Strong Ones Research Articles

Potter Cove's Heavyweights: Estimation of Species' Interaction Strength of an Antarctic Food Web.

In the West Antarctic Peninsula, global warming has led to severe alterations in community composition, species distribution, and abundance over the last decades. Understanding the complex interplay between structure and stability of marine food webs is crucial for assessing ecosystem resilience, particularly in the context of ongoing environmental changes. In this study, we estimate the interaction strength within the Potter Cove (South Shetland Islands, Antarctica) food web to elucidate the roles of species in its structure and functioning. We use these estimates to calculate food web stability in response to perturbations, conducting sequential extinctions to quantify the importance of individual species based on changes in stability and food web fragmentation. We explore connections between interaction strength and key topological properties of the food web. Our findings reveal an asymmetric distribution of interaction strengths, with a prevalence of weak interactions and a few strong ones. Species exerting greater influence within the food web displayed higher degree and trophic similarity but occupied lower trophic levels and displayed lower omnivory levels (e.g., macroalgae and detritus). Extinction simulations revealed the key role of certain species, particularly amphipods and the black rockcod Notothenia coriiceps, as their removal led to significant changes in food web stability and network fragmentation. This study highlights the importance of considering species interaction strengths in assessing the stability of polar marine ecosystems. These insights have crucial implications for guiding monitoring and conservation strategies aimed at preserving the integrity of Antarctic marine ecosystems.

The paradox of argument strength: how weak arguments undermine the persuasive effects of strong arguments.

This paper analyzes effects of the mutual presentation of weak and strong arguments. Departing from the prevalent "the-more-the-better" heuristic, our research scrutinizes whether the inclusion of weak arguments enhances or diminishes the persuasive impact of strong arguments. Leveraging insights from judgment formation literature, we conducted four experimental studies on political and health-related topics to unravel whether the presenting weak arguments strengthens the persuasive effect of a strong argument (adding) or actually weakens this persuasive effect (averaging). The results show that providing supporting arguments of moderate strength along with a strong argument increases persuasion, representing an additive pattern. However, presenting weak supporting arguments along with a strong argument reduces the persuasive effect of the strong argument, representing an averaging pattern. Exposure to weak arguments diminishes the strength of strong ones, suggesting the omission of weak arguments. These findings underscore the vital role of strategically selecting arguments to optimize persuasion across disciplines.

Pragmatic competence and pragmatic tolerance in foreign language acquisition—revisiting the case of scalar implicatures

Abstract Previous L2 studies used binary Truth-Value-Judgment (TVJ) tasks to investigate L1–L2 differences in scalar implicature derivation (some X implicates some but not all X). They examined participants’ judgments of sentences with weak scalar expressions (“Timothy ate some of the pretzels”) when stronger ones are true (“Timothy ate all of the pretzels”). Some studies indicate adult L2 learners are less likely than L1 users to accept such statements while others found the opposite, concluding that implicature derivation is “costly” for L2 learners, rendering them less pragmatically competent than L1 users. Importantly, related L1 research suggests that TVJ tasks only capture sensitivity to under-informativeness. This sensitivity might be completely overridden by metalinguistic attitudes in binary tasks, whereas graded tasks reveal nuanced judgment patterns. Exploring L2 response behaviors, we tested English L1 speakers and competent German L2 English learners using binary and graded tasks. In both tasks, we found evidence of pragmatic responding with no evidence of differences between groups. Bayes factor analyses of the graded data favored H0 over the hypotheses that L2 learners provide fewer or more rejections to under-informative input than L1 learners. We explore implications for L2 learners’ pragmatic abilities, differences with previous studies, and the role of TVJ tasks in under-informative contexts.

THE ROLE OF FINANCIAL PERFORMANCE IN DIFFERENCE OF TWO MANUFACTURER’S BRAND VALUE

Brands are becoming more and more important for enterprises that spend significant amounts on building strong ones. Howewer, the value of brands and the way it should be represented in financial reports is still controversial. Our general objective is to present a calculation method able to estimate brand value that we establish for the calculation method of Interbrand corporation and results of our own survey research. Our specific objective in the course of analysis is to determine Daimler AG Mercedes-Benz’s and Nestlé cereal’s brand value based on data of 2022. Firstly we calculated the so-called Economic Value of researched enterprises by analysing their financial reports. Applying the results from our survey research we determined the role of brand plays in gaining EVA, which is Brand Income. Finally we calculated a ratio using WACC which we discounted the Brand Income with we obtained the Brand Value. Our survey research is assembled according to Keller’s Brand Equity Model. During our research we have confirmed our hypothesis that people filling the survey consider brand to be a more important purchasing aspect in case of Mercedes-Benz than Nestlé cereals; purchasing Nestlé cereals respondents consider brand as the most important purchasing aspect out of the given list; respondents choose analysed brands contra unknown ones which has the same features and price. Final results show that Mercedes-Benz and Nestlé cereals have strong brand knowledge, the Mercedes brand value was several times higher, while the difference between these brand values caused by not the different financial performance but rather the devation of brand power and strength of the analysed manifacture companies.

