julilili42/papers huggingface dataset:
Investigating the Social Boundaries of Fairness by Modeling Ultimatum Game Responders’ Decisions with Multinomial Processing Tree Models
2025-01-03

Fairness in competitive games such as the Ultimatum Game is often defined theoretically. According to some of the literature, in which fairness is determined only based on resource allocation, a proposal splitting resources evenly (i.e., 5:5) is generally assumed as fair, and minimal deviation (i.e., 4:6) is considered enough to classify the proposal as unfair. Relying on multinomial processing tree models (MPTs), we investigated where the boundaries of fairness are located in the eye of responders, and pit fairness against relative and absolute gain maximization principles. The MPT models we developed and validated allowed us to separate three individual processes driving responses in the standard and Third-Party Ultimatum Game. The results show that, from the responder’s perspective, the boundaries of fairness encompass proposals splitting resources in a perfectly even way and include uneven proposals with minimal deviance (4:6 and 6:4). Moreover, the results show that, in the context of Third-Party Ultimatum Games, the responder must not be indifferent between favoring the proposer and the receiver, demonstrating a boundary condition of the developed model. If the responder is perfectly indifferent, absolute and relative gain maximization are theoretically unidentifiable. This theoretical and practical constraint limits the scope of our theory, which does not apply in the case of a perfectly indifferent decision-maker.
Connectome-based disentangling of epilepsy networks from insular stereoelectroencephalographic leads
2025-01-03

Objective Epilepsy is considered as a network disorder of interacting brain regions. The propagation of local epileptic activity from the seizure onset zone (SOZ) along neuronal networks determines the semiology of seizures. However, in highly interconnected brain regions such as the insula, the association between the SOZ and semiology is blurred necessitating invasive stereoelectroencephalography (SEEG). Normative connectomes on MRI data enable to link different symptoms and lesion locations to a common functional network. The present study applied connectomics to disentangle epilepsy networks from insular SEEG recordings and to describe their relationship to seizure semiology. Methods We retrospectively extracted functional networks by normative connectome analysis from 118 insular contacts depicting epileptic discharges during SEEG in 20 epilepsy patients. The resulting epilepsy networks were correlated to the corresponding semiology by voxel-wise regression and multivariate analyses of variances. Results Epileptic foci were found in the posterior insula for somatosensory, other sensory and motor seizures, while cognitive and autonomic symptoms were related to the anterior insula. We identified insular connections to the superior temporal gyrus and heschl gyrus in sensory seizures and projections to the somatosensory cortex in somatosensory seizures. Insula-basal ganglia pathways were found in cognitive seizure manifestations, while insular connectivity to fronto-basal regions were strongest in patients with autonomic seizures. Conclusion The semiology of seizures is mirrored in the functional connectivity of insular epileptic discharges. Combining SEEG and connectomics could provide additional information about seizure propagation within the epilepsy network and might enable new treatment options in the future like deep brain stimulation.
Data Science and Business Intelligence Transforming Insights Into Action
2025-01-03

In today's data-driven world, organizations across industries are leveraging data science and Business Intelligence (BI) to extract actionable insights from vast amounts of data. This article explores the role of data science and BI in driving informed decision-making, optimizing business processes, and gaining a competitive edge in the digital era. From data collection and preprocessing to advanced analytics and visualization techniques, we delve into the key components of data science and BI and their transformative impact on businesses. Additionally, we examine real-world applications, challenges, and future trends shaping the convergence of data science and BI, paving the way for data-driven innovation and organizational success.
Advanced Technologies for Sustainability and Environment
2025-01-03

The pressing challenges of climate change, resource depletion, and environmental degradation necessitate innovative solutions that harness advanced technologies to promote sustainability and mitigate adverse environmental impacts. This article explores the diverse array of advanced technologies that hold promise for addressing key sustainability and environmental challenges. From renewable energy systems and smart grid technologies to sustainable agriculture practices and green manufacturing processes, these cutting-edge technologies offer opportunities to transition towards a more sustainable and resilient future. By leveraging the power of artificial intelligence, Internet of Things (IoT), and advanced materials, these technologies enable more efficient resource utilization, reduce greenhouse gas emissions, and enhance environmental conservation efforts. This article provides an overview of key advanced technologies for sustainability and environment, highlighting their potential benefits, challenges, and implications for addressing pressing global environmental issues.
Integrating IoT and AI Solutions for Addressing Urbanism Challenges
2025-01-03

