Miracle-dz/UniFAR-FTUs huggingface dataset:
Divergent effects of listening demands and evaluative threat on listening effort in online and laboratory settings

Objective Listening effort (LE) varies as a function of listening demands, motivation and resource availability, among other things. Motivation is posited to have a greater influence on listening effort under high, compared to low, listening demands. Methods To test this prediction, we manipulated the listening demands of a speech recognition task using tone vocoders to create moderate and high listening demand conditions. We manipulated motivation using evaluative threat, i.e., informing participants that they must reach a particular “score” for their results to be usable. Resource availability was assessed by means of working memory span and included as a fixed effects predictor. Outcome measures were indices of LE, including reaction times (RTs), self-rated work and self-rated tiredness, in addition to task performance (correct response rates). Given the recent popularity of online studies, we also wanted to examine the effect of experimental context (online vs. laboratory) on the efficacy of manipulations of listening demands and motivation. We carried out two highly similar experiments with two groups of 37 young adults, a laboratory experiment and an online experiment. To make listening demands comparable between the two studies, vocoder settings had to differ. All results were analysed using linear mixed models. Results Results showed that under laboratory conditions, listening demands affected all outcomes, with significantly lower correct response rates, slower RTs and greater self-rated work with higher listening demands. In the online study, listening demands only affected RTs. In addition, motivation affected self-rated work. Resource availability was only a significant predictor for RTs in the online study. Discussion These results show that the influence of motivation and listening demands on LE depends on the type of outcome measures used and the experimental context. It may also depend on the exact vocoder settings. A controlled laboratory settings and/or particular vocoder settings may be necessary to observe all expected effects of listening demands and motivation.
Trials and Tribulations of MicroRNA Therapeutics

The discovery of the link between microRNAs (miRNAs) and a myriad of human diseases, particularly various cancer types, has generated significant interest in exploring their potential as a novel class of drugs. This has led to substantial investments in interdisciplinary research fields such as biology, chemistry, and medical science for the development of miRNA-based therapies. Furthermore, the recent global success of SARS-CoV-2 mRNA vaccines against the COVID-19 pandemic has further revitalized interest in RNA-based immunotherapies, including miRNA-based approaches to cancer treatment. Consequently, RNA therapeutics have emerged as highly adaptable and modular options for cancer therapy. Moreover, advancements in RNA chemistry and delivery methods have been pivotal in shaping the landscape of RNA-based immunotherapy, including miRNA-based approaches. Consequently, the biotechnology and pharmaceutical industry has witnessed a resurgence of interest in incorporating RNA-based immunotherapies and miRNA therapeutics into their development programs. Despite substantial progress in preclinical research, the field of miRNA-based therapeutics remains in its early stages, with only a few progressing to clinical development, none reaching phase III clinical trials or being approved by the US Food and Drug Administration (FDA), and several facing termination due to toxicity issues. These setbacks highlight existing challenges that must be addressed for the broad clinical application of miRNA-based therapeutics. Key challenges include establishing miRNA sensitivity, specificity, and selectivity towards their intended targets, mitigating immunogenic reactions and off-target effects, developing enhanced methods for targeted delivery, and determining optimal dosing for therapeutic efficacy while minimizing side effects. Additionally, the limited understanding of the precise functions of miRNAs limits their clinical utilization. Moreover, for miRNAs to be viable for cancer treatment, they must be technically and economically feasible for the widespread adoption of RNA therapies. As a result, a thorough risk evaluation of miRNA therapeutics is crucial to minimize off-target effects, prevent overdosing, and address various other issues. Nevertheless, the therapeutic potential of miRNAs for various diseases is evident, and future investigations are essential to determine their applicability in clinical settings.
Rapid seedling emergence of invasive Phytolacca americana is related to higher soluble sugars produced by starch metabolism and photosynthesis compared to native P. acinosa

