New College of Florida

In this paper, a novel ionization energy, IE, set theory-based organizational structure is suggested: (i) iso-protonic sets, IZE; (ii) iso-electronic sets, IEs; and (iii) iso-ionic sets, IEi+. A computational algorithm is proposed which was demonstrated on twenty-five iso-electronic IEs-sets plotted vs. the nuclear charge, Z. The algorithm allows for: (i) the interpolative assessment of 162 new (not measured) IE values, with their uncertainties estimated by the Lagrange method, for ions from 30Zn to 41Nb; and (ii) effective atomic nuclear charge assessment. It is shown that the IE effective atomic nuclear charge assessment is strongly correlated with the Slater’s effective charge and Pauling electronegativity scale.

The design of experiments to investigate the combined effects of multiple stressors requires exposing target organisms to multiple combinations of stressor doses. Concurrent manipulation of stressors is often infeasible with wildlife, but long-lasting health effects allow individual health to be used as an integrator of prior stressor exposure. The population of bottlenose dolphins in Barataria Bay, Louisiana, experienced long-lasting health effects after exposure to oil from the Deepwater Horizon spill. We investigated whether compromised health status affects dolphins' ability to respond to other stressors, specifically vessel traffic, potentially leadingto increased collision risk. We used this case study to develop a hypothesis-driven experimental approach to assess the combined effects of multiple stressors in a large, long-lived vertebrate species. We conducted controlled vessel approaches to test whether the health status of targeted dolphins affected their behavioral responses. Our results highlighted some effects of health, suggesting that oil spills may exacerbate the effects of other stressors in coastal populations. For example, lung disease was associated with a delayed dive response, which could affect the ability to vertically avoid vessels and lead to increased collision risk. However, health effects on response probability were overall smaller than anticipated, and other contextual variables (e.g., sex, age, calf presence, prior experience, and exposure context) contributed to response variability. Our work demonstrated the value of formalizing stressor interactions as multidimensional dose-response functions and showed the feasibility of an experimental, multiple-stressor study in a wild system in which individual health status can be used as an integrator of prior stressor exposure. This approach has broad implications for other species that are difficult to handle experimentally. The quantification and management of the cumulative risk from multiple stressors on wildlife will require a combination of empirical and mechanistic approaches to inform long-term, population consequences.

This research examines the representations and influence of Arabic literature in the poetry of Muhammad Iqbal, renowned as the poet of the East. Despite never traveling to Arab lands, Iqbal's profound mastery of the Arabic language and literature profoundly shaped his poetic style, themes, and symbolism. The study employs a literary-analytical approach to identify how Iqbal drew from classical Arabic poetry, Quranic texts, and Arab cultural history. Through close reading of poems such as "The Mosque of Córdoba" and "Khidr-e-Rah," the analysis reveals his extensive use of Arabic vocabulary, adaptation of motifs like ruins and longing (al-atlal), and symbolic references to Arab figures and history. The findings demonstrate that Iqbal creatively reshaped these elements to formulate a modern poetic discourse centered on Islamic revival and civilizational renewal. His work thus serves as a bridge between classical Arabic literary traditions and contemporary Islamic thought. This study highlights the centrality of Arabic heritage in Iqbal's vision and contributes to understanding the intertextual connections within the Islamic literary sphere.

Introduction Coral reefs are essential ecosystems facing severe global decline due to various environmental stressors. Understanding coral resilience and adaptability is critical for their conservation. Methods We examined the microbial communities associated with the scleractinian coral Favia fragum in both mangrove and adjacent reef habitats in the Panamanian Caribbean. Results Our results reveal that F. fragum colonies in mangrove habitats at different sites share similar microbial communities, distinct from those in adjacent reef habitats. Notably, certain bacterial lineages, including Cyanobacteria and Hyphomicrobiales, are enriched in mangrove-associated corals, suggesting potential roles in carbon and nitrogen cycling. Conversely, the family Vibrionaceae, which includes known coral pathogens, is more abundant in reef habitats. Discussion These findings emphasize the significance of microbial communities in coral resilience and highlight the complex interplay between corals and microbial symbionts across different habitats. Protecting mangroves, which serve as nurseries for coral biodiversity, is crucial for overall reef health in the face of global coral decline.

ABSTRACT Cognition is an animal's real‐time adaptation system for responding to change. Rapid environmental change, often anthropogenic, is expanding the range and severity of challenges confronting wild animals. Effective conservation requires a multifaceted approach that includes animals' capacities. Large‐brained, long‐lived animals such as marine mammals often have extensive capability to adaptively modify their behavior due to their cognition, which comprises the mechanisms of information acquisition, processing, and flexible action. Consequently, current behavior need not be a final predictor of future behavior for these animals. This flexibility provides an underutilized and under examined point of leverage for humans interested in improving life outcomes for wild animals. In this team‐written, interdisciplinary paper, we argue that application of cognitive approaches may facilitate many conservation efforts directed toward marine mammals. Starting with a workshop on this topic at the 24th Biennial Conference on the Biology of Marine Mammals, scientists representing a wide range of disciplinary expertise addressed eight different conservation concerns for six marine mammal species and provided potential cognitive explanations of and interventions aimed at related behavior. Our treatment highlights the value of integrated laboratory and field research, and the importance of tight lines of communication between scientists and conservation managers.