Urban areas face numerous challenges related to population growth, resource management, environmental sustainability, and infrastructure efficiency. The integration of Internet of Things (IoT) and Artificial Intelligence (AI) technologies offers innovative solutions to tackle these urbanism problems. This article explores the application of IoT and AI in addressing various urban challenges, including traffic congestion, energy consumption, waste management, public safety, and urban planning. By leveraging real-time data collection, predictive analytics, and autonomous systems, IoT and AI solutions empower cities to optimize resource utilization, enhance service delivery, and improve overall quality of life for residents.
Processes and measurements: a framework for understanding neural oscillations in field potentials
2025-01-05

Various neuroscientific theories maintain that brain oscillations are important for neuronal computation, but opposing views claim that these macroscale dynamics are 'exhaust fumes' of more relevant processes. Here, we approach the question of whether oscillations are functional or epiphenomenal by distinguishing between measurements and processes, and by reviewing whether causal or inferentially useful links exist between field potentials, electric fields, and neurobiological events. We introduce a vocabulary for the role of brain signals and their underlying processes, demarcating oscillations as a distinct entity where both processes and measurements can exhibit periodicity. Leveraging this distinction, we suggest that electric fields, oscillating or not, are causally and computationally relevant, and that field potential signals can carry information even without causality.
Oral Maintenance Therapy in Early Breast Cancer—How Many Patients Are Potential Candidates?
2025-01-05

Background/Objectives: This single-center analysis evaluated the number of potential candidates for endocrine-based oral maintenance therapy in a real-world setting, focusing on three therapeutic agents, namely, olaparib, abemaciclib, and ribociclib, for patients with hormone receptor-positive HER2-negative early breast cancer. Methods: All breast cancer cases from the past 10 years (n = 3230) that underwent treatment at the certified Breast Cancer Center of the Department of Gynecology and Obstetrics, University Hospital Schleswig-Holstein, Lübeck Campus, were analyzed. Results: Of a total of 2038 patients with HR+ HER2− eBC, 685 patients (33.6%) qualified for one or more of the three agents—olaparib, abemaciclib, and ribociclib. Of these 685 patients, 523 patients (76.4%) had node-positive and 162 (23.6%) node-negative disease. Moreover, 368 patients (18.1% of a total of 2038 patients with HR+ HER2− eBC) were eligible exclusively for ribociclib, including all node-negative patients. A total of 141 patients (6.9%) met the criteria for all three agents. In contrast, 1353 patients (66.4%) had no indication for combined endocrine therapy. Conclusions: To our knowledge, this is the largest analysis addressing all three therapeutic strategies for combined endocrine therapy. The broad indication criteria of the NATALEE study may increase clinic workloads due to more frequent physician/patient interactions. It also remains unclear how therapy recommendations will influence actual treatment, as increased visits and potential side effects could affect patient compliance and adherence.
Bridging the fields of cognition and birdsong with corvids
2025-01-05

Corvids, readily adaptable across social and ecological contexts, successfully inhabit almost the entire world. They are seen as highly intelligent birds, and current research examines their cognitive abilities. Despite being songbirds with a complete 'song system', corvids have historically received less attention in studies of song production, learning, and perception compared to non-corvid songbirds. However, recent neurobiological studies have demonstrated that songbird vocal production and its neuronal representations are regularly influenced by environmental and cognitive factors. This opinion article discusses the literature on 'corvid song' before introducing other flexible vocal behaviors of corvids in both the wild and controlled laboratory studies. We suggest corvids with their flexible vocal control as promising model species to study the links between brain networks for cognition and vocalization. Studying corvid vocal flexibility and associated cognitive processes in both ecological and lab settings offers complementary insights, crucial for bridging the fields of cognition and birdsong.
High-performance thin-layer chromatography–umu combined with nontarget analysis—a sensitive genotoxicity screening tool applicable for potable water analysis
2025-01-06