Seedling emergence is an essential event in the life cycle of plants. Most invasive plants have an advantage in population colonization over native congeners. However, differential seedling emergence between invasive plants and native congeners, especially their mechanisms, have rarely been explored. In this study, we show that the seedlings of invasive Phytolacca americana emerge faster compared to native P. acinosa. Genome-wide transcriptomes of initially germinated seeds versus seedlings at 4 days after germination (DAG) suggested that differentially expressed genes (DEGs) in the photosynthesis-antenna proteins pathway were up-regulated in both P. americana and P. acinosa, while DEGs in starch and sucrose metabolism were significantly down-regulated in P. americana. Gene expression analysis indicated that photosynthesis-related DEGs reached their highest level at 3 DAG in P. americana, while they peaked at 4 DAG in P. acinosa. We also identified one β-amylase gene in P. americana (PameAMYB) that showed the highest expression at 1 DAG, and two β-amylase genes in P. acinosa that expressed lower than PameAMYB at 0 and 1 DAG. Enzymatic activity of β-amylases also suggested that P. americana had the highest activity at 1 DAG, which was earlier than P. acinosa (at 4 DAG). Soluble sugars, the main source of energy for seedling emergence, were showed higher in P. americana than in P. acinosa, and reached the highest at 4 DAG that positively affected by photosynthesis. These results indicate that the rapid seedling emergence of invasive P. americana benefited from the high soluble sugar content produced by starch metabolism and photosynthesis. Altogether, this work contributes to our fundamental knowledge on physiological and molecular mechanisms for plant invasion success.
Mind over mood: exploring the executive function’s role in downregulation

Emotion regulation plays a key role in well adapted behaviour, however, factors influencing individual differences in ER are still under investigation. Across two studies we investigate the complex relationship between executive functions (EFs) and emotional downregulation through two complementary research designs. The focus lies on key components of EFs—working memory, inhibitory control, and switching—and their relationship with effective emotional regulation. Surprisingly, switching emerged as the sole significant predictor in two multiple linear regression models, challenging the conventional belief that all major EFs broadly contribute to emotional downregulation. The first study, involving 248 Ecuadorian adults between 18 and 60 years old, used experimental tasks to assess the association between EFs and emotional regulation, aligning with existing literature that posits a link between EFs and emotional control. The second study, involving 180 Ecuadorian adults between 18 and 43 years old, added depth by incorporating self-report measures, providing a broader, ecologically valid perspective. However, these measures did not significantly predict downregulation, highlighting a gap between self-perception and actual cognitive abilities. Additionally, demographic predictors varied between the two studies, urging future research to consider methodological design and task selection carefully. The study also raises questions about the validity of commonly used measures, emphasising the need for more nuanced tools to capture the complexity of EFs and emotional regulation. Our findings suggest a targeted research avenue focusing on EFs for both future research and clinical interventions. Attention is called to the methodological decisions that can influence the observed associations, and the need for broader demographic representation in future studies.
Cultural Differences in Apparel Product Return Behavior: An Exploratory Study of Indonesia and USA E-Commerce Consumers

Results and Discussion. Results show differences and similarities in consumer return behavior and expectations between Indonesia and U.S. Regarding similarities, most respondents rarely read return policies before purchasing, aligning with low uncertainty avoidance in both countries according to the Hofstede Cultural Dimension theory (Hofstede Insight, 2022). Uncertainty avoidance reflects the ability of a society to tolerate ambiguity. Equally important, factors such as trust in the brand and product price influenced consumers’ willingness to read return policies
Model Projections of East Asian Summer Climate under the ‘Free Arctic’ Scenario

Abstract This paper addresses the ‘ice-free Arctic’ issue under the future global warming scenario. Four coupled climate models used in the third phase of the Coupled Model Intercomparison Project (CMIP3) were selected to project summer climate conditions over East Asia once the Arctic becomes ice-free. The models project that an ice-free Arctic summer will begin in the 2060s under the SRESA1B (according to IPCC Special Reports on Emissions Scenarios) simulations. Our results show that the East Asian summer monsoons will tend to be stronger and that the water vapor transport to central northern China will be strengthened, leading to increased summer precipitation in central northern China. The models also project an intensified Antarctic Oscillation, a condition which favors increased precipitation in South China’s Yangtze River Valley. The overall precipitation in Northwest China is projected to increase under ice-free Arctic summer conditions.
Validation of the Korean Version of the Health Care Climate Questionnaire among Cancer Survivors

Healthcare professionals should support autonomy in their patients in order for them to maintain the motivation to cope actively with their conditions. The Health Care Climate Questionnaire (HCCQ) is useful for assessing patients’ perceptions of the autonomy support provided to them. We aimed to validate the psychometric properties of the Korean version of the HCCQ (HCCQ-K) among Korean cancer survivors. This study evaluated the factor structure, concurrent validity, and internal consistency. Data from 367 cancer survivors were analyzed using confirmatory factor analysis (CFA), Pearson’s correlations, and Cronbach’s α values. The CFA validated that the single-factor structure of the HCCQ-K had an excellent fit that was consistent with that of the original English version. Concurrent validity was confirmed by moderate correlations between the HCCQ-K and both psychological well-being and self-management. Reliability was verified by satisfactory internal consistency, with a Cronbach’s α value of 0.91 and strong item-total and inter-item correlations. The HCCQ-K is therefore a valid and reliable tool for assessing autonomy support provided by healthcare professionals to Korean cancer survivors. The HCCQ-K may help healthcare professionals understand their patients’ needs for autonomy support and develop strategies to motivate active coping behaviors.
A BIM-GIS integration method in support of the assessment and 3D visualisation of flood damage to a building

