Hasil untuk "Animal culture"

S. Galgano, L. Conway, A. Fellows et al.

Several authors described the sexual dimorphism of the gut microbiota in pigs and other animals in relation to sex-specific modulation following interventions such as diet or prebiotics and probiotics. These differences can also influence the host phenotype through the bi-directional pathways of the microbiota-gut-brain axis and could ultimately impact an animal’s welfare and well−being. Postweaning diarrhoea is a multifactorial disease that occurs in piglets and is characterised by the sudden diet change from the sow milk to solid feedstuff, with moderate to heavy diarrhoea, accompanied by decreased performance, usually BW gain. In our previous work, we described that the broad-spectrum antimicrobial-alternative peracetic acid ameliorated the diarrhetic symptoms in piglets similarly to what was observed for zinc oxide. Here, we present a further analysis of this data set, assessing the interactions between interventions and sex. A 14-day animal study was carried out, during which 28-day−old, weaned piglets were allocated to 24-floor pens with four treatments, six pens and 12 piglets per treatment, six males and six females. The four treatments were a negative control, supra-nutritional in-feed zinc oxide, and either 50 or 150 mg/kg of in-water peracetic acid. Performance and postweaning diarrhoea were assessed throughout the study, whereas at day 14, gastrointestinal content samples were collected from all the pigs to allow downstream total bacterial quantification and 16S rRNA sequencing analysis. We found that the BW gain was greater in females compared to males given zinc oxide or peracetic acid. Moreover, apart from sex-specific differences in the microbial composition, we observed that both peracetic acid and zinc oxide led to different microbial modulation in males and females. Indeed, in the stomach, Sarcina, Actinobacillus and unclassified Neisseriaceae were depleted only in males given the high peracetic acid concentration, whilst the same treatment led to the reduction of Moraxella in females. Escherichia-Shigella was reduced after zinc oxide administration, but only in females. Finally, although Lactobacillus was less abundant in males in the caecum, both zinc oxide and peracetic acid led to its increase, but only in males.

Taihei Shiotani, Masahiro Kaneko, Ayana Niwa et al.

Social biases reflected in language are inherently shaped by cultural norms, which vary significantly across regions and lead to diverse manifestations of stereotypes. Existing evaluations of social bias in large language models (LLMs) for non-English contexts, however, often rely on translations of English benchmarks. Such benchmarks fail to reflect local cultural norms, including those found in Japanese. For instance, Western benchmarks may overlook Japan-specific stereotypes related to hierarchical relationships, regional dialects, or traditional gender roles. To address this limitation, we introduce Japanese cUlture adversarial BiAs benchmarK Under handcrafted creation (JUBAKU), a benchmark tailored to Japanese cultural contexts. JUBAKU uses adversarial construction to expose latent biases across ten distinct cultural categories. Unlike existing benchmarks, JUBAKU features dialogue scenarios hand-crafted by native Japanese annotators, specifically designed to trigger and reveal latent social biases in Japanese LLMs. We evaluated nine Japanese LLMs on JUBAKU and three others adapted from English benchmarks. All models clearly exhibited biases on JUBAKU, performing below the random baseline of 50% with an average accuracy of 23% (ranging from 13% to 33%), despite higher accuracy on the other benchmarks. Human annotators achieved 91% accuracy in identifying unbiased responses, confirming JUBAKU's reliability and its adversarial nature to LLMs.

Chongyuan Dai, Yaling Shen, Jinpeng Hu et al.