Abstract Monitoring of genotoxic chemicals released into the water cycle or formed through transformation processes is critical to prevent harm to human health. The development of the high-performance thin-layer chromatography (HPTLC)–umu bioassay combines sample separation and detection of genotoxic substances in the low ng/L concentration range. In this study, raw, process, and drinking water samples from 11 different waterworks in Germany were analyzed using the HPTLC-umu. A genotoxic response was detected in three out of 42 samples (one raw water sample and two drinking water samples). Genotoxicity testing using the micronucleus and p53-CALUX (chemical activated luciferase gene expression) assays revealed genotoxic effects for the raw water sample and one of the drinking water samples. Fortunately, only minor genotoxic effects could be detected in the two drinking water samples, with estimated 4-nitroquinoline-N-oxide equivalency concentrations of 0.12 ng/L and 0.17 ng/L, respectively. After extraction of the genotoxic zones from HPTLC plates, identification attempts were conducted with nontarget analysis (NTA). A prioritization approach based on chlorine and bromine isotope pattern revealed several halogenated features for both drinking water samples. These tentatively identified substances were previously reported in the literature as possible carcinogens. Although the detected features could not be conclusively identified, the presence of halogenated features in the genotoxic effective zone of the HPTLC-umu assay strongly suggests that the chlorine disinfection process in both waterworks was responsible for the formation of the genotoxic substances in the drinking water samples. These findings emphasize that the HPTLC-umu in combination with additional genotoxicity assays and NTA can be used to evaluate even relatively clean samples, such as drinking water.
Brolucizumab and Platelet Activation and Reactivity
2025-01-06

Brolucizumab does not appear to directly affect platelet activation or reactivity to thrombin receptor agonists. No platelet interaction was observed after increasing brolucizumab concentrations or anti-brolucizumab antibodies in resting and activated platelets. However, brolucizumab might be taken up in platelets.
Geometric distances between closed universes
2025-01-06

The large-scale structure of the Universe is well approximated by the Friedmann equations, parametrized by several energy densities which can be observationally inferred. A natural question to ask is: How different would the Universe be if these densities took on other values? While there are many ways this can be approached depending on interpretation and mathematical rigor, we attempt an answer by building a “history space” of different cosmologies. A metric is introduced after overcoming technical hurdles related to Lorentzian signature and infinite volume, at least for topologically closed cases. Geodesics connecting two points on the superspace are computed to express how distant—in a purely geometric sense—two universes are. Age can be treated as a free parameter in such an approach, leading to a more general mathematical construct relative to geometrodynamical configuration space. Connections to bubble inflation and phase transitions are explored.
Geochemical Drivers of Enhanced Rock Weathering in Soils
2025-01-06

Experimental research indicates that the efficiency of enhanced rock weathering (ERW) as a form of carbon dioxide removal (CDR), is subject to large variations in effectivity, and that the current state of knowledge is not sufficient to develop robust predictive capabilities. It appears that the heterogeneous mineralogy and reactivity of basalt, as well as the regional and local pedoclimatic parameters, greatly influence its weathering characteristics, and in turn, its ability to sequester CO 2 . Therefore, ERW efficiency should not be taken for granted but should, rather, be pursued according to a careful rock and soil geochemical selection. If ERW is to eventually become a significant CDR technology, then future research programs must bring together the fields of geochemistry, engineering, life cycle analysis, biology, soil physics, hydrology, and agronomy, as well as social sciences such as economy, law, and sociology. Furthermore, it is vitally important that research constraints relating to CDR methodologies be lifted in the immediate future. Indeed, CDR funds need to be allocated based on solid science to insure their overall efficiency as well as the credibility of the scientific community in the long run.
The burden of X-linked retinitis pigmentosa (XLRP) on patient experience and patient-reported outcomes (PROs): findings from the EXPLORE XLRP-2 study
2025-01-07

Abstract Background/aims X-linked retinitis pigmentosa (XLRP) is considered one of the most severe forms of retinitis pigmentosa (RP), accounting for 5–15% of all RP cases and primarily affecting males. However, the real-world humanistic impacts of this disease on patients are poorly investigated, especially with respect to burdens faced by patients with varying disease severities. Methods EXPLORE XLRP-2 was an exploratory, multicentre, non-interventional study. A retrospective chart review was conducted to collect clinical/demographic data, including XLRP clinical stage (mild, moderate or severe). Cross-sectional surveys were used to gather experiences directly from patients by validated and modified patient-reported outcomes. Results 176 patients with XLRP caused by retinitis pigmentosa GTPase regulator ( RPGR ) gene mutation were enrolled, of whom 169 were included in analyses. 81% of patients were male, mean (SD) age was 39.3 (17.61) years, and 20 adolescents were included. Mean age (SD) at genetic confirmation was 33.4 years (17.98), and the mean duration (SD) from initial symptoms to genetic diagnosis was 16.4 (15.66) years. Compared with patients with mild disease, patients with severe XLRP are more likely to experience difficulties with functioning in low luminance, depression, unemployment, productivity issues, mobility and daily activities. Conclusion This is the first real-world study to collect data directly from patients on the burden of XLRP and to correlate that burden with disease stage. As a result, several areas of significant burden, especially for patients with severe disease, have been identified that should provide focus for future public policies and therapeutic prospects.
Fish early-life stage toxicity and environmental relevance: what does high-dose toxicity testing tell us?
2025-01-07