Abstract Flood damage assessment (FDA) provides an effective basis for the flood risk management process to evaluate and treat risks. Current FDA methods, however, are ill-equipped to account for the distinctiveness of buildings in the analysis. This is mainly due to their limited input data that on the one hand requires complete building information (well-represented in building information models [BIM]) and, on the other hand, the flood information (commonly managed by geographic information systems [GIS]). While such requirements cannot be satisfied via independent use of BIM or GIS, their integration can potentially be used for this purpose. The current BIM-GIS integration methods, however, are limited or application-specific. Therefore they fall short in satisfying the micro-level FDA information requirements. This paper presents a new data model as a profile of Geography Markup Language (GML) for BIM-GIS integration to support the detailed assessment and 3D visualisation of flood damage to buildings. The model was further evaluated using a case study and found effective for this purpose.
Evaluation and application of Finite Element Sea Ice-Ocean Model (FESOM) for the Arctic-North Atlantic region in variable resolution global simulations

The changes and variability of the Arctic – North Atlantic Oceans and the inter-exchange of water mass and heat is of crucial relevance for the global ocean and climate. In this work the Finite Element Sea-ice Ocean Model (FESOM) is used to simulate the global ocean with focus on the Arctic – North Atlantic region. FESOM is formulated on unstructured meshes and offers variable-resolution functionality which is difficult to achieve in traditional structured-mesh models. With this powerful tool we are able to resolve the key areas with locally refined resolutions in global simulations. The performance of FESOM in the Arctic Ocean and North Atlantic on large time scales is first evaluated in a 240-yr hindcast experiment. The model can reproduce realistic Atlantic Meridional Overturning Circulation (AMOC) and realistic Arctic freshwater content variability and sea ice extent. A water-hosing experiment is conducted to study the model sensitivity to increased freshwater input from Greenland Ice Sheet (GrIS) melting in a 0.1 Sv discharge rate scenario. The released freshwater from Greenland can penetrate into the Arctic Ocean, especially in the Eurasian Basin. The anomalous freshwater also leads to a reduction in the AMOC strength and changes in freshwater exchange between the two oceans. Simulations with different local resolutions of 24 km and 9 km in the Arctic Ocean and surrounding regions are carried out to study the influence of resolution on the simulated Arctic Ocean and Arctic-Subarctic fluxes. Both simulations can reasonablly simulate the mean state and variability of sea ice condition, freshwater content in the Arctic Ocean, and the fluxes through the Arctic gateways when compared to observations and previous model studies. Although the high resolution (9 km) run tends to improve the representation
A Probabilistic Economic/CO2eq Emissions Dispatch Model: Real Applications

The worldwide evolution of the electric systems requires, i. a. : a) fossil-fuel generators with carbon capture and b) clean technologies based on renewable energies. For this reason, dispatch centers are in constant search for solutions in order to improve decision-making that involve the generation matrix. Consequently, in this paper a probabilistic economic dispatch model is proposed. The proposed methodology considers uncertainties, affecting the short–term control, the emission factors and the load dispatching. Wind speed, solar radiation and power demand are treated as random variables. Unavailability factors are also taken into account. The solution strategy is based on the Monte Carlo method and a bi-objective linear optimization constrained procedure. The approach involves multidimensional probabilities, descriptive statistics, clusters studies and bimodal analysis. The optimal solution yields the probability distributions of system marginal prices, dual costs, load-shedding, thermal and renewable power generation and emission factors. The proposed model and methodology are applied to the electric power system of northern Chile.
Assessment of carbon stock and selected soil fertility indicators in a bush encroached savanna at Erichsfelde farm, Namibia