Culture serves as a fundamental determinant of human affective processing and profoundly shapes how individuals perceive and interpret emotional stimuli. Despite this intrinsic link extant evaluations regarding cultural alignment within Large Language Models primarily prioritize declarative knowledge such as geographical facts or established societal customs. These benchmarks remain insufficient to capture the subjective interpretative variance inherent to diverse sociocultural lenses. To address this limitation, we introduce CEDAR, a multimodal benchmark constructed entirely from scenarios capturing Culturally \underline{\textsc{E}}licited \underline{\textsc{D}}istinct \underline{\textsc{A}}ffective \underline{\textsc{R}}esponses. To construct CEDAR, we implement a novel pipeline that leverages LLM-generated provisional labels to isolate instances yielding cross-cultural emotional distinctions, and subsequently derives reliable ground-truth annotations through rigorous human evaluation. The resulting benchmark comprises 10,962 instances across seven languages and 14 fine-grained emotion categories, with each language including 400 multimodal and 1,166 text-only samples. Comprehensive evaluations of 17 representative multilingual models reveal a dissociation between language consistency and cultural alignment, demonstrating that culturally grounded affective understanding remains a significant challenge for current models.

Qian Tan, Lei Jiang, Yuting Zeng et al.

Large language models (LLMs) exhibit systematic Western-centric bias, yet whether prompting in non-Western languages (e.g., Chinese) can mitigate this remains understudied. Answering this question requires rigorous evaluation and effective mitigation, but existing approaches fall short on both fronts: evaluation methods force outputs into predefined cultural categories without a neutral option, while mitigation relies on expensive multi-cultural corpora or agent frameworks that use functional roles (e.g., Planner--Critique) lacking explicit cultural representation. To address these gaps, we introduce CEBiasBench, a Chinese--English bilingual benchmark, and Multi-Agent Vote (MAV), which enables explicit ``no bias'' judgments. Using this framework, we find that Chinese prompting merely shifts bias toward East Asian perspectives rather than eliminating it. To mitigate such persistent bias, we propose Multi-Agent Cultural Debate (MACD), a training-free framework that assigns agents distinct cultural personas and orchestrates deliberation via a "Seeking Common Ground while Reserving Differences" strategy. Experiments demonstrate that MACD achieves 57.6% average No Bias Rate evaluated by LLM-as-judge and 86.0% evaluated by MAV (vs. 47.6% and 69.0% baseline using GPT-4o as backbone) on CEBiasBench and generalizes to the Arabic CAMeL benchmark, confirming that explicit cultural representation in agent frameworks is essential for cross-cultural fairness.

L.A. Jiménez-Maroto, S. Govindasamy-Lucey, J.J. Jaeggi et al.

ABSTRACT: High-pressure processing (HPP) and low-temperature storage (0°C) were explored as alternatives to freezing for extending the performance shelf life of low-moisture, part-skim (LMPS) mozzarella intended for export. Batches (n = 5) of reduced Na LMPS mozzarella were manufactured using camel chymosin as a lower proteolytic type of rennet. Cheeses were stored for 2 wk at 4°C, divided into control (non-HPP) and HPP (600 MPa for 3 min) groups, and stored at 3 different temperatures (4, 0, and −18°C) for 365 d. Analyses were performed at 0, 90, 150, 210, 270, and 365 d of storage. Frozen and 0°C samples (∼2.3 kg) were thawed/tempered at 4°C for 1 wk before analysis. Urea PAGE and quantification of the pH 4.6 soluble N over time were used to monitor primary proteolysis. Body and rheological properties were monitored using texture profile analysis (TPA) and dynamic low-amplitude oscillatory rheology. Changes in flavor, body, shred properties, and pizza performance were evaluated using quantitative descriptive analysis with 12 trained panelists using a 15-point scale. High-pressure processing treatment caused ∼5 log cfu/mL reduction in starter counts, partial solubilization of the insoluble Ca, and a small pH increase (from ∼5.2 to 5.3). The rate of primary proteolysis was reduced by HPP and low-temperature storage. High-pressure processing treatment reduced initial cheese hardness, but no further significant decrease was observed over storage time, whereas the hardness of non-HPP samples decreased over the 365 d of storage, apart from the frozen samples. In pizza applications, blister quantity development and loss of strand thickness were limited by storage at −18°C. Freezing LMPS mozzarella to −18°C gave the least changes in proteolysis and pizza performance over the 365 d of study, storage of cheese at 0°C slowed the loss of hardness and the deterioration of pizza performance attributes. The combination of HPP and 0°C storage of cheese resulted in little change in blistering quantity of pizza during the 365 d of study, whereas cheese stored at 0°C had blisters covering much of the pizza after this extended storage time. Combining HPP with low-temperature storage is a promising alternative approach to freezing for the extension of the functionality shelf life of LMPS mozzarella.

