Hasil untuk "Animal culture"

B. Wood

R. Kohler

Mengling Zhang, Mengling Zhang, Yunlei Li et al.

Although studies have investigated Solanum nigrum L. (SNL) in mice, its effects on broilers remain unclear. This study examined how dietary SNL influences growth performance, antioxidant capacity, ileal transcriptome, and gut microbiota in broilers. A total of 200 one-day-old healthy Wuhua yellow-feathered chickens were randomly divided into four groups of five replicates (10 birds each). The groups received: a basal diet (CON), a basal diet with 500 mg/kg amoxicillin (AMO), a basal diet with 1000 mg/kg SNL grass meal (0.1% SNL), and a basal diet with 2000 mg/kg SNL grass meal (0.2% SNL). The experiment lasted 35 days. SNL supplementation modestly improved feed efficiency and jejunal villus height (p = 0.019). It also altered cecal microbiota by increasing Bacteroidetes, Bacteroides, and Faecalibacterium, while decreasing Firmicutes and Oscillibacter. Ileal transcriptomics identified multiple differentially expressed genes (DEGs) across comparisons, which were enriched in intestinal immune network pathways for IgA production. Correlation analysis linked cecal microbiota changes to ileal gene expression. In conclusion, SNL exhibits the potential as an alternative to antibiotics in chickens, and this study provides empirical support for its broader adoption in poultry industry.

Tian Hua, Rui Pan, Yong Jiang et al.

As a pigment-related trait, beak color is an important feature for duck breeds. Nowadays, several studies have been conducted on the genetic mechanisms and candidate markers of duck beak color. However, related loci which were mostly single base mutations could hardly explain the phenotype. To select greater structural mutations associated with beak color, all 308 birds of the F2 population of the Runzhou white crested ducks were selected to perform the genome-wide association studies to select key genes and differential InDels related to the formation of beak color in ducks. To verify the accuracy of the GWAS and to further select the candidate variants of beak colors, Line H (H1, H2, H3 and HF) was selected as black-beaked ducks along with yellow-beaked ducks which consist of CV ducks and Line E for genomic selection signatures by integrated analysis of FST and θπ. Genotyping was performed to verify the functions of the candidate sites. As the result, 2 InDels in the intronic region were selected as candidate variants by GWAS. Furthermore, eight genes were selected according to a standard FDR of <0.05 and MITF was finally selected based on a comparison of the FST values by genomic selection signature. After the selection of the loci, 1 bp insertion (InDel-4, at the position of 17829988 on chromosome 10 of ASM874695v1) in intron regions of MITF were selected as candidate sites. As the result of the genotyping, all yellow-beaked ducks were homozygous mutated individuals, while all individuals in Line H (black-beaked ducks) were found to have the RR (ref / ref) genotype. In addition, the relative expression of MITF from beak tissue of the H2 ducks was significantly higher than that of CV ducks(p < 0.001). Thus, MITF plays a critical role in melanogenesis and melanin deposition in duck beaks, which can affect beak color, and InDel-4 were significantly different in the yellow- and black-beaked individuals and could be used as markers to identify the beak colors of ducks.

Hancai Jiang, Xiaoxian Xu, Xinhui Song et al.

Currently, most studies on lactation-related traits and gene expression rely on invasive techniques to obtain mammary tissue. These methods are not only difficult to perform but also limit the availability of samples. Therefore, this study aimed to utilize whole transcriptome sequencing to investigate the gene expression profiles of Golden hamsters (Gh, n = 5) and Kunming mice (Km, n = 5). It compared the transcriptome expression between milk fat globules (MFG) and the mammary gland (MG), identified candidate genes and pathways associated with lactation traits, and assessed the potential of MFG as an effective alternative to MG. The data showed that a total of 21,360 genes were identified in the Gh group, with 66.5% of the mRNAs showing no differential expression between MG and MFG. In the Km group, a total of 44,248 genes were identified, with non-differentially expressed genes (NDEGs) accounting for 58.8%. Additionally, the majority of ncRNA data consisted of NDEGs. In both groups, approximately 80% of miRNA data were NDEGs. Notably, the proportion of NDEGs in circRNA data approached 100%. Enrichment analysis revealed that NDEGs from both groups were significantly enriched in several pathways, including the MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, and prolactin signaling pathway, all of which are closely associated with lactation traits and the lactation process. Furthermore, we identified various ncRNAs that regulate the expression of target genes either directly or indirectly, thereby influencing the lactation process. This study validates MFG as a reliable substitute for MG, with potential applications in improving dairy science. By identifying key genes and pathways, it provides new insights for optimizing genetic selection and breeding strategies. It also supports the improvement of dairy animal management practices.

