Evaluating essential processes and forecast requirements for meteotsunami-induced coastal flooding

Meteotsunamis pose a unique threat to coastal communities and often lead to damage of coastal infrastructure, deluge of nearby property, and loss of life and injury. The Great Lakes are a known hot-spot of meteotsunami activity and serve as an important region for investigation of essential hydrodynamic processes and model forecast requirements in meteotsunami-induced coastal flooding. For this work, we developed an advanced hydrodynamic model and evaluate key model attributes and dynamic processes, including: (1) coastal model grid resolution and wetting and drying process in low-lying zones, (2) coastal infrastructure, including breakwaters and associated submerging and overtopping processes, (3) annual/seasonal (ambient) water level change, and (4) wind wave-current coupling. Numerical experiments are designed to evaluate the importance of these attributes to meteotsunami modeling, including a “representative storm” scenario in the context of regional climate change in which a meteotsunami wave is generated under high ambient lake-level conditions with a preferable wind direction and speed for wind-wave growth. Results demonstrate that accurate representation of coastal topography and fully resolving associated hydrodynamic processes are critical to forecasting the realistic hazards associated with meteotsunami events. As most of existing coastal forecast systems generally do not resolve many of these features due to insufficient model grid resolution or lack of essential model attributes, this work shows that calibrating or assessing existing forecast models against coastal water level gauges alone may result in underestimating the meteotsunami hazard, particularly when gauging stations are sparse and located behind harbor breakwaters or inside estuaries, which represent dampened or otherwise unrepresentative pictures of meteotsunami intensity. This work is the first hydrodynamic modeling of meteotsunami-induced coastal flooding for the Great Lakes, and serves as a template to guide where resources may be most beneficial in forecast system development and implementation

The Impact of Heterogeneous Shared Leadership in Scientific Teams

Leadership is evolving dynamically from an individual endeavor to shared efforts. This paper aims to advance our understanding of shared leadership in scientific teams. We define three kinds of leaders, junior (10-15), mid (15-20), and senior (20+) based on career age. By considering the combinations of any two leaders, we distinguish shared leadership as heterogeneous when leaders are in different age cohorts and homogeneous when leaders are in the same age cohort. Drawing on 1,845,351 CS, 254,039 Sociology, and 193,338 Business teams with two leaders in the OpenAlex dataset, we identify that heterogeneous shared leadership brings higher citation impact for teams than homogeneous shared leadership. Specifically, when junior leaders are paired with senior leaders, it significantly increases team citation ranking by 1-2%, in comparison with two leaders of similar age. We explore the patterns between homogeneous leaders and heterogeneous leaders from team scale, expertise composition, and knowledge recency perspectives. Compared with homogeneous leaders, heterogeneous leaders are more adaptive in large teams, have more diverse expertise, and trace both the newest and oldest references

MaCH-Admix: Genotype Imputation for Admixed Populations: MaCH-Admix: Imputation for Admixed Populations

Imputation in admixed populations is an important problem but challenging due to the complex linkage disequilibrium (LD) pattern. The emergence of large reference panels such as that from the 1,000 Genomes Project enables more accurate imputation in general, and in particular for admixed populations and for uncommon variants. To efficiently benefit from these large reference panels, one key issue to consider in modern genotype imputation framework is the selection of effective reference panels. In this work, we consider a number of methods for effective reference panel construction inside a hidden Markov model and specific to each target individual. These methods fall into two categories: identity-by-state (IBS) based and ancestry-weighted approach. We evaluated the performance on individuals from recently admixed populations. Our target samples include 8,421 African Americans and 3,587 Hispanic Americans from the Women’s Health Initiative, which allow assessment of imputation quality for uncommon variants. Our experiments include both large and small reference panels; large, medium, and small target samples; and in genome regions of varying levels of LD. We also include BEAGLE and IMPUTE2 for comparison. Experiment results with large reference panel suggest that our novel piecewise IBS method yields consistently higher imputation quality than other methods/software. The advantage is particularly noteworthy among uncommon variants where we observe up to 5.1% information gain with the difference being highly significant (Wilcoxon signed rank test P-value < 0.0001). Our work is the first that considers various sensible approaches for imputation in admixed populations and presents a comprehensive comparison

Machine Learning Explanations to Prevent Overtrust in Fake News Detection

Combating fake news and misinformation propagation is a challenging task in the post-truth era. News feed and search algorithms could potentially lead to unintentional large-scale propagation of false and fabricated information with users being exposed to algorithmically selected false content. Our research investigates the effects of an Explainable AI assistant embedded in news review platforms for combating the propagation of fake news. We design a news reviewing and sharing interface, create a dataset of news stories, and train four interpretable fake news detection algorithms to study the effects of algorithmic transparency on end-users. We present evaluation results and analysis from multiple controlled crowdsourced studies. For a deeper understanding of Explainable AI systems, we discuss interactions between user engagement, mental model, trust, and performance measures in the process of explaining. The study results indicate that explanations helped participants to build appropriate mental models of the intelligent assistants in different conditions and adjust their trust accordingly for model limitations

Research to Establish the Validity, Reliability, and Clinical Utility of a Comprehensive Language Assessment of Mandarin