CWF: Consolidating Weak Features in High-quality Mesh Simplification

In mesh simplification, common requirements like accuracy, triangle quality, and feature alignment are often considered as a trade-off. Existing algorithms concentrate on just one or a few specific aspects of these requirements. For example, the well-known Quadric Error Metrics (QEM) approach [Garland and Heckbert 1997] prioritizes accuracy and can preserve strong feature lines/points as well, but falls short in ensuring high triangle quality and may degrade weak features that are not as distinctive as strong ones. In this paper, we propose a smooth functional that simultaneously considers all of these requirements. The functional comprises a normal anisotropy term and a Centroidal Voronoi Tessellation (CVT) [Du et al. 1999] energy term, with the variables being a set of movable points lying on the surface. The former inherits the spirit of QEM but operates in a continuous setting, while the latter encourages even point distribution, allowing various surface metrics. We further introduce a decaying weight to automatically balance the two terms. We selected 100 CAD models from the ABC dataset [Koch et al. 2019], along with 21 organic models, to compare the existing mesh simplification algorithms with ours. Experimental results reveal an important observation: the introduction of a decaying weight effectively reduces the conflict between the two terms and enables the alignment of weak features. This distinctive feature sets our approach apart from most existing mesh simplification methods and demonstrates significant potential in shape understanding. Please refer to the teaser figure for illustration.

The strength of weak ties and fake news believability

Are we more likely to believe a social media news story shared by someone with whom we have a strong or weak tie? We tend to trust close ties more than weak ties, but weak ties are sources of new information more often than strong ones. We conducted an online experiment to examine the effect of tie strength (strong ties vs. weak ties) on the decision to believe or not believe fake news stories. Participants perceived false stories from weak ties to be more believable than false stories from strong ties (after controlling for the trustworthiness of the sharer). We found that a sharer's perceived ability to share reliable information plays a significant role in individuals' decision to believe news stories on social media, regardless of whether the source is a strong or weak tie. Interestingly, a sharer's perceived integrity was found to be important only when the information came from weak ties, while a sharer's perceived benevolence was not important for either weak or strong ties. These findings show that the perceived integrity of the sharer is a key factor in the decision to believe stories from weak ties, more so than from strong ties. Furthermore, a sharer's perceived ability to share reliable information is less critical when weak ties share true stories. The impact of weak ties does not stem from the novelty of their information, as we used identical headlines across both study groups. Thus, while the strength of weak ties effect is present in this context, the underlying theoretical mechanism differs from the novelty of information traditionally observed in other settings.

Why sports? Sketching a typology of young people’s reasons for taking part in sports

We sketch a typology of sport participation reasons grounded in data from 2581 short-answers from youths in organized sports. We develop the typology abductively against theories from philosophy, sociology, and psychology to better capture the full scale of possible participation reasons in organized youth sport. Key empirical findings are, first, that in addition to having fun and being with friends, youths participate to expand their social networks and develop weak social ties into stronger ones. Second, competition and mastery are intertwined. Competitions can function as a measure stick for individual and team skill development. Third, physical and mental health reasons are common participation reasons. Youths appreciate how sport impact their everyday health. Fourth, youths combine reasons for sport participation in diverse ways that have theoretical and practical implications. We end by suggesting two ideal types of how organized sport participation reasons combine—a heavy and light sport appreciation.

De novo DNA-based catch bonds.

All primary chemical interactions weaken under mechanical stress, which imposes fundamental mechanical limits on the materials constructed from them. Biological materials combine plasticity with strength, for which nature has evolved a unique solution-catch bonds, supramolecular interactions that strengthen under tension. Biological catch bonds use force-gated conformational switches to convert weak bonds into strong ones. So far, catch bonds remain exclusive to nature, leaving their potential as mechanoadaptive elements in synthetic systems untapped. Here we report the design and realization of artificial catch bonds. Starting from a minimal set of thermodynamic design requirements, we created a molecular motif capable of catch bonding. It consists of a DNA duplex featuring a cryptic domain that unfolds under tension to strengthen the interaction. We show that these catch bonds recreate force-enhanced rolling adhesion, a hallmark feature of biological catch bonds in bacteria and leukocytes. This Article introduces catch bonds into the synthetic domain, and could lead to the creation of artificial catch-bonded materials.

