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Background & aimsNonalcoholic fatty liver disease (NAFLD) was shown to disproportionally affect Hispanic persons. We examined the prevalence of suspected NAFLD in Hispanic/Latino persons with diverse backgrounds.MethodsWe studied the prevalence of suspected NAFLD among 12,133 persons included in the Hispanic Community Health Study/Study of Latinos. We collected data on levels of aminotransferase, metabolic syndrome (defined by National Cholesterol Education Program-Adult Treatment Panel III guidelines), demographics, and health behaviors. Suspected NAFLD was defined on the basis of increased level of aminotransferase in the absence of serologic evidence for common causes of liver disease or excessive alcohol consumption. In multivariate analyses, data were adjusted for metabolic syndrome, age, acculturation, diet, physical activity, sleep, and levels of education and income.ResultsIn multivariate analysis, compared with persons of Mexican heritage, persons of Cuban (odds ratio [OR], 0.69; 95% confidence interval [CI], 0.57-0.85), Puerto Rican (OR, 0.67; 95% CI, 0.52-0.87), and Dominican backgrounds (OR, 0.71; 95% CI, 0.54-0.93) had lower rates of suspected NAFLD. Persons of Central American and South American heritage had a similar prevalence of suspected NAFLD compared with persons of Mexican heritage. NAFLD was less common in women than in men (OR, 0.49; 95% CI, 0.40-0.60). Suspected NAFLD associated with metabolic syndrome and all 5 of its components.ConclusionsOn the basis of an analysis of a large database of health in Latino populations, we found the prevalence of suspected NAFLD among Hispanic/Latino individuals to vary by region of heritage.

Locust plagues inflict severe agricultural damage. Climate change-induced extreme events like rainfall and droughts have expanded locust habitats. These new areas, often beyond routine monitoring, could become potential high-risk locust areas (PHRLA). Quantitatively understanding the outbreak mechanism driving drought and flood dynamics is crucial for identifying PHRLA, but such studies are scarce. To address this gap, we conducted a case study on locust outbreaks in Xiashan Reservoir, the largest reservoir in Shandong Province, China, in 2017 and 2018. Using time series satellite imagery and meteorological products, we quantitatively analyzed how drought–flood dynamics and temperature affect locust habitats, reproduction, and aggregation. Employing an object-oriented random forest classifier, we generated locust habitat classification maps with 93.77% average overall accuracy and Kappa coefficient of 0.90. Combined with meteorological analysis, we found that three consecutive drought years from 2014 to 2016 reduced the water surface area by 75%, expanding suitable habitats (primarily reeds and weeds) to cover 60% of the reservoir. Warm winters and high temperatures during locust key growth periods, coupled with expanding suitable habitats, promoted multi-generational locust reproduction. However, substantial flooding events in 2017 and 2018, driven by plentiful rainfall during key growth periods, reduced suitable habitats by approximately 54% and 29%, respectively. This compression led to high locust density, causing the locust plague and high-density spots of locusts (HDSL). Our study elucidates locust plague outbreak mechanisms under dynamic drought and flood environments. Based on this, we propose an approach to identify PHRLA by monitoring changes in drought and flood patterns around water bodies and variations in suitable habitat size and distribution, as well as surrounding topography. These findings hold significant implications for enhancing locust monitoring and early warning capabilities, reducing pesticide usage, and ensuring food and ecological security and sustainable agriculture. [ABSTRACT FROM AUTHOR]

Low mathematics achievement is a persistent problem in the United States, and multiplication is a fundamental area in which many students manifest learning difficulties. This study examined the strategic developmental levels of multiplication problem solving among 121 elementary school students in Grades 3 through 5. A latent class analysis modeling was used to identify three valid groups representing different patterns of strategy choices for each of three types of multiplication problems. Findings indicated intra-group variability for problem-solving accuracy, for frequency of using different strategies, and for accuracy of executing direct retrieval/algorithm (DR/AG) strategies. Students demonstrated relative consistency in their strategy choices for solving the three problem types. Students who used DR/AG strategies most frequently showed the highest problem-solving accuracy and the highest accuracy of executing the DR/AG strategies. Students who most frequently relied on incorrect operations or who indicated they did not know how to solve problems demonstrated the lowest problem-solving accuracy among the three groups; the number of students in this group increased with problem difficulty levels. Implications are discussed in terms of identifying students' strategic developmental levels and providing differentiated instruction based on the identified levels.

This study investigates the effects of uncertainty in rockphysics models on estimates of reservoir parameters from joint inversion of seismic AVA and CSEM data. The reservoir parameters are related to electrical resistivity using Archie's law, and to seismic velocity and density using the Xu-White model. To account for errors in the rock-physics models, we use two methods to handle uncertainty: (1) the model outputs are random functions with modes or means given by the model predictions, and (2) the parameters of the models are themselves random variables. Using a stochastic framework and Markov Chain Monte Carlo methods, we obtain estimates of reservoir parameters as well as of the uncertainty in the estimates. Synthetic case studies show that uncertainties in both rock-physics models and their associated parameters can have significant effects on estimates of reservoir parameters. Our method provides a means of quantifying how the uncertainty in the estimated reservoir parameters increases with increasing uncertainty in the rock-physics model and in the model parameters. We find that in the example we present, the estimation of water saturation is relatively less affected than is the estimation of clay content and porosity.

