The Rhythm of Tai Chi reinterprets the ancient Chinese martial art as a dynamic, interactive virtual reality (VR) experience. By leveraging computer vision and multimedia technologies, the project transforms Tai Chi's philosophy and movements into an immersive digital form. Real-time motion tracking captures user gestures, while visual feedback systems simulate the flow of Qi, enabling an intuitive and engaging practice environment. Beyond technological innovation, this work bridges traditional Chinese culture and modern audiences. It offers a global platform - accessible even to those unfamiliar with Tai Chi - to explore its cultural significance, connections to balance, health, and mindfulness. Serving as both a preservation tool and an educational resource, The Rhythm of Tai Chi revitalizes this heritage for the digital age.
Language Models (LMs) are typically tuned with human preferences to produce helpful responses, but the impact of preference tuning on the ability to handle culturally diverse queries remains understudied. In this paper, we systematically analyze how native human cultural preferences can be incorporated into the preference learning process to train more culturally aware LMs. We introduce \textbf{CARE}, a multilingual resource containing 3,490 culturally specific questions and 31.7k responses with human judgments. We demonstrate how a modest amount of high-quality native preferences improves cultural awareness across various LMs, outperforming larger generic preference data. Our analyses reveal that models with stronger initial cultural performance benefit more from alignment, leading to gaps among models developed in different regions with varying access to culturally relevant data. CARE is publicly available at https://github.com/Guochry/CARE.
A 10-year-old intact female Bichon Frise presented with multiple firm skin nodules on all four limbs. The nodules progressively increased in number and size over seven months. Diagnostic tests included cytology of fine-needle aspirates, histopathology of skin biopsies, radiography, and abdominal ultrasonography. Cytology revealed spindle-shaped mesenchymal cells and extracellular matrix components, and histopathology confirmed ND characterized by mature collagen deposition without evidence of malignancy. Ultrasonography detected multiple kidney cysts bilaterally, although their exact nature (benign or malignant) could not be confirmed histologically. Genetic analysis was performed, revealing no mutation in the traditionally implicated FLCN gene but multiple nonsynonymous mutations in the BRCA2 gene. This case suggests a potential association between BRCA2 gene mutations and the development of ND with renal cystic lesions, broadening the known genetic causes beyond the commonly reported FLCN mutation. Regular genetic screening and close monitoring of dermatological and renal conditions in atypical breeds are recommended. To the best of current knowledge, this is the first case report demonstrating ND and renal cysts associated with BRCA2 mutations in a Bichon Frise.
Scrapie is a notifiable transmissible spongiform encephalopathy (TSE) in sheep that relies on clinical examinations for reporting suspects. A short examination protocol was used in 1002 sheep to define clinical markers suggestive of scrapie. Sheep were naturally or experimentally exposed to a classical, atypical scrapie or bovine spongiform encephalopathy agent; 312 were positive for a transmissible spongiform encephalopathy (TSE) by brain examination and included non-exposed controls. Assessed signs were posture, behaviour, menace, scratch and blindfolding response, wool loss and skin changes, body condition, incoordination and tremor. First, the combined occurrence of two or more clinical signs was compared between TSE-positive and negative sheep. Second, the importance of clinical markers was determined in a general classification and regression tree model. The main clinical markers to predict TSEs according to the tree model were incoordination and a positive scratch test. Test sensitivities and specificities were 70.8–81.5% and 96.1–93.0%, respectively, and predictive values above 87%. The results suggest that the short clinical protocol, which assesses the presence of certain clinical signs associated with a TSE in sheep and is quick to perform, may be useful to reach a suspect diagnosis in both naturally and experimentally generated TSEs.
Shreya Havaldar, Salvatore Giorgi, Sunny Rai
et al.
Cultural variation exists between nations (e.g., the United States vs. China), but also within regions (e.g., California vs. Texas, Los Angeles vs. San Francisco). Measuring this regional cultural variation can illuminate how and why people think and behave differently. Historically, it has been difficult to computationally model cultural variation due to a lack of training data and scalability constraints. In this work, we introduce a new research problem for the NLP community: How do we measure variation in cultural constructs across regions using language? We then provide a scalable solution: building knowledge-guided lexica to model cultural variation, encouraging future work at the intersection of NLP and cultural understanding. We also highlight modern LLMs' failure to measure cultural variation or generate culturally varied language.