Tadesse Destaw Belay, Ahmed Haj Ahmed, Alvin Grissom et al.

NLP research has increasingly focused on subjective tasks such as emotion analysis. However, existing emotion benchmarks suffer from two major shortcomings: (1) they largely rely on keyword-based emotion recognition, overlooking crucial cultural dimensions required for deeper emotion understanding, and (2) many are created by translating English-annotated data into other languages, leading to potentially unreliable evaluation. To address these issues, we introduce Cultural Lenses on Emotion (CuLEmo), the first benchmark designed to evaluate culture-aware emotion prediction across six languages: Amharic, Arabic, English, German, Hindi, and Spanish. CuLEmo comprises 400 crafted questions per language, each requiring nuanced cultural reasoning and understanding. We use this benchmark to evaluate several state-of-the-art LLMs on culture-aware emotion prediction and sentiment analysis tasks. Our findings reveal that (1) emotion conceptualizations vary significantly across languages and cultures, (2) LLMs performance likewise varies by language and cultural context, and (3) prompting in English with explicit country context often outperforms in-language prompts for culture-aware emotion and sentiment understanding. The dataset and evaluation code are publicly available.

Depanshu Sani, Mehar Khurana, Saket Anand

Animal Re-ID has recently gained substantial attention in the AI research community due to its high impact on biodiversity monitoring and unique research challenges arising from environmental factors. The subtle distinguishing patterns, handling new species and the inherent open-set nature make the problem even harder. To address these complexities, foundation models trained on labeled, large-scale and multi-species animal Re-ID datasets have recently been introduced to enable zero-shot Re-ID. However, our benchmarking reveals significant gaps in their zero-shot Re-ID performance for both known and unknown species. While this highlights the need for collecting labeled data in new domains, exhaustive annotation for Re-ID is laborious and requires domain expertise. Our analyses show that existing unsupervised (USL) and AL Re-ID methods underperform for animal Re-ID. To address these limitations, we introduce a novel AL Re-ID framework that leverages complementary clustering methods to uncover and target structurally ambiguous regions in the embedding space for mining pairs of samples that are both informative and broadly representative. Oracle feedback on these pairs, in the form of must-link and cannot-link constraints, facilitates a simple annotation interface, which naturally integrates with existing USL methods through our proposed constrained clustering refinement algorithm. Through extensive experiments, we demonstrate that, by utilizing only 0.033% of all annotations, our approach consistently outperforms existing foundational, USL and AL baselines. Specifically, we report an average improvement of 10.49%, 11.19% and 3.99% (mAP) on 13 wildlife datasets over foundational, USL and AL methods, respectively, while attaining state-of-the-art performance on each dataset. Furthermore, we also show an improvement of 11.09%, 8.2% and 2.06% for unknown individuals in an open-world setting.

Ian Noronha, Advait Prasad Jawaji, Juan Camilo Soto et al.

Animal-robot interaction (ARI) remains an unexplored challenge in robotics, as robots struggle to interpret the complex, multimodal communication cues of animals, such as body language, movement, and vocalizations. Unlike human-robot interaction, which benefits from established datasets and frameworks, animal-robot interaction lacks the foundational resources needed to facilitate meaningful bidirectional communication. To bridge this gap, we present the MBE-ARI (Multimodal Bidirectional Engagement in Animal-Robot Interaction), a novel multimodal dataset that captures detailed interactions between a legged robot and cows. The dataset includes synchronized RGB-D streams from multiple viewpoints, annotated with body pose and activity labels across interaction phases, offering an unprecedented level of detail for ARI research. Additionally, we introduce a full-body pose estimation model tailored for quadruped animals, capable of tracking 39 keypoints with a mean average precision (mAP) of 92.7%, outperforming existing benchmarks in animal pose estimation. The MBE-ARI dataset and our pose estimation framework lay a robust foundation for advancing research in animal-robot interaction, providing essential tools for developing perception, reasoning, and interaction frameworks needed for effective collaboration between robots and animals. The dataset and resources are publicly available at https://github.com/RISELabPurdue/MBE-ARI/, inviting further exploration and development in this critical area.