Bush encroachment is a form of land degradation common predominantly in semi-arid areas of the world. The resulting habitat degradation and loss of resource productivity make bush encroachment a serious environmental and economic problem in Namibia. Despite these negative effects, bush encroachment offers potential woody carbon stock storage, which can render Namibia a net carbon sink. This study was, therefore, aimed at quantifying potential woody carbon stock storage from different pools and assessing selected soil fertility indicators in low, medium and high bush-encroached sites at Erichsfelde farm in Otjozondjupa region. This was a quantitative study employing a stratified random sampling with systematic sampling along transects. For vegetation surveys in each site, five 20m x 10m plots were set up along two line transects, while established allometric equations were applied to related measured vegetation variables to estimate carbon stock. Additionally, five 1m x 1m soil pits were nested within the vegetation plots and soil samples collected at different soil depths for analysis. Across the three sites, the Kruskal-Wallis test showed no significant difference in the total (P=0.294>0.05) and above-ground (P=0.718>0.05) carbon stock. However, the belowground carbon stock was significantly higher in the medium encroached site (P<0.001). This can be attributed to the fact that savanna vegetation accumulates most of its biomass underground as a protection against fire and herbivory. Additionally, the dense shrubs in the high encroached site do not invest in the below-ground biomass and carbon stock because of low herbivory as livestock will find it difficult to roam in there as oppose to the medium encroached site that feature higher below-ground carbon storage to protect the vegetation from herbivory and fire. The fact that the
Application And Challenges of Alphazero Algorithm in Chinese Chess

In the field of artificial intelligence, AlphaZero has achieved significant success in games like Go and Shogi. However, its application in Chinese Chess remains relatively unexplored. This study aims to unveil the potential and limitations of AlphaZero in Chinese Chess and explore strategies for optimizing its performance. In this paper, we begin by reviewing the fundamental principles and algorithmic structure of AlphaZero, emphasizing its deep reinforcement learning and self-play characteristics. Subsequently, we delve into the specific application of AlphaZero in Chinese Chess, encompassing aspects such as chess rule representation, training procedures, position evaluation, and strategy prediction. By analyzing successful instances of AlphaZero in Chinese Chess, we showcase its potential in the domain of board games. Furthermore, this paper elucidates the challenges that AlphaZero encounters in the context of Chinese Chess, including issues related to computational complexity and position representation. We particularly underscore the potential cost escalation due to high computational resource requirements and the risk of data loss or excessive time consumption associated with extended computation periods. IN conclusion, this research provides valuable insights into the application of AlphaZero in the realm of Chinese Chess and offers recommendations for future research directions to further expand its utility in this domain.
Easy-to-Hard Domain Adaptation With Human Interaction for Hyperspectral Image Classification

In real-world hyperspectral image classification (HSIC), the limited annotated examples usually lead to an insufficiently trained classifier, which further generates low classification accuracy. To overcome this challenge, domain adaptation (DA) methods have been developed to transfer learnable knowledge from the external HSIs with sufficient labeled examples (i.e., the source domain) to the interested HSIs with scarce labeled examples (i.e., the target domain). Conventional DA approaches often pseudo-label the examples with high classification confidence and then incorporate them into the training process. However, due to the significant domain gap, relying solely on confident examples may not be adequate to achieve satisfactory performance. Therefore, this article proposes an interactive easy-to-hard DA method (IEH-DA) to arrange the adaptation process so that the “easy” examples are adapted ahead of the “hard” ones. In an early stage, the easy examples with high pseudo-labeling confidence are selected for the adversarial learning-based DA. In a later stage, the “hard” examples with high informativity are further selected, and they are interactively labeled by human experts to provide accurate supervision information for adaptation. As a result, the examples in the target domain are used in an easy-to-hard way, which forms a curriculum sequence for orderly model training. Extensive experiments conducted on typical public datasets demonstrate that IEH-DA outperforms other state-of-the-art DA methods for HSIC.
Study of beam-beam interaction in FCC-ee including updated transverse and longitudinal Impedances

Beam-beam interaction in FCC-ee can be seriously affected by the vacuum chamber coupling impedance resulting in a safe tune areas reduction, tune shifts and spread, bunch length and energy spread variation. The interplay of the two effects has a drastic impact on the stability of colliding bunches and respectively on the achievable luminosity. In this paper, beam-beam collisions in FCC-ee with 4 interaction points are studied including the updated transverse and longitudinal impedances.
Computer system for determining a customized animal feed

The present invention discloses a method and system for making an on-demand animal feed. The method and system comprises a material data and the animal data, evaluation data and from the more than one region. Documentation for the on-demand feed is calculated from the material data representing the mix of materials which can be obtained from one or more locations. The demand feed is calculated is designed to meet the nutritional requirements of the animal feed. The nutritional requirements are derived from the animal data. In addition, the feed will be optimized to meet the criteria of the requirements. Then, the evaluation criteria along with the feed data and the animal data, that is, (ⅰ) by using the weight of the production rate of the animal, (ⅱ) feed per increment weight of the animal cost, and (ⅲ) feed per increment weight of animals and it provides an on-demand feed which is calculated on the basis of the evaluation data representative of one or more of the evaluation criteria. Feed on demand, computer systems, data