Purpose With no existing gold standard for comparison, challenges arise for establishing the validity of a new standardized Mandarin language assessment normed in mainland China. Method A new assessment, Diagnostic Receptive and Expressive Assessment of Mandarin (DREAM), was normed with a stratified sample of 969 children ages 2;6 (years;months) to 7;11 in multiple urban and nonurban regions in northern and southern China. In this study of 230 children, the sensitivity and specificity of DREAM were examined against an a priori judgment of disorders. External validity was assessed using 2 indices of language production for different age groups. Results External validity was assessed against spontaneous language indices (correlation range: r = .6–.7; all ps \u3c .01) and narrative indices (overall: r = .45, p \u3c .01). Sensitivity (.73) and specificity (.82) of DREAM are moderate to good using a priori judgment as the standard. The values improved to .95 and .82 when spontaneous language and narratives were added to a priori judgment to define typicality. Divergent validity was moderate with nonlinguistic indices. Conclusion DREAM holds promise as a diagnostic test of Mandarin language impairment for children aged 2;6 to 7;11

Investigation of HIFU-induced anti-tumor immunity in a murine tumor model

<p>Abstract</p> <p>Background</p> <p>High intensity focused ultrasound (HIFU) is an emerging non-invasive treatment modality for localized treatment of cancers. While current clinical strategies employ HIFU exclusively for thermal ablation of the target sites, biological responses associated with both thermal and mechanical damage from focused ultrasound have not been thoroughly investigated. In particular, endogenous danger signals from HIFU-damaged tumor cells may trigger the activation of dendritic cells. This response may play a critical role in a HIFU-elicited anti-tumor immune response which can be harnessed for more effective treatment.</p> <p>Methods</p> <p>Mice bearing MC-38 colon adenocarcinoma tumors were treated with thermal and mechanical HIFU exposure settings in order to independently observe HIFU-induced effects on the host's immunological response. <it>In vivo </it>dendritic cell activity was assessed along with the host's response to challenge tumor growth.</p> <p>Results</p> <p>Thermal and mechanical HIFU were found to increase CD11c+ cells 3.1-fold and 4-fold, respectively, as compared to 1.5-fold observed for DC injection alone. In addition, thermal and mechanical HIFU increased CFSE+ DC accumulation in draining lymph nodes 5-fold and 10-fold, respectively. Moreover, focused ultrasound treatments not only caused a reduction in the growth of primary tumors, with tumor volume decreasing by 85% for thermal HIFU and 43% for mechanical HIFU, but they also provided protection against subcutaneous tumor re-challenge. Further immunological assays confirmed an enhanced CTL activity and increased tumor-specific IFN-γ-secreting cells in the mice treated by focused ultrasound, with cytotoxicity induced by mechanical HIFU reaching as high as 27% at a 10:1 effector:target ratio.</p> <p>Conclusion</p> <p>These studies present initial encouraging results confirming that focused ultrasound treatment can elicit a systemic anti-tumor immune response, and they suggest that this immunity is closely related to dendritic cell activation. Because DC activation was more pronounced when tumor cells were mechanically lysed by focused ultrasound treatment, mechanical HIFU in particular may be employed as a potential strategy in combination with subsequent thermal ablations for increasing the efficacy of HIFU cancer treatment by enhancing the host's anti-tumor immunity.</p

Recirculation over Complex Terrain

This study generated eddy covariance data to investigate atmospheric dynamics leeward of a small, forested hillside in upstate New York. The causes and effects of recirculation eddies were examined to support the larger goal of improving measurement of the exchange of energy, moisture, and trace gases between the terrestrial biosphere and the atmosphere over complex terrain. Sensors operated at five different altitudes on two separate towers—one at the top of the hill and one down the slope to the east—for approximately 8 weeks in the spring of 2013. During the experiment, the vertical potential temperature gradient was found to be the primary factor for determining whether winds interacting with the terrain features caused a recirculating eddy leeward of the hill. The study found evidence that the recirculation influenced carbon dioxide flux and caused the air column to be vertically well mixed

Determinants of pro-environmental behavior among excessive smartphone usage children and moderate smartphone usage children in Taiwan

Introduction Although there is evidence linking the relationships between smartphone usage with health, stress, and academic performance, there is still inadequate knowledge about the influence on pro-environmental behaviors. This study seeks to bridge this gap by adapting the theory of attribution framework to examine the effects of personal norms, social norms, perceived behavioral control on pro-environmental behavior of smartphone usage in children. Methods A total of 225 children aged between 11 to 12 from eight selected public primary schools at the Hsinchu Science and Industrial Park in Taiwan were surveyed. Two distinct groups (excessive versus moderate usage) were purposefully selected for comparison, of which 96 participants were excessive smartphone users while the remaining 129 were moderate smartphone users. Results Findings revealed significant differences between excessive and moderate smartphone usage children groups in personal norms (p  0.05), as well as social norms and pro-environmental behavior for moderate smartphone usage children (β = 0.181, t = 1.924, p > 0.05), but such a relationship could be developed through the mediating effect of perceived behavioral control (β = 0.497, t = 4.471***, p < 0.001). Discussion The results suggested that excessive smartphone usage children lack positive perceived behavioral control, and their pro-environmental behavior could only be predicted through explicit social norms, whereas pro-environmental behavior of moderate smartphone usage children was implicitly influenced by personal norms through perceived behavioral control

A comprehensive SNP and indel imputability database

Motivation: Genotype imputation has become an indispensible step in genome-wide association studies (GWAS). Imputation accuracy, directly influencing downstream analysis, has shown to be improved using re-sequencing-based reference panels; however, this comes at the cost of high computational burden due to the huge number of potentially imputable markers (tens of millions) discovered through sequencing a large number of individuals. Therefore, there is an increasing need for access to imputation quality information without actually conducting imputation. To facilitate this process, we have established a publicly available SNP and indel imputability database, aiming to provide direct access to imputation accuracy information for markers identified by the 1000 Genomes Project across four major populations and covering multiple GWAS genotyping platforms