Miracle-dz/UniFAR-FTUs huggingface dataset:
Climatology of cross‐tropopause mass exchange over the Tibetan Plateau and its surroundings

The cross‐tropopause mass flux (CTMF) and long‐term trends in stratosphere–troposphere exchange (STE) over the Tibetan Plateau (TP) and its surroundings were analyzed using European Centre for Medium‐Range Weather Forecasts reanalysis data. The gross CTMF (the sum of upward and downward mass flux) shows an evident wave train structure over the TP, which is mainly related to the horizontal exchange of air masses along the tropopause associated with the sharp meridional gradient in tropopause pressure or vertical discontinuity of the thermal tropopause in winter. The seasonal cycle of the STE over the TP shows that the gross mass flux is downwards in Northern Hemisphere (NH) winter and upwards in NH summer. The gross CTMF over the TP accounts for 2.96% of the global total CTMF arising from STE processes resolved by Wei method. Both the upward and downward CTMF over the TP exhibit statistically significant positive trends in winter during the period 1979–2009. The strong positive trends of STE in winter over the TP are resulted from the combined effects of the rising tropopause height, enhanced westerlies and decreasing plateau winter monsoon. In summer, both the upward and downward CTMF exhibit statistically significant negative trends over the northern TP, while the trend in upward CTMF is positive over the southern TP, in accordance with the increasing intensity of Asian summer monsoon in recent decades. The sensitivity simulations with a climate model confirm that changes in the Asian monsoon can significantly affect the tropopause and the CTMF over the TP.
Participatory Causal Loop Diagrams Building for Supporting Decision‐Makers Integrating Flood Risk Management in an Urban Regeneration Process

Abstract Several modeling tools commonly used for supporting flood risk assessment and management are highly effective in representing physical phenomena, but provide a rather limited understanding of the multiple implications that flood risk and flood risk reduction measures have on highly complex systems such as urban areas. In fact, most of the available modeling tools do not fully account for this complexity—and related uncertainty—which heavily affects the interconnections between urban systems evolution and flood risk, ultimately resulting in an ineffective flood risk management. The present research proposes an innovative methodological framework to support decision‐makers involved in an urban regeneration process at a planning/strategic level, accounting for the multi‐dimensional implications of flood risk and of different flood risk management strategies. The adopted approach is based on the use of System Thinking principles and participatory System Dynamics modeling techniques, and pursues an integration between scientific and stakeholder knowledge. Reference is made to one of the case studies of the CUSSH and CAMELLIA projects, namely Thamesmead (London), a formerly inhospitable marshland currently undergoing a process of urban regeneration, and perceived as being increasingly vulnerable to flooding. It represents an interesting opportunity for building a replicable modeling approach to integrate urban development dynamics with flood risk, ultimately supporting policy and decision‐makers in identifying mitigation/prevention measures and understanding how they could help achieve multi‐dimensional benefits (e.g., environmental, social and economic).
An Environmental Uncertainty Perception Framework for Misinformation Detection and Spread Prediction in the COVID-19 Pandemic: Artificial Intelligence Approach

Amidst the COVID-19 pandemic, misinformation on social media has posed significant threats to public health. Detecting and predicting the spread of misinformation are crucial for mitigating its adverse effects. However, prevailing frameworks for these tasks have predominantly focused on post-level signals of misinformation, neglecting features of the broader information environment where misinformation originates and proliferates. This study aims to create a novel framework that integrates the uncertainty of the information environment into misinformation features, with the goal of enhancing the model’s accuracy in tasks such as misinformation detection and predicting the scale of dissemination. The objective is to provide better support for online governance efforts during health crises. In this study, we embraced uncertainty features within the information environment and introduced a novel Environmental Uncertainty Perception (EUP) framework for the detection of misinformation and the prediction of its spread on social media. The framework encompasses uncertainty at 4 scales of the information environment: physical environment, macro-media environment, micro-communicative environment, and message framing. We assessed the effectiveness of the EUP using real-world COVID-19 misinformation data sets. The experimental results demonstrated that the EUP alone achieved notably good performance, with detection accuracy at 0.753 and prediction accuracy at 0.71. These results were comparable to state-of-the-art baseline models such as bidirectional long short-term memory (BiLSTM; detection accuracy 0.733 and prediction accuracy 0.707) and bidirectional encoder representations from transformers (BERT; detection accuracy 0.755 and prediction accuracy 0.728). Additionally, when the baseline models collaborated with the EUP, they exhibited improved accuracy by an average of 1.98% for the misinformation detection and 2.4% for spread-prediction tasks. On unbalanced data sets, the EUP yielded relative improvements of 21.5% and 5.7% in macro-F1-score and area under the curve, respectively. This study makes a significant contribution to the literature by recognizing uncertainty features within information environments as a crucial factor for improving misinformation detection and spread-prediction algorithms during the pandemic. The research elaborates on the complexities of uncertain information environments for misinformation across 4 distinct scales, including the physical environment, macro-media environment, micro-communicative environment, and message framing. The findings underscore the effectiveness of incorporating uncertainty into misinformation detection and spread prediction, providing an interdisciplinary and easily implementable framework for the field.
Algorithm of Mental Model of Art Design Based on Virtual Reality Technology