Alexandre Delporte, Susanne Ditlevsen, Adeline Samson

Advances in tracking technologies for animal movement require new statistical tools to better exploit the increasing amount of data. Animal positions are usually calculated using the GPS or Argos satellite system and include potentially complex non-Gaussian and heavy-tailed measurement error patterns. Errors are usually handled through a Kalman filter algorithm, which can be sensitive to non-Gaussian error distributions. In this paper, we introduce a realistic latent movement model through an underdamped Langevin stochastic differential equation (SDE) that includes an additional drift term to ensure that the animal remains in a known spatial domain of interest. This can be applied to aquatic animals moving in water or terrestrial animals moving in a restricted zone delimited by fences or natural barriers. We demonstrate that the incorporation of these spatial constraints into the latent movement model improves the accuracy of filtering for noisy observations of the positions. We implement an Extended Kalman Filter as well as a particle filter adapted to non-Gaussian error distributions. Our filters are based on solving the SDE through splitting schemes to approximate the latent dynamic.

Ji-Eun Han, Yoonseok Heo

Incorporating personas into conversational AI models is crucial for achieving authentic and engaging interactions. However, the cultural diversity and adaptability of existing persona datasets is often overlooked, reducing their efficacy in building culturally aware AI systems. To address this issue, we propose a two-step pipeline for generating culture-specific personas and introduce KoPersona, a dataset comprising 200,000 personas designed to capture Korean cultural values, behaviors, and social nuances. A comprehensive evaluation through various metrics validates the quality of KoPersona and its relevance to Korean culture. This work not only contributes to persona-based research, but also establishes a scalable approach for creating culturally relevant personas adaptable to various languages and cultural contexts.

Xiutian Zhao, Rochelle Choenni, Rohit Saxena et al.

Despite their impressive performance, vision-language models (VLMs) still struggle on culturally situated inputs. To understand how VLMs process culturally grounded information, we study the presence of culture-sensitive neurons, i.e. neurons whose activations show preferential sensitivity to inputs associated with particular cultural contexts. We examine whether such neurons are important for culturally diverse visual question answering and where they are located. Using the CVQA benchmark, we identify neurons of culture selectivity and perform causal tests by deactivating the neurons flagged by different identification methods. Experiments on three VLMs across 25 cultural groups demonstrate the existence of neurons whose ablation disproportionately harms performance on questions about the corresponding cultures, while having minimal effects on others. Moreover, we propose a new margin-based selector - Contrastive Activation Selection (CAS), and show that it outperforms existing probability- and entropy-based methods in identifying culture-sensitive neurons. Finally, our layer-wise analyses reveals that such neurons tend to cluster in certain decoder layers. Overall, our findings shed new light on the internal organization of multimodal representations.

Emily Quiroga

The importance of maritime heritage in providing benefits such as a sense of place and identity has been widely discussed. However, there remains a lack of comprehensive quantitative analysis, particularly regarding monetary valuation and its impact on people's preferences. In this study, I present the results of a choice experiment that assesses the value of the maritime cultural heritage associated with shrimp fishing through seafood consumption preferences in Germany. Additionally, I investigate people's attitudes toward cultural heritage and examine how these attitudes affect their stated preferences. I find that these attitudes are significantly stronger in towns where local fishermen led a prominent awareness campaign on fishing culture during the study period. Moreover, I observe a positive willingness to pay for a cultural heritage attribute in shrimp dishes, which varies depending on individuals' attitudes toward cultural heritage.

Quoc-Duy Tran, Anh-Tuan Vo, Dinh-Khoi Vo et al.

Humans possess a unique ability to perceive meaningful patterns in ambiguous stimuli, a cognitive phenomenon known as pareidolia. This paper introduces Shape2Animal framework to mimics this imaginative capacity by reinterpreting natural object silhouettes, such as clouds, stones, or flames, as plausible animal forms. Our automated framework first performs open-vocabulary segmentation to extract object silhouette and interprets semantically appropriate animal concepts using vision-language models. It then synthesizes an animal image that conforms to the input shape, leveraging text-to-image diffusion model and seamlessly blends it into the original scene to generate visually coherent and spatially consistent compositions. We evaluated Shape2Animal on a diverse set of real-world inputs, demonstrating its robustness and creative potential. Our Shape2Animal can offer new opportunities for visual storytelling, educational content, digital art, and interactive media design. Our project page is here: https://shape2image.github.io