Abstract The early-life stage (ELS) toxicity syndrome for fish is well described and has been reported in hundreds of toxicity studies. It is generally characterized by a reduced heart rate, yolk sac and pericardial edemas, and various morphological abnormalities, the most common being spinal curvature. For many of those studies, it appears that the ELS toxicity syndrome is the result of nonspecific (baseline) toxicity that occurs at aqueous and whole-body concentrations that are just below lethal concentrations. Baseline toxicity is essentially a nonspecific response that results from chemicals accumulating in and disturbing the function of biological membranes that leads to lethality and sublethal effects at relatively high doses. The commonality of this acute ELS toxicity syndrome among highly diverse organic and inorganic chemicals is remarkable. It is important to identify baseline toxicity because it is considered minimal toxicity that acts in all tissues and cells, and it has the potential to impair all cellular functions. This means if an effect is observed around baseline-toxic concentrations, it is likely that other cellular functions are also affected (i.e., the effect is not specific). The fish ELS toxicity syndrome can also be the result of specific effects involving receptor interactions; therefore, we emphasize the importance of distinguishing between specific and nonspecific toxicity responses to provide the most relevant data for environmental risk assessment.
Machine learning applications in archaeological practices: a review
2025-01-07

Artificial intelligence and machine learning applications in archaeology have increased significantly in recent years, and these now span all subfields, geographical regions, and time periods. The prevalence and success of these applications have remained largely unexamined, as recent reviews on the use of machine learning in archaeology have only focused only on specific subfields of archaeology. Our review examined an exhaustive corpus of 135 articles published between 1997 and 2022. We observed a significant increase in the number of publications from 2019 onwards. Automatic structure detection and artefact classification were the most represented tasks in the articles reviewed, followed by taphonomy, and archaeological predictive modelling. From the review, clustering and unsupervised methods were underrepresented compared to supervised models. Artificial neural networks and ensemble learning account for two thirds of the total number of models used. However, if machine learning models are gaining in popularity they remain subject to misunderstanding. We observed, in some cases, poorly defined requirements and caveats of the machine learning methods used. Furthermore, the goals and the needs of machine learning applications for archaeological purposes are in some cases unclear or poorly expressed. To address this, we proposed a workflow guide for archaeologists to develop coherent and consistent methodologies adapted to their research questions, project scale and data. As in many other areas, machine learning is rapidly becoming an important tool in archaeological research and practice, useful for the analyses of large and multivariate data, although not without limitations. This review highlights the importance of well-defined and well-reported structured methodologies and collaborative practices to maximise the potential of applications of machine learning methods in archaeology.
The non-nutritive sweetener rebaudioside a enhances phage infectivity
2025-01-08

Abstract Non-nutritive sweeteners (NNS) are widely employed in foodstuffs. However, it has become increasingly evident that their consumption is associated with bacterial dysbiosis, which, in turn, is linked to several health conditions, including a higher risk of type 2 diabetes and cancer. Among the NNS, stevia, whose main component is rebaudioside A (rebA), is gaining popularity in the organic food market segment. While the effect of NNS on bacteria has been established, the impact of these sweeteners on bacterial viruses (phages) has been neglected, even though phages are crucial elements in maintaining microbial eubiosis. The present study sought to provide a proof-of-concept of the impact of NNS on phage infectivity by assessing the binding of rebA to phage proteins involved in the infection process of enteropathogenic bacteria, namely the fiber protein gp17 of Yersinia enterocolitica phage φYeO3-12 and the tubular baseplate protein gp31 of Klebsiella pneumoniae phage 32. We employed docking analysis and a panel of in vitro confirmatory tests (microscale thermophoresis, RedStarch TM depolymerization, adsorption, and lysis rates). Docking analysis indicated that NNS can bind to both fiber and baseplate proteins. Confirmatory assays demonstrated that rebA can bind gp31 and that such binding increased the protein’s enzymatic activity. Moreover, the binding of rebA to gp17 resulted in a decrease in the adsorption rate of the recombinant protein to its host but increased the Yersinia bacteriolysis caused by the whole phage compared to unexposed controls. These results support the hypothesis that NNS can impair phage infectivity, albeit the resulting effect on the microbiome remains to be elucidated.