With the evolution of biometric technology, this research embarks on a multidimensional exploration, encompassing design innovation, ethical scrutiny, and the application of advanced optimization techniques. The core objective is to redefine elemental packaging design through the lens of machine vision cognition into the ethical and social implications inherent in biomedical biometrics. With the integration of Hidden Markov Probabilistic Swarm Optimization (HMPSO) to amplify the capabilities of biometric systems. At the forefront of this study is the reimagination of elemental packaging design, characterized by aesthetics, ergonomics, and functionality. The infusion of machine vision cognition into these designs not only enhances user experience but also prompts contemplation of ethical considerations surrounding privacy, accessibility, and informed consent. Ethical and social implications are scrutinized comprehensively, acknowledging the profound impact of biometrics on individual rights, security, and privacy. The research probes into equitable access to biometric technologies, ethical data utilization in healthcare, identity verification, and surveillance contexts. Central to this multidisciplinary inquiry is the integration of Hidden Markov Probabilistic Swarm Optimization (HMPSO). With swarm intelligence and probabilistic modeling, HMPSO enhances the efficiency, accuracy, and reliability of biomedical biometric systems. It addresses the critical challenge of reducing false positives and false negatives in biometric authentication. The research methodology comprises performance evaluations, ethical analyses, and socio-cultural investigations, offering a comprehensive view of the interplay between design innovation, machine vision cognition, ethical awareness, and the application of HMPSO in the biomedical biometrics.
Threats to Ecosystem Engineering Macrophytes: Climate Change

Anthropogenic activities are impacting Earth’s climate dynamics, causing rapid global climate change and increasing climate variability (IPCC 2007, 2012). Coastal marine ecosystems, which are among the most ecologically and socio-economically important on the planet (Costanza et al. 1997, Barbier et al. 2011), are already experiencing the effects of this physical forcing, with impacts on biodiversity and ecosystem functioning at multiple spatial and temporal scales (Harley et al. 2006, Hoegh-Guldberg and Bruno 2010, Wernberg et al. 2011b, Doney et al. 2012). Although geological records show climatic changes throughout the history of the Earth, anthropogenic activities have been causing a rapid increase in atmospheric carbon dioxide (Hansen et al. 2006, IPCC 2007, Meehl et al. 2007). This increase in CO2, in combination with other greenhouse gases, has intensifi ed the infrared
Increasing Reproductive Health Knowledge of Indonesian Female Migrant Workers Through Case Study Learning Method

Background: Reproduction health in migrant workers is complicated and difficult to handle. Health education is one of the methods to increase the knowledge about health reproduction. Aims: The study aimed to analyze the knowledge of migrant workers related to reproductive health through case study learning method. Methods: The study is an intervention research. Total respondents were 135 participants. The intervention was conducted in 3 groups of female migrant workers. The intervention given was related to reproductive health with 4 meetings in the first group, 8 meetings in the second group and 12 meetings in the third group. Group 2 and 3 used case study as learning method. The measurement of knowledge of the three groups was through pre-test and post-test. The statistical test used ANOVA to determine differences between intervention groups and T Test to determine the difference between pre-test and post-test scores. Results: There were significant differences in pre-test and post-test scores in all groups and there was significant difference in post-test scores in groups 1 and 3 of p=0.001. Conclusion: Health education given to migrant workers is proven to be able to increase the level of knowledge related to reproductive health. The group that received case study as learning method and more number of meeting, had a better level of knowledge.
Existing Opportunities to Adapt the Rio Grande/Bravo Basin Water Resources Allocation Framework