Athanase Papadopoulos, Susumu Tanabé

This is an essay on the relation of Andr{é} and Simone Weil with Indian culture and Sanskrit literature, especially the Bhagavad G{ī}t{ā}, a Hindu scripture which they knew well, which they quoted extensively, and which guided them in making important life decisions. In addressing this question, we will also talk about the life paths of the two Weils, and more specifically about certain aspects that relate to their deep convictions.

Vinh Truong

This study explores how emotions and sentiments differ in customer reviews of products and services on e-commerce platforms. Unlike earlier research that treats all reviews uniformly, this study distinguishes between reviews of products, typically fulfilling basic, functional needs, and services, which often cater to experiential and emotional desires. The findings reveal clear differences in emotional expression and sentiment between the two. Product reviews frequently focus on practicality, such as functionality, reliability, and value for money, and are generally more neutral or pragmatic in tone. In contrast, service reviews involve stronger emotional engagement, as services often entail personal interactions and subjective experiences. Customers express a broader spectrum of emotions, such as joy, frustration, or disappointment when reviewing services, as identified using advanced machine learning techniques. Cultural background further influences these patterns. Consumers from collectivist cultures, as defined by Hofstede cultural dimensions, often use more moderated and socially considerate language, reflecting an emphasis on group harmony. Conversely, consumers from individualist cultures tend to offer more direct, emotionally intense feedback. Notably, gender appears to have minimal impact on sentiment variation, reinforcing the idea that the nature of the offering (product vs. service) and cultural context are the dominant factors. Theoretically, the study extends Maslow hierarchy of needs and Hofstede cultural framework to the domain of online reviews, proposing a model that explains how these dimensions shape consumer expression. Practically, the insights offer valuable guidance for businesses looking to optimize their marketing and customer engagement strategies by aligning messaging and service design with customer expectations across product types and cultural backgrounds.

Aline Marangon de Oliveira, Anna Luiza Silva de Faria, Daiana Francisca Quirino et al.

Biopsy techniques in dairy goats are currently limited. This study aimed to describe a liver biopsy technique in dairy goats and to evaluate liver triglyceride levels and glycogen content. Sixty-nine dairy goats in the final stage of pregnancy and early lactation period were selected. Fifty goats were selected randomly for hepatic biopsy (HB) according to gestational period and were characterized according to fetus number (single: <i>n</i> = 16, multiple: <i>n</i> = 34), supplementation with propylene glycol (diet: <i>n</i> = 23, diet+PG: <i>n</i> = 27), and milk production levels (high: 3.0 ± 0.4 L/day, n = 15; low: 1.4 ± 0.4 L/day, n = 26). Liver tissue samples were obtained through biopsy on days −30, −20, −15, −10, −5, and 15 days after calving. Hepatic triglyceride and glycogen were quantified. The results were analyzed using the F-test at a 5% significance level and a comparison of means using the Tukey test. The liver biopsies did not influence dry matter intake, body weight, or milk yield. Hepatic glycogen concentration was lower 15 days after calving than it was prior to calving, except on day −20. Goats that generated high levels of milk production had lower triglyceride levels than goats that generated low levels of milk production. The biopsy technique is a safe method for obtaining tissue and evaluating liver content in dairy goats. The milk production level and days relative to parturition influence the hepatic triglyceride and glycogen content in dairy goats.

Lorella Giuliotti, Maria Novella Benvenuti, Giovanna Preziuso et al.