Probabilistic assessment of rockburst risk in TBM-excavated tunnels with multi-source data fusion

In recent years, tunnel boring machines (TBMs) have become extensively utilized in underground engineering projects. However, as a prevalent type of dynamic geological hazard, rockburst poses a serious threat to the safety of personnel, equipment, and property. To ensure the safe advancement of TBMs, we integrate the data of microseismic monitoring, TBM excavation, and surrounding rock and establish multiple probabilistic assessment models of rockburst risk using probabilistic ensemble learning and quantum particle swarm optimization. In order to identify the most optimal model for geological engineers, a comprehensive evaluation system is devised based on metrics like accuracy, Cohen’s kappa, and F1-score. This system provides a thorough assessment of the models’ global and local generalization performance. The results indicate that the classification and regression tree-extremely randomized trees (CART-ERT) hybrid model achieves the highest score, demonstrating superior generalization performance with an accuracy of 93.06% and a Cohen’s kappa of 0.9074. Moreover, the F1-scores for no rockburst, low rockburst, moderate rockburst, and strong rockburst are 0.9412, 0.9444, 0.9189, and 0.9189, respectively. Based on the operational framework of the CART-ERT hybrid model, a user-friendly graphical user interface (GUI) system is developed. This significantly enhances the practicality and deployability of the model. Through application in a TBM diversion tunnel project in Xinjiang, the on-site early-warning accuracy of rockburst with the GUI system reaches 90%. Notably, the GUI system maintains high early-warning sensitivity and reliability for high-intensity rockburst such as moderate and strong ones. Lastly, to enhance the model’s interpretability, a variable importance measure (VIM) analysis on 14 features extracted from three types of heterogeneous data is conducted to assess their contributions to the early warning of rockburst. We discover that the cumulative energy change rate of microseismic events exhibits the highest importance score, indicating its crucial role in rockburst early warning.

A novel three-phase expansion algorithm for uncovering communities in social networks using local influence and similarity in embedding space

Community detection can help uncover and understand complex networks’ underlying patterns and structures. It involves identifying cohesive groups with similar entities while being separated from other groups. Social networks are a prime example of an area where community detection is particularly relevant, as it can provide insight into the behaviors of individuals. Several community detection methods have been proposed, each addressing the problem from different perspectives. However, the rise of vast and intricate networks from diverse domains has necessitated the development of community detection methods that can effectively handle large-scale graphs. This study introduces a novel three-phase expansion algorithm for community discovery based on nodes’ local information and similarity in embedding space. The proposed model consists of three steps. In the first stage, we generate an embedding space in which nodes are represented as vectors, and we extract nodes that greatly influence others and have an extraordinary ability to create communities using degree centrality measures. Then, based on cosine similarity in the embedding space, we group the most similar nodes to the influential ones in the same community and create an initial community structure. In the last phase, we extract the weak communities from the initial community structure generated in the second phase and merge them with the strong ones. We conduct extensive experiments on both real-world and synthetic networks to demonstrate the effectiveness of our proposal. The experimental results show that the proposed algorithm performs better than other widely used algorithms and is highly reliable and efficient in large-scale graphs.

More than just your name: Public donations drive inferences of egoistic and altruistic motives

AbstractThe present research shows that public (vs. anonymous) donations are viewed as a sign of egoistic motives, such as wanting to impress others. In addition, such public donations also are viewed as a sign of altruistic motives, such as wanting to encourage others to donate. These perceptions inform inferences of donors' communal traits, with egoistic motives suggesting weaker communal traits, and altruistic motives suggesting stronger ones. Inferences of communal traits impact behavior, with stronger communal traits predicting greater charitable donations. In sum, public modes of giving can decrease donations (through inferences of egoistic motives and weaker communal traits) and increase donations (through inferences of altruistic motives and stronger communal traits). These effects occur in the context of $100 and $10 donations (Study 1) and impact real contributions of money (Study 2) and volunteer work (Study 3). Platform managers can strengthen inferences of altruistic motives by communicating that public donations can motivate others to give (Study 4). Together, these findings enhance understanding of how public forms of giving influence others to donate, which has practical implications for donation platform managers.

Brain Structural Connectivity Guided Vision Transformers for Identification of Functional Connectivity Characteristics in Preterm Neonates.