The study of the Rio Grande/Bravo (RGB) Basin water allocation demonstrates how the United States (U.S.) and Mexico have consolidated a transboundary framework based on water sharing. However, the water supply no longer meets the ever-increasing demand for water or the expectations of different stakeholders. This paper explores opportunities for an enhanced management regime that will address past problems and better examine how to balance demands for a precious resource and environmental needs. Based on an overview of the RGB Basin context and the water allocation framework, as well as a discussion on stakeholders’ ability to achieve solutions, this paper explores three key questions: (1) Does the current binational water allocation framework meet current and future human and environmental needs? (2) How can the U.S.-Mexico water allocation framework be adapted to balance social and environmental water demands so it can support and preserve the RGB Basin ecosystem? (3) What are the main opportunities to be explored for expanding the U.S.-Mexico water resources allocation framework? The U.S.-Mexico water resources framework is subject to broad interpretation and may be adapted to the circumstances taking the fullest advantage of its flexibility. Policy recommendations highlight the existing flexibility of the binational framework, the potential to move forward with an ad hoc institutional arrangement, and the creation of political will to achieve change through stakeholders recommendations.
Functional GnRH receptor signaling regulates striatal cholinergic neurons in neonatal but not in adult mice

Reproduction in mammals is controlled by hypothalamic gonadotropin-releasing hormone (GnRH) neurons. Recent studies from our laboratory established that the basal ganglia of the human brain contain additional large populations of GnRH synthesizing neurons which are absent in adult mice. Such extrahypothalamic GnRH neurons mostly occur in the putamen where they correspond to subsets of the striatal cholinergic interneurons (ChINs) and express GnRHR autoreceptors. In an effort to establish a mouse model for functional studies of striatal GnRH/GnRHR signaling, we carried out electrophysiological experiments on acute brain slices from male transgenic mice. Using PN4-7 neonatal mice, half of striatal ChINs responded with transient hyperpolarization and decreased firing rate to 1.2 µM GnRH, whereas medium spiny projection neurons remained unaffected. GnRH acted on its specific receptor because no response was observed in the presence of the GnRHR antagonist Antide. Addition of the membrane-impermeable G protein-coupled receptor inhibitor GDP-β-S to the internal electrode solution eliminated the effect of GnRH. Further, GnRH was able to inhibit ChINs in presence of tetrodotoxin which blocked action potential mediated events. Collectively, these data indicated that the receptor underlying the effects of GnRH in neonatal mice is localized within ChINs. GnRH responsiveness of ChINs was transient and entirely disappeared in adult mice. These results raise the possibility to use neonatal transgenic mice as a functional model to investigate the role of GnRH/GnRHR signaling discovered earlier in adult human ChINs.
Telomere Length Variation in Model Bryophytes

The ends of linear chromosomes of most eukaryotes consist of protein-bound DNA arrays called telomeres, which play essential roles in protecting genome integrity. Despite general evolutionary conservation in function, telomeric DNA is known to drastically vary in length and sequence between different eukaryotic lineages. Bryophytes are a group of early diverging land plants that include mosses, liverworts, and hornworts. This group of ancient land plants recently emerged as a new model for important discoveries in genomics and evolutionary biology, as well as for understanding plant adaptations to a terrestrial lifestyle. We measured telomere length in different ecotypes of model bryophyte species, including Physcomitrium patens, Marchantia polymorpha, Ceratodon purpureus, and in Sphagnum isolates. Our data indicate that all analyzed moss and liverwort genotypes have relatively short telomeres. Furthermore, all analyzed ecotypes and isolates of model mosses and liverworts display evidence of substantial natural variation in telomere length. Interestingly, telomere length also differs between male and female strains of the dioecious liverwort M. polymorpha and dioecious moss C. purpureus. Given that bryophytes are extraordinarily well adapted to different ecological niches from polar to tropical environments, our data will contribute to understanding the impact of natural telomere length variation on evolutionary adaptations in this ancient land plant lineage.
Audiovisual interactions outside of visual awareness during motion adaptation

Abstract Motion aftereffects (MAEs), illusory motion experienced in a direction opposed to real motion experienced during prior adaptation, have been used to assess audiovisual interactions. In a previous study from our laboratory, we demonstrated that a congruent direction of auditory motion presented concurrently with visual motion during adaptation strengthened the consequent visual MAE, compared to when auditory motion was incongruent in direction. Those judgments of MAE strength, however, could have been influenced by expectations or response bias from mere knowledge of the state of audiovisual congruity during adaptation. To prevent such knowledge, we now employed continuous flash suppression to render visual motion perceptually invisible during adaptation, ensuring that observers were completely unaware of visual adapting motion and only aware of the motion direction of the sound they were hearing. We found a small but statistically significant congruence effect of sound on adaptation strength produced by invisible adaptation motion. After considering alternative explanations for this finding, we conclude that auditory motion can impact the strength of visual processing produced by translational visual motion even when that motion transpires outside of awareness.
How brain structure–function decoupling supports individual cognition and its molecular mechanism