James Luther, Donald Brown

Culture is a core component of human-to-human interaction and plays a vital role in how we perceive and interact with others. Advancements in the effectiveness of Large Language Models (LLMs) in generating human-sounding text have greatly increased the amount of human-to-computer interaction. As this field grows, the cultural alignment of these human-like agents becomes an important field of study. Our work uses Hofstede's VSM13 international surveys to understand the cultural alignment of the following models: DeepSeek-V3, V3.1, GPT-4, GPT-4.1, GPT-4o, and GPT-5. We use a combination of prompt language and cultural prompting, a strategy that uses a system prompt to shift a model's alignment to reflect a specific country, to align these LLMs with the United States and China. Our results show that DeepSeek-V3, V3.1, and OpenAI's GPT-5 exhibit a close alignment with the survey responses of the United States and do not achieve a strong or soft alignment with China, even when using cultural prompts or changing the prompt language. We also find that GPT-4 exhibits an alignment closer to China when prompted in English, but cultural prompting is effective in shifting this alignment closer to the United States. Other low-cost models, GPT-4o and GPT-4.1, respond to the prompt language used (i.e., English or Simplified Chinese) and cultural prompting strategies to create acceptable alignments with both the United States and China.

Dane H. Klinger, R. Naylor

P. Joseph

O. V. Krushelnytska

An important aspect of industrial fish farming is the increase in technogenic influence on the habitat of aquatic organisms, which suppresses the functions of the fish immune system or promotes the development of hypersensitivity and autoimmune reactions due to disruption of the mechanisms of immune system regulation, which leads to disruption of the homeostasis of the fish organism. Due to the tense environmental situation, including aquatic ecosystems, the search for environmentally safe immunostimulants necessary to maintain the organism's homeostasis and its correction is urgent. The search was conducted on carp (Cyprinus carpio) in aquarium conditions. The main hydrochemical parameters corresponded the fishery standards. The investigation was conducted for 5 – 10 – 15 – 20 days using the preparation in different doses: 5 – 10 – 15 mg per kilogram of fish weight. Thus, 4 groups were formed: a control and three experimental groups. The results of investigation of the influence of an immunostimulant of natural origin on immunological indicators are presented. The relationship between humoral and cellular immunity when using the immunostimulant in different doses and time ranges is searched. It was set up that the optimal dose of the preparation is 10 mg/kg of fish weight, which leads to an increase in the level of immunoglobulins, T- and B-lymphocytes without changes in the content of circulating immune complexes. Their ratio varies depending on the dose and duration of preparation use. Analyzing the data got over time, a significant increase in the number of immunocompetent cells investigated was observed on the 15th-20th day of preparation use. Researches have not revealed a negative influence of the preparation on regulatory T-cells, which indicates a normal course of immune response regulation. The activation of the biosynthesis of immunoglobulins indicates an increase in the tension of humoral immunity. However, such an increase in the humoral component of the immune response is not the result of an increasing antigenic load, since the searches were conducted in aquarium conditions. Evidence of this fact is the absence of significant changes in the level of circulating immune complexes at different doses of the immunostimulant and the period of its use, given that circulating immune complexes characterize the degree of interaction of the antigen-antibody complex in the animal organism and are directed at eliminating pathogens. The use of the immunostimulating preparation had a beneficial influence on the level of cellular and humoral immunity of fish. This was reflected in an increase in the level of total T-lymphocytes, active T-lymphocytes, B-lymphocytes and immunoglobulins. An effective immunostimulating effect was achieved at a dose of 10 mg/kg of fish weight with a duration of use of the preparation  for 15–20 days. Research into optimal preparation doses for different age groups and sizes of fish will help determine the most effective doses for different categories of carp. In addition, it is important to conduct searches on other fish species to evaluate the efficacy of the investigational preparation and its potential use in different aquaculture systems. It is also actual to further investigation the possibility of combined use of the preparation with other immunostimulants or therapeutic preparation to enhance the overall immune defense of fish. An important aspect is the research of the ecological influence of the use of the immunostimulant in fish farming, including the possibility of its accumulation in aquatic ecosystems and the influence on other aquatic organisms.

Xuyang Cao, Guoxin Wang, Sheng Shi et al.

Audio-driven portrait animation has made significant advances with diffusion-based models, improving video quality and lipsync accuracy. However, the increasing complexity of these models has led to inefficiencies in training and inference, as well as constraints on video length and inter-frame continuity. In this paper, we propose JoyVASA, a diffusion-based method for generating facial dynamics and head motion in audio-driven facial animation. Specifically, in the first stage, we introduce a decoupled facial representation framework that separates dynamic facial expressions from static 3D facial representations. This decoupling allows the system to generate longer videos by combining any static 3D facial representation with dynamic motion sequences. Then, in the second stage, a diffusion transformer is trained to generate motion sequences directly from audio cues, independent of character identity. Finally, a generator trained in the first stage uses the 3D facial representation and the generated motion sequences as inputs to render high-quality animations. With the decoupled facial representation and the identity-independent motion generation process, JoyVASA extends beyond human portraits to animate animal faces seamlessly. The model is trained on a hybrid dataset of private Chinese and public English data, enabling multilingual support. Experimental results validate the effectiveness of our approach. Future work will focus on improving real-time performance and refining expression control, further expanding the applications in portrait animation. The code is available at: https://github.com/jdh-algo/JoyVASA.

