Blackstone (United States)

Stentor, the genus of large trumpet-shaped ciliates, is well-known for its complex morphology and striking behaviors. Members of this genus are distributed throughout the world in a wide and diverse pool of freshwater ecosystems. Recently, the molecular phylogeny of Stentor has been explored through comparison of 18 S small subunit (SSU) ribosomal DNA (rDNA) sequences, clarifying several previously mischaracterized species and species complexes. However, despite their wide distribution, to-date, only about a dozen species of Stentor have been described and verified by phylogenetic means. Here, we introduce the discovery of a new species within genus Stentor: Stentor stipatus spec. nov., so named for their distinctive cytosolic dark pigmented granules which surround the macronucleus and are also present cortically alongside cortically-distributed green microalgae. We present morphological, phylogenetic, ecological, and behavioral characterizations of these cells. Phylogenetic analysis of S. stipatus spec. nov. by comparison of SSU rDNA sequence suggests it is a distinct species from its closest relative, S. amethystinus. We demonstrate that S. stipatus spec. nov. is capable of habituation in response to repeated mechanical stimulation. Further, S. stipatus spec. nov. exhibits strongly directed positive phototaxis, like its relative S. pyriformis, but with a distinct action spectrum from both S. coeruleus and S. pyriformis. Finally, S. stipatus phototaxis response strength varies in a consistent pattern throughout the day, providing evidence of potential circadian regulation. This work expands the current understanding of the ecological distribution of and behavioral features present within genus Stentor.

Limited annotated data often constrain accurate yield prediction in underrepresented crops. To address this challenge, we developed a cross-crop deep transfer learning (TL) framework that leverages potato (Solanum tuberosum L.) as the source domain to predict sweet potato (Ipomoea batatas L.) yield using multi-temporal uncrewed aerial vehicle (UAV)-based multispectral imagery. A hybrid convolutional–recurrent neural network (CNN–RNN–Attention) architecture was implemented with a robust parameter-based transfer strategy to ensure temporal alignment and feature-space consistency across crops. Cross-crop feature migration analysis showed that predictors capturing canopy vigor, structure, and soil–vegetation contrast exhibited the highest distributional similarity between potato and sweet potato. In comparison, pigment-sensitive and agronomic predictors were less transferable. These robustness patterns were reflected in model performance, as all architectures showed substantial improvement when moving from the minimal 3 predictor subset to the 5–7 predictor subsets, where the most transferable indices were introduced. The hybrid CNN–RNN–Attention model achieved peak accuracy (R2≈0.64 and RMSE ≈ 18%) using time-series data up to the tuberization stage with only 7 predictors. In contrast, convolutional neural network (CNN), bidirectional gated recurrent unit (BiGRU), and bidirectional long short-term memory (BiLSTM) baseline models required 11–13 predictors to achieve comparable performance and often showed reduced or unstable accuracy at higher dimensionality due to redundancy and domain-shift amplification. Two-way ANOVA further revealed that cover crop type significantly influenced yield, whereas nitrogen rate and the interaction term were not significant. Overall, this study demonstrates that combining robustness-aware feature design with hybrid deep TL model enables accurate, data-efficient, and physiologically interpretable yield prediction in sweet potato, offering a scalable pathway for applying TL in other underrepresented root and tuber crops.

This paper presents an intelligent AI test modeling framework for computer vision systems, focused on image-based systems. A three-dimensional (3D) model using decision tables enables model-based function testing, automated test data generation, and comprehensive coverage analysis. A case study using the Seek by iNaturalist application demonstrates the framework’s applicability to real-world CV tasks. It effectively identifies species and non-species under varying image conditions such as distance, blur, brightness, and grayscale. This study contributes a structured methodology that advances our academic understanding of model-based CV testing while offering practical tools for improving the robustness and reliability of AI-driven vision applications.

Black Space Week (BSW) is a dedicated celebration of the contributions by Black professionals and students in space-related fields, including astronomy, aeronautics, climate studies, and beyond. This annual event highlights the diverse work being done in the community, emphasizing the importance of space exploration and scientific advancement. Created and organized by Black In Astro, the week features a variety of engaging activities, panel discussions, and showcasing student research and art competitions. Through these gatherings, scientists, astronauts, and educators alike have been a platform for those to share their mutual experiences, expertise, and motivation. BSW has fostered connections across multiple demographics that extends beyond academia or research. This year, our focus is on the impact of humanities and how it has shaped the current state of space sciences and exploration. Specifically, we’ll explore how humanities plays a huge role in the space sciences and overlaps with journalism, planetarium, environmental justice, and art work. Scientists are extremely multifaceted and how we envision the universe through scientific research and various cultural aspects. We aim to illustrate how diversity drives innovation, strengthens inclusivity, and captures participation from underrepresented groups in the space sciences and planetary mission development.

This review explores the concept of infant mental health and its relevance to the African context. Infant mental health refers to the capacity of infants (0-3 years) to regulate emotions, form secure relationships and explore their environment. It is crucial for neurological development, mental maturity, and cognitive capacity. The field of infant mental health started with developmental psychology but has evolved in its multidisciplinary approach to the mental healthcare of newborns. Classificatory systems of mental disorders have expanded to include infant mental disorders. Awareness of this discipline is rising due to advocacy and research. Research started in Europe, but also began quite early in Africa, with the attachment studies of Mary Ainsworth. Africa has unique cultural factors that promote infant mental health, such as communal living and practices like carrying infants. However, some cultural beliefs/practices may be detrimental. Research is limited but institutions such as the Centre for Child and Adolescent Mental Health are bridging the research gap. Infant mental health is essential for healthy development and Africa needs culturally sensitive approaches to promote it. Strengthening policies, existing structures, and research output will help drive progress in this field.

Enhancers play critical roles in gene expression, but a full understanding of their complex functions has yet to be defined. The cellular response to excess zinc levels in C. elegans requires the HIZR-1 transcription factor, which binds the high-zinc activation (HZA) enhancer in the promoters of multiple target genes. Cadmium hijacks the excess zinc response by binding and activating HIZR-1. By analyzing the genome-wide transcriptional response to excess zinc and cadmium, we identified two positions in the genome where head-to-head oriented genes are both induced by metals. In both examples, a single predicted HZA enhancer is positioned between the two translational start sites. We hypothesized that a single enhancer can control both head-to-head genes, an arrangement that has not been extensively characterized. To test this hypothesis, we used CRISPR genome editing to precisely delete the HZAmT enhancer positioned between mtl-2 and T08G5.1; in this mutant, both head-to-head genes display severely reduced zinc-activated transcription, whereas zinc-activated transcription of more distant genes was not strongly affected. Deleting the HZAcF enhancer positioned between cdr-1 and F35E8.10 caused both head-to-head genes to display reduced cadmium-activated transcription, whereas cadmium-activated transcription of more distant genes was not strongly affected. These studies rigorously document that a single HZA enhancer can control two head-to-head genes, advancing our understanding of the diverse functions of enhancers.