Preterm birth is the leading cause of death in children under five years old, and is associated with a wide sequence of complications in both short and long term. In view of rapid neurodevelopment during the neonatal period, preterm neonates may exhibit considerable functional alterations compared to term ones. However, the identified functional alterations in previous studies merely achieve moderate classification performance, while more accurate functional characteristics with satisfying discrimination ability for better diagnosis and therapeutic treatment is underexplored. To address this problem, we propose a novel brain structural connectivity (SC) guided Vision Transformer (SCG-ViT) to identify functional connectivity (FC) differences among three neonatal groups: preterm, preterm with early postnatal experience, and term. Particularly, inspired by the neuroscience-derived information, a novel patch token of SC/FC matrix is defined, and the SC matrix is then adopted as an effective mask into the ViT model to screen out input FC patch embeddings with weaker SC, and to focus on stronger ones for better classification and identification of FC differences among the three groups. The experimental results on multi-modal MRI data of 437 neonatal brains from publicly released Developing Human Connectome Project (dHCP) demonstrate that SCG-ViT achieves superior classification ability compared to baseline models, and successfully identifies holistically different FC patterns among the three groups. Moreover, these different FCs are significantly correlated with the differential gene expressions of the three groups. In summary, SCG-ViT provides a powerfully brain-guided pipeline of adopting large-scale and data-intensive deep learning models for medical imaging-based diagnosis.

An Investigation of Efficiency Issues in a Low-Pressure Steam Turbine Using Neural Modelling.

This study utilizes neural networks to detect and locate thermal anomalies in low-pressure steam turbines, some of which experienced a drop in efficiency. Standard approaches relying on expert knowledge or statistical methods struggled to identify the anomalous steam line due to difficulty in capturing nonlinear and weak relations in the presence of linear and strong ones. In this research, some inputs that linearly relate to outputs have been intentionally neglected. The remaining inputs have been used to train shallow feedforward or long short-term memory neural networks using measured data. The resulting models have been analyzed by Shapley additive explanations, which can determine the impact of individual inputs or model features on outputs. This analysis identified unexpected relations between lines that should not be connected. Subsequently, during periodic plant shutdown, a leak was discovered in the indicated line.

Taking time to compose thoughts with prefrontal schemata

Under what conditions can prefrontal cortex direct the composition of brain states, to generate coherent streams of thoughts? Using a simplified Potts model of cortical dynamics, crudely differentiated into two halves, we show that once activity levels are regulated, so as to disambiguate a single temporal sequence, whether the contents of the sequence are mainly determined by the frontal or by the posterior half, or by neither, depends on statistical parameters that describe its microcircuits. The frontal cortex tends to lead if it has more local attractors, longer lasting and stronger ones, in order of increasing importance. Its guidance is particularly effective to the extent that posterior cortices do not tend to transition from state to state on their own. The result may be related to prefrontal cortex enforcing its temporally-oriented schemata driving coherent sequences of brain states, unlike the atemporal “context” contributed by the hippocampus. Modelling a mild prefrontal (vs. posterior) lesion offers an account of mind-wandering and event construction deficits observed in prefrontal patients.

What Are the Factors That Enable Thread Lifting to Last Longer?

Thread-lifting traditionally addressed aging-related skin laxity by leveraging precise thread placement and traction. However, recent advancements, notably cog threads, expanded its application to younger patients seeking facial contour refinement. These newer threads effectively lift sagging areas and refine facial contours, broadening the procedure’s appeal. Challenges arise in selecting threads due to variable physician preferences and patient needs. Clear indications for thread efficacy are vital for credibility and tailored selection. Thread choice depends on tissue laxity, necessitating lighter threads for minimal laxity and stronger ones for significant sagging. However, no single thread universally suits all cases. Combining different threads is favored for optimal outcomes and minimizing side effects. Excessive traction post-procedure may lead to prolonged discomfort and skin irregularities. Post-procedural tension adjustments through massage remain debated, potentially conflicting with minimally invasive principles. Understanding thread characteristics guides tailored selection, considering patient conditions and procedural goals. This comprehensive understanding extends beyond specific products, aiming for optimal outcomes in thread-lifting procedures. Key factors influencing outcomes encompass thread materials, thickness, cog shapes, insertion depth, lifting vectors, and absorbable thread expiration dates.

Strong Leaders in the Former Soviet Union: Successful or Simply Authoritarian?