Abstract Functional signals emerge from the structural network, supporting multiple cognitive processes through underlying molecular mechanism. The link between human brain structure and function is region‐specific and hierarchical across the neocortex. However, the relationship between hierarchical structure–function decoupling and the manifestation of individual behavior and cognition, along with the significance of the functional systems involved, and the specific molecular mechanism underlying structure–function decoupling remain incompletely characterized. Here, we used the structural‐decoupling index (SDI) to quantify the dependency of functional signals on the structural connectome using a significantly larger cohort of healthy subjects. Canonical correlation analysis (CCA) was utilized to assess the general multivariate correlation pattern between region‐specific SDIs across the whole brain and multiple cognitive traits. Then, we predicted five composite cognitive scores resulting from multivariate analysis using SDIs in primary networks, association networks, and all networks, respectively. Finally, we explored the molecular mechanism related to SDI by investigating its genetic factors and relationship with neurotransmitter receptors/transporters. We demonstrated that structure–function decoupling is hierarchical across the neocortex, spanning from primary networks to association networks. We revealed better performance in cognition prediction is achieved by using high‐level hierarchical SDIs, with varying significance of different brain regions in predicting cognitive processes. We found that the SDIs were associated with the gene expression level of several receptor‐related terms, and we also found the spatial distributions of four receptors/transporters significantly correlated with SDIs, namely D2, NET, MOR, and mGluR5, which play an important role in the flexibility of neuronal function. Collectively, our findings corroborate the association between hierarchical macroscale structure–function decoupling and individual cognition and provide implications for comprehending the molecular mechanism of structure–function decoupling. Practitioner Points Structure–function decoupling is hierarchical across the neocortex, spanning from primary networks to association networks. High‐level hierarchical structure–function decoupling contributes much more than low‐level decoupling to individual cognition. Structure–function decoupling could be regulated by genes associated with pivotal receptors that are crucial for neuronal function flexibility.
Chytrid infections exhibit historical spread and contemporary seasonality in a declining stream-breeding frog

Species with extensive geographical ranges pose special challenges to assessing drivers of wildlife disease, necessitating collaborative and large-scale analyses. The imperilled foothill yellow-legged frog (Rana boylii) inhabits a wide geographical range and variable conditions in rivers of California and Oregon (USA), and is considered threatened by the pathogen Batrachochytrium dendrobatidis (Bd). To assess drivers of Bd infections over time and space, we compiled over 2000 datapoints from R. boylii museum specimens (collected 1897–2005) and field samples (2005–2021) spanning 9° of latitude. We observed a south-to-north spread of Bd detections beginning in the 1940s and increase in prevalence from the 1940s to 1970s, coinciding with extirpation from southern latitudes. We detected eight high-prevalence geographical clusters through time that span the species' geographical range. Field-sampled male R. boylii exhibited the highest prevalence, and juveniles sampled in autumn exhibited the highest loads. Bd infection risk was highest in lower elevation rain-dominated watersheds, and with cool temperatures and low stream-flow conditions at the end of the dry season. Through a holistic assessment of relationships between infection risk, geographical context and time, we identify the locations and time periods where Bd mitigation and monitoring will be critical for conservation of this imperilled species.
Prevalence and determinants of multimorbidity in the Canadian population

Multimorbidity, which is defined as having at least two or more chronic diseases concurrently, has been a rising public health issue in recent years in Canada and worldwide. The increasing prevalence of multimorbidity has posed a burden on the current health care system and quality of life for the Canadian population. There is a lack of up-to-date research on determinants of multimorbidity in the Canadian population, which is necessary to better understand and prevent multimorbidity. This study aims to determine the prevalence and risk factors of multimorbidity in the middle-aged and older Canadian adult population. Multivariable logistic regression analyses incorporating survey weights and biologically plausible interactions were conducted to examine the determinants of multimorbidity using data from the 2017/2018 Canadian Community Health Survey (CCHS). Of the 113,290 CCHS participants, 82,508 subjects who were aged 35 years and above were included in the study. The prevalence of multimorbidity was 22.20% (95% CI: 21.74%, 22.67%) and was greater for females. Multimorbidity was more likely in subjects who were obese, abstaining from alcohol, inactive, had a lower education level, widowed, divorced, or separated and was less likely among subjects living in Quebec. The protective effect of household income on multimorbidity decreased with age. Current smokers who reported extreme stress were more likely to have multimorbidity. Multimorbidity is associated with various determinants that need to be considered in chronic disease control and prevention. These results suggest that future research should focus not only on these determinants but also on the relationships between them. A future longitudinal study is required to provide causal evidence for the study findings.