IntroductionCervical cancer (CC) is the third most prevalent malignancy among women worldwide. Candidate gene studies have identified multiple single nucleotide polymorphisms (SNPs) that are associated with an increased risk of CC. The objective of this study was to examine the relationship between 8 specific single-nucleotide polymorphisms (SNPs) and the risk of cervical cancer in the Georgian population.MethodsThe present study employed a prospective case-control design, with 40 patients diagnosed with CC and 45 healthy women. A total of 8 single-nucleotide polymorphisms (SNPs) were genotyped using the TaqMan genotyping assay: rs7579014, rs11263763, rs7726159, rs6897196, rs2853672, rs635634, rs231775, and rs2304204.ResultsOur analysis demonstrated that rs7579014 (BCL11A, G/A), rs7726159 (TERT, C/A), and rs6356634 (ABO, T/A) were associated with an increased risk of cervical cancer in Georgian patients. However, following the implementation of the Benjamini-Hochberg correction, only rs6356634 (ABO T/A) and rs7579014 (BCL11A G/A) remained statistically significant. A lack of statistically significant correlation was identified between the genetic variants rs11263763, rs6897196, rs2853672, rs2304204, and rs231775 and susceptibility to cervical cancer.ConclusionsThis study represents the first attempt to investigate SNP associations in women with cervical cancer in Georgia. The findings indicate that SNP-based analysis may hold promise for the early identification of susceptibility to cervical cancer, and potentially to other cancers. Nevertheless, further research involving larger sample sizes is required to validate and strengthen these preliminary observations.

The surface finishing and robotic painting processes in automotive manufacturing are critical determinants of vehicle exterior quality and production efficiency. Despite considerable progress in automation, real-time correction of paint irregularities remains a major challenge due to the absence of continuous, adaptive feedback mechanisms. Conventional vision-based inspection systems primarily detect defects post-application, leading to increased rework, material wastage, and production downtime. To overcome these constraints, this paper proposes the Real-Time Adaptive Aeroacoustic Robotic Painting and Finishing System (RAARPS)-a novel intelligent framework that integrates aeroacoustic sensing and deep learning-driven adaptive control for instant defect detection and correction. The RAARPS system utilizes an array of miniature directional microphones and airflow sensors strategically positioned on robotic arms and within the paint booth to capture high-frequency acoustic and aerodynamic signals generated during spray atomization and surface wetting. These signals are processed by a hybrid convolutional and recurrent neural network model, which interprets subtle variations in sound and airflow patterns to identify turbulence, overspray, or non-uniform atomization within milliseconds. The inference model then autonomously adjusts spray parameters, such as paint flow rate, electrostatic charge, and arm motion trajectory, ensuring consistent coating thickness and finish quality. Experimental validation demonstrates that RAARPS achieves a 6% improvement in defect detection accuracy and enhances first-pass yield compared to existing vision-based systems. Furthermore, the system reduces paint waste by approximately 12% and lowers volatile organic compound (VOC) emissions by about 8%, contributing significantly to sustainable and eco-efficient manufacturing. The results confirm that RAARPS provides a transformative advancement in intelligent robotic painting, offering real-time, data-driven adaptability that enhances surface precision, operational reliability, and environmental compliance.

PremisePlastid-based data sets continue to play a major role in our understanding of early flowering-plant relationships, although organellar genomes of major lineages outside the monocots and eudicots remain under-sampled. A tendency of mitochondrial RNA-edit sites to mislead phylogenetic analysis in mixed transcriptomic/genomic data sets needs attention in angiosperm-wide studies, which only rarely consider mitochondrial genomes.MethodsWe compared mitochondrial- vs. plastid-based phylogenomic inferences, examined the effect of removing putative RNA-edit sites from mitochondrial data, and performed combined organellar analysis (plastid plus filtered mitochondrial genomes). We expanded taxon sampling for multiple angiosperm lineages for phylogenomic analysis using both organellar genomes, representing several poorly sampled lineages (in particular Degeneriaceae, Trimeniaceae) with smaller (few-gene) data sets.ResultsPlastid-based inferences recover well-supported relationships that align with and build upon previous studies, and recover well-supported internal relationships for two ANA-grade families (Hydatellaceae, Trimeniaceae) sampled for nearly all species. By contrast, unfiltered mitochondrial inferences of angiosperm phylogeny are generally poorly supported, and recover anomalous relationships compared to plastid-based inferences. However, removing putative mitochondrial RNA-edit sites dramatically reduces inter-organellar conflict and improves overall branch support.ConclusionsWe accounted for phylogenomic discordance between the two organellar genomes regarding overall angiosperm-wide relationships and filled in taxonomic gaps (poorly sampled lineages). Removing RNA edit sites substantially improves congruence in interorganellar inferences by effectively correcting a systematic bias in mitochondrial data. Uncertain relationships persist among five major mesangiosperm lineages in plastid-based inferences, but a clade comprising Chloranthales, Ceratophyllales and eudicots is well supported by filtered mitochondrial data.