Photocatalytic reactions for fuel generation are crucial for the world's energy needs. Covalent‐Organic‐Frameworks (COFs) have been extensively studied as promising designable photocatalysts for these reactions due to their efficient visible‐light absorption, suitable energy‐band structure, facilitated intramolecular charge separation, and fast mass transfer. However, the activities of pristine COFs remain unsatisfactory, due to intermolecular charge recombination. Recently, COF‐based heterostructures, which combine COFs with metal‐sulfides, metal‐oxides, carbon materials, or MOFs, have attracted increasing attention for enhancing solar‐to‐fuel conversion efficiency by facilitating interfacial photo‐generated carrier separation, sensitizing wide‐gap semiconductors, and promoting surface redox reactions. Thus, a review of the state‐of‐the‐art progress of COF‐based heterostructure photocatalysts in reactions such as H2 evolution, CO2 reduction, O2 evolution, H2O splitting and CO2 splitting is crucial for the design of new photocatalysts to promote solar‐to‐fuel conversion. In this review, the COF‐based heterostructures photocatalysts are highlighted based on their synthesis, properties, and reasons for enhanced activities. Moreover, design principles are raised for such photocatalysts for each fuel generation reaction, based on insights into related research. Finally, this review is concluded by proposing future trends for COF‐based heterostructures photocatalysts, with attention to the design of COFs and supports, analyzing the photocatalytic reaction dynamics, together with considering practical applications. [ABSTRACT FROM AUTHOR]

To investigate the effects of COVID-19 on individuals with tinnitus and their views to guide future tinnitus care. A mixed-methods cross-sectional research design. An online survey was completed by 365 individuals with tinnitus from Australia and other countries. Tinnitus was reported to be more bothersome during the pandemic by 36% of respondents, whereas 59% reported no change and 5% reported less bothersome tinnitus. Nearly half of the respondents had received COVID-19 vaccination(s) and 12% of them reported more bothersome tinnitus while 2% developed tinnitus post-vaccination. Australian respondents spent less time in self-isolation or quarantine and saw fewer change in in-person social contact than respondents from other countries. More than 70% of respondents thought that tinnitus care services were insufficient both before and during the pandemic. Regarding their opinions on how to improve tinnitus care in the future, five themes including alleviation of condition, government policies, reduced barriers, self- and public-awareness, and hearing devices were identified. A majority of respondents did not perceive any change in tinnitus perception and one-third of respondents had worsened tinnitus during the pandemic. To improve tinnitus care, better awareness and more accessible resources and management are crucial. [ABSTRACT FROM AUTHOR]

Understanding fluid distribution and movement in the subsurface is critical for a variety of subsurface applications, such as remediation of environmental contaminants, sequestration of nuclear waste and CO2, intrusion of saline water into fresh water aquifers, and the production of oil and gas. It is well recognized that characterizing the properties that control fluids in the subsurface with the accuracy and spatial coverage needed to parameterize flow and transport models is challenging using conventional borehole data alone. Integration of conventional borehole data with more spatially extensive geophysical data (obtained from the surface, between boreholes, and from surface to boreholes) shows promise for providing quantitative information about subsurface properties and processes. Typically, estimation of subsurface properties involves a two-step procedure in which geophysical data are first inverted and then integrated with direct measurements and petrophysical relationship information to estimate hydrological parameters. However, errors inherent to geophysical data acquisition and inversion approaches and errors associated with petrophysical relationships can decrease the value of geophysical data in the estimation procedure. In this paper, we illustrate using two examples how joint inversion approaches, or simultaneous inversion of geophysical and hydrological data, offer great potential for overcoming some of these limitations.

Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a non-cognitive-diagnostic assessment, in three steps: (a) Q-matrices construction based on item content analysis; (b) Q-matrices validation and refinement based on a saturated CDM; and (c) reduced CDMs evaluations based on acceptable Q-matrix. Our research showed that (a) the practice of retrofitting non-cognitive-diagnostic assessment for cognitive diagnostic purpose was feasible; (b) Q-matrix construction and CDM selection were especially important when retrofitting approach was adopted; (c) compensatory and saturated CDMs could fit the PISA reading assessment better than other CDMs; and (d) the application of CDMs to reading assessments may promote research on reading construct.

By analysing the test data of 1029 British secondary school students' performance on 20 Programme for International Student Assessment English reading items through the generalised deterministic input, noisy "and" gate (G-DINA) model, the study conducted two investigations on exploring the relationships among the five reading comprehension skills defined by six English language experts. Skill groups, skill types and conflicting relationship were discovered in the investigation about the relationship among reading comprehension skills as part of the cognitive structure of the examinees, which provided insights into the sequence of reading skill training. The investigation about the relationship among reading comprehension skills in the problem-solving process, conducted at the item level, conceptualised skill relationship patterns as strategies for solving items. The study also demonstrated that saturated G-DINA model catered to the characteristics of reading comprehension skills and could be applied to tests involving highly interactive and hierarchical skills.