This study investigates the genealogical and demographic trends of the Massese sheep breed in Tuscany from 2001 to 2021. The Herd Book kept by the Italian Sheep and Goat Breeders Association (Asso.Na.Pa) provided the data. The descriptive statistics were analyzed using JMP software. The pedigree parameters of a total of 311,056 animals (whole population—WP) were analyzed using CFC, ENDOG, and Pedigree viewer software. A total of 24,586 animals born in the period 2007–2021 represented the Reference Population (RP), and 18,554 animals the Base Population (BP). The demographic results showed an inconsistent trend of offspring registration. This study showed a short period of productivity for both ewes and rams, with means of 1.47 and 19.2 registered newborn ewes and rams, respectively. The genealogical analysis revealed incomplete data, highlighting inaccurate assessments of the relationships among the animals, and inbreeding with large differences among provinces. The average inbreeding coefficient in the WP was 1.16%, and it was 2.26% in the RP. The total number of inbreds was 2790 in the WP, with an average F_PED of 13.56%, and 2713 in the RP, with an average F_PED of 12.82%. The use of pedigree data is a key and economical approach to calculating inbreeding and relationship coefficients. It is the primary step in genetic management, playing a crucial role in the preservation of a breed. The regular updating of genealogical data is the first step to ensuring the conservation of animal genetic resources, and this study is compromised by the lack of such updates.

Mengya Wang, Lei Zhang, Xingwei Jiang et al.

ABSTRACT: The nutritional components and quality of milk are influenced by the rumen microbiota and its metabolites at different lactation stages. Hence, rumen fluid and milk samples from 6 dairy cows fed the same diet were collected during peak lactation, early mid-lactation, and later mid-lactation. Untargeted metabolomics and 16S rRNA sequencing were applied for analyzing milk and rumen metabolites, as well as rumen microbial composition, respectively. The levels of lipid-related metabolites, l-glutamate, glucose-1-phosphate, and acetylphosphate in milk exhibited lactation-dependent attenuation. Maltol, N-acetyl-d-glucosamine, and choline, which are associated with milk flavor or coagulation properties, as well as l-valine, lansioside A, clitocine, and ginsenoside La, increased significantly in early mid-lactation and later mid-lactation, especially in later mid-lactation. The obvious increase in rumen microbial diversities (ACE and Shannon indices) were observed in early mid-lactation compared with peak lactation. Twenty-one differential bacterial genera of the rumen were identified, with Succinivibrionaceae_UCG-001, Candidatus Saccharimonas, Fibrobacter, and SP3-e08 being significantly enriched in peak lactation. Rikenellaceae_RC9_gut_group, Eubacterium_ruminantium_group, Lachnospira, Butyrivibrio, Eubacterium_hallii_group, and Schwartzia were most significantly enriched in early mid-lactation. In comparison, only 2 bacteria (unclassified_f__Prevotellaceae and Prevotellaceae_UCG-001) were enriched in later mid-lactation. For rumen metabolites, LysoPE(16:0), l-glutamate, and l-tyrosine had higher levels in peak lactation, whereas PE(17:0/0:0), PE(16:0/0:0), PS(18:1(9Z)/0:0), l-phenylalanine, dulcitol, 2-(methoxymethyl)furan, and 3-phenylpropyl acetate showed higher levels in early mid-lactation and later mid-lactation. Multiomics-integrated analysis revealed that a greater abundance of Fibrobacter contributed to phospholipid content in milk by increasing ruminal acetate, l-glutamate, and LysoPE(16:0). Prevotellaceae_UCG-001 and unclassified_f_Prevotellaceae provide substrates for milk metabolites of the same category by increasing ruminal l-phenylalanine and dulcitol contents. These results demonstrated that milk metabolomic fingerprints and critical functional metabolites during lactation, and the key bacteria in rumen related to them. These findings provide new insights into the development of functional dairy products.

Xiukai Cao, Chen Ling, Yongqi Liu et al.