ABSTRACT The term “strong leader” is generally understood to mean a leader who concentrates power in his or her hands, dominates public policy and the political party to which he or she belongs, and takes the big decisions. Many contemporary politicians present themselves as leaders in this mold and there is substantial public support around the world for this type of leader. Recent research, however, has questioned the desirability of strong leaders, finding that they are high-risk individuals who often have negative records in office. This article is concerned specifically with the personalist authoritarian strong leaders who hold office in the Former Soviet Union (FSU), a grouping that has received little attention in this emerging literature. The article sets out to ascertain whether these personalist authoritarians have been successful leaders as well as strong ones. We undertake this by examining performance (according to a variety of socio-economic and governance indicators) in the 15 states of the FSU in the period 2000–2020. This study finds no evidence of exceptional performance in the states with personalist authoritarian leaders in this time period. Rather, what these personalist leaders have offered is authoritarianism, poor governance, and socio-economic performance that is middling to poor.

War power through restraint: The politics of unilateral military action after 1945

AbstractFrom a historical perspective, presidents have frequently directed the use of military force without explicit permission from Congress. Yet, presidents still court legislative approval on select occasions. Why do presidents sometimes seek congressional authorization and other times do not? I explain authorization‐seeking behavior according to variations in presidential bargaining strength. I argue that both weak and strong presidents prefer authorization‐seeking; by obtaining congressional backing, weak presidents conceal a lack of national resolve from international audiences, while strong ones use approval to enhance their coercive authority. Presidents with mid‐level bargaining strength, however, prefer unilateral action; on the one hand, unilateral action may demonstrate resolve in the face of potential legislative resistance, while on the other, it avoids contentious debate that risks “muddying” the diplomatic waters. I illustrate these arguments by revisiting four prominent historical cases: the Korean War, the Gulf of Tonkin crisis, the invasion of Cambodia, and the Persian Gulf War.

Female Representation in Pakistani Digital Media: A Comparative Critical Feministic Study of Rehman’s “Mere Pas Tum Ho" & Ahmed’s “Sinf-e-Ahan”

The present study aims to explore the portrayal of female characters by male and female writers in Pakistani digital media. Hence, the primary objective of this study is to figure out which gender is focused to show the strong and positive side of women. Meanwhile, the secondary objective is to trace the gender stereotypes in the context of the two particular dramas. Fairclough (1992) model of critical discourse analysis has been applied along with Beauvoir (1997) notion of feminism as the framework of the study. Two Pakistani dramas namely “Mere Pas Tum Ho" and Sinf-e-Ahan" have been the source of data. Meanwhile, a particular sample of twenty scenes from ten episodes of each drama has been selected through purposive sampling. However, the findings revealed that in Pakistani Digital media, male writers intend to portray women as negative, disloyal, passive, and emotionally frail creatures while on the other hand, female writers are trying to show the positive side of women by presenting them as strong and independent ones who are challenging patriarchal norms by pursuing their careers and fighting against every unjust thing they see happening around.

Exploring dolomite as a promising support for Ni catalysts in CO2 methanation

Ni catalysts supported on Al-modified calcined dolomite were developed, using a natural mineral as the precursor. Treatment with 3% w/w Al improved thermal stability and increased the surface area. The variation in Ni loading (5–30% w/w) was studied to characterize the structural, morphological, and chemical properties. The CO2 capture capacity of the solids, evaluated by Thermogravimetric Analysis at 400 °C (100–800 μmol∙g−1), decreased with increasing Ni loading due to the reduction of basic sites. CO2-TPD analyses revealed the presence of captured CO2 in various basic sites, especially in the strong ones, with efficient formation of thermally stable carbonates. In catalytic tests at 400 °C, conversions exceeding 50% were achieved for higher Ni loadings and around 50% for lower loadings, with 100% selectivity towards CH4. The application of in situ and operando Diffuse reflectance infrared Fourier transform spectroscopy techniques provided insights into the formation of carbonates and their transformation into formate, methoxy, and formyl species, explaining the total selectivity towards CH4 and the absence of CO in the products. This comprehensive approach significantly contributes to the understanding of the reaction dynamics and opens new perspectives for the utilization of Ni catalysts supported on modified dolomite.

The Earthquake Fatality Load: A Measure of Impact

ABSTRACT A key measure of the earthquake problem in a country is the ratio of fatalities to population size. We propose that the new parameter earthquake fatality load per year objectively measures the level of the population suffering in seismically active countries, that is, it indicates the average annual cost in lives. We present a list of this new parameter for 35 seismically important countries with adequate data for this estimate. Among these countries, Ecuador, Lebanon, Haiti, Turkmenistan, Iran, and Portugal have experienced the greatest loads during the last five centuries. The earthquake fatality load decreases significantly as a function of time in the 18 countries with enough data for analysis. Major factors causing this may be improved resistance to shaking by the built environment, and migration of the rural population leaving weak buildings and occupying stronger ones in large cities.