Alcohol consumption leads to a disproportionate number of deaths around the globe every given year. Most of the current research regarding alcohol consumption is conducted not only on the adult population, but among what could be considered affluent first-world counties in North America and Europe. This undermines two key populations, developing and under-resourced countries, and youth. Alcohol marketing is also a widely used tool to advance sales within countries, however its impact upon communities is also lacking research. This study seeks to not only advance research by studying youth in Kampala, Uganda, but to look at the relationship between drinking habits and alcohol marketing exposure among youth who live on the streets and in the slums.
 
Methods: The Kampala Youth Survey is a cross-sectional survey administered in 2014 to youth ages 12 to 18 years old, living in the slums of Kampala, Uganda (n=1,134). This study subset its survey population to look specifically at youth who had responded to questions regarding drinking habits and alcohol exposure (n=413). Descriptive statistics were calculated and logistic regression was conducted using SAS 9.3. 
 
Results: Among the population of youth included within the study, 89.1% had a high exposure to alcohol marketing within their communities. Among participants, 84.18% had consumed alcohol within the past year and 94.49% had consumed alcohol within the last 30 days. The results of the logistic regression showed that there was a significant association between age and alcohol consumption within the last year and within the last 30 days in 2014. It also showed that certain locations were also a significant indicator of alcohol consumption. High alcohol marketing exposure was not seen as significant over low exposure, though high levels reported could indicate that future research will find it to be significant.    
 
Conclusions: Exposure to alcohol marketing towards youth is a dangerous and impactful tool that can lead to alcohol consumption. While this study could not show that a higher exposure to alcohol marketing impacts drinking at a higher rate, the results suggest that alcohol marketing exposure in any form can impact drinking habits within youth. This realization is dangerous and gives pathways for not only future studies, but future regulations around alcohol marketing to protect youth not only in Kampala, but globally.
Semi-Supervised Linear Spectral Unmixing Using a Hierarchical Bayesian Model for Hyperspectral Imagery
Creators: name: Dobigeon, Nicolas
name: Tourneret, Jean-Yves
name: Chang, Chein-I
Publisher: name: IEEE
Year: 2008
Subjects: Additive noise
Bayesian methods
Gaussian noise
Gibbs sampler
hierarchical Bayesian analysis
hyperspectral images
Hyperspectral imaging
Hyperspectral sensors
Image analysis
Libraries
linear spectral unmixing
Markov chain Monte Carlo (MCMC) methods
Monte Carlo methods
reversible jumps
Signal processing
Signal processing algorithms

description: This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive Gaussian noise. The abundance parameters appearing in this model satisfy positivity and additivity constraints. These constraints are naturally expressed in a Bayesian context by using appropriate abundance prior distributions. The posterior distributions of the unknown model parameters are then derived. A Gibbs sampler allows one to draw samples distributed according to the posteriors of interest and to estimate the unknown abundances. An extension of the algorithm is finally studied for mixtures with unknown numbers of spectral components belonging to a know library. The performance of the different unmixing strategies is evaluated via simulations conducted on synthetic and real data.
Mixed principal-component-analysis/independent-component-analysis transform for hyperspectral image analysis
Creators: name: Chai, Jyh Wen
name: Wang, Jing
name: Chang, Chein-I
Publisher: name: Spie
Year: 2007

description: Principal components analysis (PCA) and independent-component analysis (ICA) are widely used transforms to perform various tasks. Mixing both transforms has not been investigated. This paper develops a new transform, called the mixed PCA/ICA transform, which combines m principal components (PCs) produced by PCA and n independent components (ICs) generated by ICA to form a new set of m+n mixed components to be used for hyperspectral image analysis. Four problems need to be addressed. One is to determine the total number of components, p, needed to be generated for the mixed (m,n)-PCA/ICA transform. The second is how to combine the PCA and ICA in a single transform. Since the ICA does not prioritize its generated ICs in the same way that the PCs are ranked by the PCA using data variances, how to generate an appropriate set of n ICs becomes a third problem. Finally, the fourth problem is to decompress the compressed data based on the mixed PCA/ICA components if there is a need to reconstruct the original data. This paper solves these four problems and further conducts experiments to demonstrate the utility of the mixed PCA/ICA transform in subpixel detection and mixed pixel classification and quantification.
Trobrianders also known as “Kilivila”, “Kiriwina”, “Kitava”, “Vakuta”, “Kaileuna”
Creators: name: Pitek, Emily
Publisher: name: Database of Religious History (DRH)
Year: 2018