Balaji VS, Mahi AR, Anirudh Ganapathy PS et al.

Agriculture faces a growing challenge with wildlife wreaking havoc on crops, threatening sustainability. The project employs advanced object detection, the system utilizes the Mobile Net SSD model for real-time animal classification. The methodology initiates with the creation of a dataset, where each animal is represented by annotated images. The SSD Mobile Net architecture facilitates the use of a model for image classification and object detection. The model undergoes fine-tuning and optimization during training, enhancing accuracy for precise animal classification. Real-time detection is achieved through a webcam and the OpenCV library, enabling prompt identification and categorization of approaching animals. By seamlessly integrating intelligent scarecrow technology with object detection, this system offers a robust solution to field protection, minimizing crop damage and promoting precision farming. It represents a valuable contribution to agricultural sustainability, addressing the challenge of wildlife interference with crops. The implementation of the Intelligent Scarecrow Monitoring System stands as a progressive tool for proactive field management and protection, empowering farmers with an advanced solution for precision agriculture. Keywords: Machine learning, Deep Learning, Computer Vision, MobileNet SSD

Michael E. Todhunter, Sheikh Jubair, Ruchika Verma et al.

Cultured meat has the potential to provide a complementary meat industry with reduced environmental, ethical, and health impacts. However, major technological challenges remain which require time- and resource-intensive research and development efforts. Machine learning has the potential to accelerate cultured meat technology by streamlining experiments, predicting optimal results, and reducing experimentation time and resources. However, the use of machine learning in cultured meat is in its infancy. This review covers the work available to date on the use of machine learning in cultured meat and explores future possibilities. We address four major areas of cultured meat research and development: establishing cell lines, cell culture media design, microscopy and image analysis, and bioprocessing and food processing optimization. This review aims to provide the foundation necessary for both cultured meat and machine learning scientists to identify research opportunities at the intersection between cultured meat and machine learning.

Shaily Bhatt, Fernando Diaz

Productive interactions between diverse users and language technologies require outputs from the latter to be culturally relevant and sensitive. Prior works have evaluated models' knowledge of cultural norms, values, and artifacts, without considering how this knowledge manifests in downstream applications. In this work, we focus on extrinsic evaluation of cultural competence in two text generation tasks, open-ended question answering and story generation. We quantitatively and qualitatively evaluate model outputs when an explicit cue of culture, specifically nationality, is perturbed in the prompts. Although we find that model outputs do vary when varying nationalities and feature culturally relevant words, we also find weak correlations between text similarity of outputs for different countries and the cultural values of these countries. Finally, we discuss important considerations in designing comprehensive evaluation of cultural competence in user-facing tasks.

Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania et al.

We present a survey of more than 90 recent papers that aim to study cultural representation and inclusion in large language models (LLMs). We observe that none of the studies explicitly define "culture, which is a complex, multifaceted concept; instead, they probe the models on some specially designed datasets which represent certain aspects of "culture". We call these aspects the proxies of culture, and organize them across two dimensions of demographic and semantic proxies. We also categorize the probing methods employed. Our analysis indicates that only certain aspects of ``culture,'' such as values and objectives, have been studied, leaving several other interesting and important facets, especially the multitude of semantic domains (Thompson et al., 2020) and aboutness (Hershcovich et al., 2022), unexplored. Two other crucial gaps are the lack of robustness of probing techniques and situated studies on the impact of cultural mis- and under-representation in LLM-based applications.

Guanghui Liu, C. Betts, D. Cunoosamy et al.

Animal models remain invaluable for study of respiratory diseases, however, translation of data generated in genetically homogeneous animals housed in a clean and well-controlled environment does not necessarily provide insight to the human disease situation. In vitro human systems such as air liquid interface (ALI) cultures and organ-on-a-chip models have attempted to bridge the divide between animal models and human patients. However, although 3D in nature, these models struggle to recreate the architecture and complex cellularity of the airways and parenchyma, and therefore cannot mimic the complex cell-cell interactions in the lung. To address this issue, lung slices have emerged as a useful ex vivo tool for studying the respiratory responses to inflammatory stimuli, infection, and novel drug compounds. This review covers the practicality of precision cut lung slice (PCLS) generation and benefits of this ex vivo culture system in modeling human lung biology and disease pathogenesis.