Uncovering genes associated with muscle growth and body size will benefit the molecular breeding of meat Hu sheep. <i>HMGA2</i> has proven to be an important gene in mouse muscle growth and is associated with the body size of various species. However, its roles in sheep are still limited. Using sheep myoblast as a cell model, the overexpression of <i>HMGA2</i> significantly promoted sheep myoblast proliferation, while interference with <i>HMGA2</i> expression inhibited proliferation, indicated by qPCR, EdU, and CCK-8 assays. Furthermore, the dual-luciferase reporter system indicated that the region NC_056056.1: 154134300-154134882 (-618 to -1200 bp upstream of the <i>HMGA2</i> transcription start site) was one of the habitats of the <i>HMGA2</i> core promoter, given the observation that this fragment led to a ~3-fold increase in luciferase activity. Interestingly, SNP rs428001129 (NC_056056.1:g.154134315 C>A) was detected in this fragment by Sanger sequencing of the PCR product of pooled DNA from 458 crossbred sheep. This SNP was found to affect the promoter activity and was significantly associated with chest width at birth and two months old, as well as chest depth at two and six months old. The data obtained in this study demonstrated the phenotypic regulatory role of the <i>HMGA2</i> gene in sheep production traits and the potential of rs428001129 in marker-assisted selection for sheep breeding in terms of chest width and chest depth.

Thiago H Silva, Daniel Silver

Urban research has long recognized that neighbourhoods are dynamic and relational. However, lack of data, methodologies, and computer processing power have hampered a formal quantitative examination of neighbourhood relational dynamics. To make progress on this issue, this study proposes a graph neural network (GNN) approach that permits combining and evaluating multiple sources of information about internal characteristics of neighbourhoods, their past characteristics, and flows of groups among them, potentially providing greater expressive power in predictive models. By exploring a public large-scale dataset from Yelp, we show the potential of our approach for considering structural connectedness in predicting neighbourhood attributes, specifically to predict local culture. Results are promising from a substantive and methodologically point of view. Substantively, we find that either local area information (e.g. area demographics) or group profiles (tastes of Yelp reviewers) give the best results in predicting local culture, and they are nearly equivalent in all studied cases. Methodologically, exploring group profiles could be a helpful alternative where finding local information for specific areas is challenging, since they can be extracted automatically from many forms of online data. Thus, our approach could empower researchers and policy-makers to use a range of data sources when other local area information is lacking.

Shuai Tan, Biao Gong, Xiang Wang et al.

Character image animation, which generates high-quality videos from a reference image and target pose sequence, has seen significant progress in recent years. However, most existing methods only apply to human figures, which usually do not generalize well on anthropomorphic characters commonly used in industries like gaming and entertainment. Our in-depth analysis suggests to attribute this limitation to their insufficient modeling of motion, which is unable to comprehend the movement pattern of the driving video, thus imposing a pose sequence rigidly onto the target character. To this end, this paper proposes Animate-X, a universal animation framework based on LDM for various character types (collectively named X), including anthropomorphic characters. To enhance motion representation, we introduce the Pose Indicator, which captures comprehensive motion pattern from the driving video through both implicit and explicit manner. The former leverages CLIP visual features of a driving video to extract its gist of motion, like the overall movement pattern and temporal relations among motions, while the latter strengthens the generalization of LDM by simulating possible inputs in advance that may arise during inference. Moreover, we introduce a new Animated Anthropomorphic Benchmark (A^2Bench) to evaluate the performance of Animate-X on universal and widely applicable animation images. Extensive experiments demonstrate the superiority and effectiveness of Animate-X compared to state-of-the-art methods.

Weiguo Cui, Qian Zhang, Hanqiong Wang et al.