description: Located off the coast of Papua New Guinea, the Trobriand Islands are home to several thousand individuals who live in villages organized by matrilineages. The Trobrianders do not participate in an official, organized religion. Their belief system is largely dominated by magic and ceremonial practices, including garden magic and the kula, an inter-island trading ring. Spells, land, taboos, ancestral history, and social position are owned and shared by members of specific matrilineages. This entry focuses on the main island, Kiriwina, ca. 1914.
Metabolic Pathway Activation: An Analysis of the Effects of Traffic Related Air Pollution and Physical Activity
Creators: name: Streiff, Micah
Publisher: name: Georgia State University
Year: 2020

description: INTRODUCTION: Air pollution is a major public health concern. Reducing air pollution exposure can reduce the burden of disease and improve cardiovascular and respiratory health. Traffic related air pollution (TRAP) is a significant contributor to air pollution globally. TRAP and physical activity have a dynamic relationship with interacting and opposing effects that are not fully understood.
AIM: This study investigates the relationship between physical activity and exposure to TRAP by identifying the metabolic pathways associated with important TRAP components including Black Carbon (BC), Ozone (O3), Fine Particulate Matter
METHODS: Saliva samples were collected from 57 study participants playing sports outdoors near major roadways in Atlanta, GA in 2016. Outdoor air pollution measurements were taken along with participants’ physical activity level and breathing metrics. Liquid chromatography coupled with high resolution mass spectrometry was used to process the saliva samples. Mummichog, a pathway analysis tool, was used to identify the metabolic pathways activated.
RESULTS: Ninety-seven pathways were found to be activated as a result of exposure to TRAP and covariates. Acute air pollution exposure was found to be significant in activating metabolic pathways a total of 81 times, with 14 metabolic pathways that showed significant correlation with acute TRAP: Vitamin B6, Beta-Alanine metabolism, Pyruvate metabolism, Selenoamino acid metabolism, Drug metabolism pathway, Saturated fatty acids beta-oxidation, Fatty acid activation metabolism, Glyoxylate and dicarboxylate, TCA cycle metabolism, Vitamin B3 metabolism, Propanoate, Bile acid biosynthesis, Caffeine metabolism, Glyoxylate and dicarboxylate metabolism. One-day lagged PM2.5 exposure has a higher number of pathways activated when compared to acute pollutant exposure.
DISCUSSION: The lower degree of acute exposure pathway activation may be due to insufficient time for changes in metabolic activity to be expressed in saliva compared to long-term exposure or ongoing biological processes. While acute exposure to air pollution may contribute to activating less metabolic pathways than long term exposure, heat index and other covariates all contribute to activating metabolic pathways in addition to the effects of static covariates. There is limited research in untargeted, high-resolution metabolomics data of the effects of air pollution in activating metabolic pathways, but this study offers a glimpse into this relationship for future studies to build upon.
title: Increased Student Incentive through Material Gamification
title: STUDENT INCENTIVES
titleType: AlternativeTitle
Creators: name: Barron, Ryan
Publisher: name: Maryland Shared Open Access Repository
Year: 2021

description: This paper explores the concept that academic progress should be approached as a marathon rather than a sprint, emphasizing the importance of steady learning over rapid course completion. It addresses the challenges faced by students who struggle with the long-term demands of higher education and may lack motivation. The study suggests that adapting educational strategies to align with students' comfort zones can enhance engagement. One effective approach discussed is the gamification of lectures and quizzes, which can make learning more interactive and enjoyable, thereby improving student motivation and retention.
Diversidad de Cangrejos pinotéridos asociados a invertebrados marinos en la costa Atlántica Mexicana
Creators: name: Martínez-García, Maritza
name: Simoes, Nuno
name: Campos, Ernesto
Publisher: name: Zenodo
Year: 2013
Subjects: subject: Ecology
subject: FOS: Biological sciences
subject: Ecology
subject: Aquatic ecology
subject: Ecology/trends
subject: Ecology/classification
subject: Animal ecology
subject: Biological diversity
subject: Marine ecosystem
subject: Marine ecology
subject: Marina
subject: Marine Biology
subject: Marine biodiversity
subject: Marine biology
subject: Marine fauna
subject: Marine biota
subject: Marine biology
subject: Marine organism
subject: Conservation
subject: Biodiversity conservation
subject: Evolution
subject: Biological Evolution
subject: Biodiversity
subject: Fauna
subject: Biology
subject: Animal biology
subject: Evolutionary biology
subject: Biology/classification
subject: Biology/education
subject: Biology/trends
subject: Marine Science
subject: Coastal environment
subject: Coastal ecosystems
subject: Coastal area
subject: Crustacea
subject: Crustacean
subject: Crustacea/classification
subject: Crustacea/growth & development
subject: Symbolic Interactionism
subject: symbiotic relation
subject: Sea
subject: Brachyura
subject: Brachyura/classification
subject: Brachyura/growth & development
subject: Species
subject: Animal species
subject: Cangrejos pinotéridos
subject: invertebrados
subject: Pinnotheridae
subject: ITIS: 98964
subject: WoRMS: 106775
subject: pinotéridos
subject: GBIF: 8672
subject: Pinnixa sayana
subject: Parapinnixa bouvieri

description: Este cartel fue presentado en el IV Congreso Mexicano de Ecología, en Fremantle western, Australia celebrado del 18 al 22 de marzo, 2013

This poster was presented at the IV Mexican Congress of Ecology, in Fremantle Western, Australia, March 18 to 22, 2013

This poster was produced in collaboration with the Biodiversidad Marina de Yucatán project. https://www.bdmy.org.mx/

English version: https://doi.org/10.5281/zenodo.15123372

Designed and illustrated by: naturae.art@gmail.com
Regional Income Inequality and Current Substance Use Among Hispanic 12th Grade Students in the United States
Creators: name: Nadeem, Aresha
Publisher: name: Georgia State University
Year: 2021

description: INTRODUCTION: Income inequality has been previously shown to be related to adverse population health outcomes. A suggested etiology is that income inequality intensifies status anxiety, leading to unhealthy coping mechanisms such as substance use. Behavioral factors specific to Hispanic cultures may have the potential to build resiliency in adolescents against substance use related to status anxiety, but have not been considered as protective factors in large, nationwide studies on substance use among adolescents.
AIM: Determine the association between regional income inequality in the U.S. and substance use among 12th grade students, and determine whether this association is different for Hispanic students.
METHODS: Public survey data from 2012 – 2018 from  the Monitoring the Future Survey, an annual, nationally representative survey on substance use and social and political views of secondary school and college students in the U.S., were used along with data from the U.S. Census Bureau on household income inequality for 4 regions of the U.S, represented by the Gini coefficient. Odds ratios, 95% confidence intervals, and p-values were calculated using binary logistic regression carried out in SAS 9.4 to determine the likelihood of substance use given the respective region’s Gini coefficients and controlling for confounders.
RESULTS: The Gini coefficient was negatively associated with substance use for the whole sample (OR <0.001), as well as for Hispanic (OR 0.002) and Black (OR <0.001) participants, and positively associated with substance use for White participants (OR 2.339), but was not significant (CI 0.032 – 170.112). When disaggregated by race only Future Plans and Father’s Education were consistently significant predictors for all three racial/ethnic groups and the whole sample. The model’s concordance statistic was 0.581, meaning it was able to correctly predict substance use among participants a little more than half the time.
DISCUSSION: Because the model’s predictive power was low, it is not sufficient for determining the true association between substance use and income inequality among the survey population, and differences among racial and ethnic groups could not be determined. Future research should look at specific cultural factors to determine whether they can build resiliency against substance related to status-anxiety at a population level.