Transcription factor Homeobox C8 (HOXC8) is identified as a white adipose gene as revealed by expression profile analysis in fat tissues. However, the specific role of HOXC8 in fat accumulation remains to be identified. This study was designed to reveal the effects of HOXC8 on preadipocyte proliferation and differentiation. We first make clear that the expression of HOXC8 is associated with fat contents in muscles, highlighting a role of HOXC8 in fat accumulation. Next, it is demonstrated that HOXC8 promotes the proliferation and differentiation of preadipocytes through gain- and loss-of-function assays in primary cultured porcine preadipocytes. Then, mechanisms underlying the regulation of HOXC8 on preadipocyte proliferation and differentiation are identified with RNA sequencing, and a number of differentially expressed genes (DEGs) in response to HOXC8 knockdown are identified. The top GO (Gene Ontology) terms enriched by DEGs involved in proliferation and differentiation, respectively, are identical. IL-17 signaling pathway is the common one significantly enriched by DEGs involved in preadipocyte proliferation and differentiation, respectively, indicating its importance in mediating fat accumulation regulated by HOXC8. Additionally, we find that the inhibition of proliferation is one of the main processes during preadipocyte differentiation. The results will contribue to further revealing the mechanisms underlying fat accumulation regulated by HOXC8.

Adony Querubino Andrade Neto, José Ricardo Barboza Silva, Carla Lopes de Mendonça et al.

Objetivou-se estudar os achados epidemiológico e anatomopatológico de úlceras do abomaso tipo 1 e 2 em bovinos com diferentes comorbidades primárias. Um total de 201 animais; 40/201 (20%) eram bovinos jovens com idade inferior a dois anos e 161/201 (80%) eram bovinos adultos com idade superior a dois anos, os quais foram internados para atendimento clínico 152/201 (75,62%), 19/201 (9,45%) obstétrico, 17/201 (8,46%) para atendimento clínico-cirúrgico e 13/201 (6,47%) para diagnóstico anatomopatológico, sendo eutanasiados ou tiveram morte natural. O diagnóstico das úlceras foi baseado no exame post-mortem (análise macroscópica e histopatológica). O exame histopatológico foi realizado em 201 fragmentos de úlceras e classificado como tipo 1 ou do tipo 2. Destes, 193/201 (96,01%) corresponderam a úlceras tipo 1, das quais, 12/193 (5,97%) corresponderam a lesões subtipo 1a, 101/193 (50,25%) a subtipo 1b, 77/193 (38,31%) a subtipo 1c, 03/193 (1,49%) ao subtipo 1d, enquanto 08/201 (3,98%) foram úlceras tipo 2. As úlceras foram caracterizadas por processo inflamatório focal, focalmente extenso, multifocais ou difusos, principalmente por células mononucleares. Abomasite associada à mucosa ulcerada foi encontrada em 160/201 (79,60%). Em 26/201 (12,93%) a abomasite apresentava focos difusos de proliferação linfocítica multifocal por linfócitos atípicos. As comorbidades digestivas e reprodutivas foram observadas com maior frequência em bovinos com úlceras tipo 1 ou tipo 2. As úlceras focais subtipo 1b e úlceras multifocais subtipo 1a e 1b foram mais prevalentes. Além da presença de comorbidades, a maioria dos casos ocorrerem no período seco, associados à alimentação com maiores aportes de concentrados e silagens. Palavras Chave: bovinos leiteiros; doenças do abomaso; melena; úlcera; histopatologia.

António Leitão, Maxime Lucas, Simone Poetto et al.

We provide quantitative evidence suggesting social learning in sperm whales across socio-cultural boundaries, using acoustic data from the Pacific and Atlantic Oceans. Traditionally, sperm whale populations are categorized into clans based on their vocal repertoire: the rhythmically patterned click sequences (codas) that they use. Among these codas, identity codas function as symbolic markers for each clan, accounting for 35-60% of codas they produce. We introduce a computational method to model whale speech, which encodes rhythmic micro-variations within codas, capturing their vocal style. We find that vocal style-clans closely align with repertoire-clans. However, contrary to vocal repertoire, we show that sympatry increases vocal style similarity between clans for non-identity codas, i.e. most codas, suggesting social learning across cultural boundaries. More broadly, this subcoda structure model offers a framework for comparing communication systems in other species, with potential implications for deeper understanding of vocal and cultural transmission within animal societies.

Peter Galison, Juliusz Doboszewski, Jamee Elder et al.

This white paper outlines the plans of the History Philosophy Culture Working Group of the Next Generation Event Horizon Telescope Collaboration.