Self-tracking, the collection, analysis, and interpretation of personal data, signifies an individualized way of health governance as people are demanded to build a responsible self by internalizing norms. However, the technological promises often bear conflicts with various social factors such as a strenuous schedule, a lack of motivation, stress, and anxieties, which fail to deliver health outcomes. To re-problematize the phenomenon, this paper situates self-tracking in an overworking culture in China and draws on semi structured and in depth interviews with overworking individuals to reveal the patterns in users interactions and interpretations with self-tracking data. It builds on the current literature of self-tracking and engages with theories from Science and Technology Studies, especially sociomaterial assemblages (Lupton 2016) and technological mediation (Verbeek 2005), to study self-tracking in a contextualized way which connects the micro (data reading, visualization, and affective elements in design) with the macro (work and workplaces, socioeconomic and political background) contexts of self-tracking. Drawing on investigation of the social context that users of self-tracking technologies internalize, reflect, or resist, the paper argues that the productivity and value oriented assumptions and workplace culture shape the imaginary of intensive (and sometimes impossible) self-care and health, an involution of competence embedded in the technological design and users affective experiences. Users respond by enacting different design elements and social contexts to frame two distinctive data practices of self-tracking.
The integration of new technology with cultural studies enhances our understanding of cultural heritage but often struggles to connect with diverse audiences. It is challenging to align personal interpretations with the intended meanings across different cultures. Our study investigates the important factors in appreciating art from a cross-cultural perspective. We explore the application of Large Language Models (LLMs) to bridge the cultural and language barriers in understanding Traditional Chinese Paintings (TCPs). We present CultiVerse, a visual analytics system that utilizes LLMs within a mixed-initiative framework, enhancing interpretative appreciation of TCP in a cross-cultural dialogue. CultiVerse addresses the challenge of translating the nuanced symbolism in art, which involves interpreting complex cultural contexts, aligning cross-cultural symbols, and validating cultural acceptance. CultiVerse integrates an interactive interface with the analytical capability of LLMs to explore a curated TCP dataset, facilitating the analysis of multifaceted symbolic meanings and the exploration of cross-cultural serendipitous discoveries. Empirical evaluations affirm that CultiVerse significantly improves cross-cultural understanding, offering deeper insights and engaging art appreciation.
In order to further reveal the special characteristics of energy metabolism and the characteristics of energy requirements of fattening pigs grown in low-temperature environments, this study used a 2 × 2 × 2 factorial array of treatments, which harnessed two temperatures (low-temperature, LT group: 10 °C; normal-temperature, NT group: 20 °C), two feed energy levels (normal-energy, NE group: 14.02 MJ/kg metabolic energy; high-energy, HE group: 15.14 MJ/kg metabolic energy), and two feed energy sources (LF group: low fat, HF group: high fat). Thirty-two Songliao black fattening pigs with an initial body weight of 85.48 ± 2.31 kg were completely randomized into eight treatment groups, with four replicates in each treatment group and one pig in each replicate. The pigs were placed in a respiratory metabolic chamber for a 6-day trial. There was one pig per respiratory metabolic chamber in a single cage. The results showed that the average daily weight gain in the normal-temperature, high-energy, and high-fat groups was higher than that of the low-temperature, normal-energy, and low-fat groups (<i>p</i> < 0.05). The fat deposition rate, protein oxidation, and fat oxidation of the high-fat group were higher than those of the low-fat group (<i>p</i> < 0.05). The energy digestibility, protein digestibility, and fat digestibility in the high-fat group were higher than those in the normal-energy group (<i>p</i> < 0.05). The fat digestibility and energy deposition rate in the high-fat group were higher than those in the low-fat group (<i>p</i> < 0.05). The respiratory quotient in the high-energy group was lower than that in the normal-energy group (<i>p</i> < 0.05), and the respiratory quotient in the high-fat group was lower than that in the low-fat group (<i>p</i> < 0.05). There was an interaction between temperature and energy sources in terms of the respiratory quotient, fat oxidation, blood urea nitrogen content, and glucose content (<i>p</i> < 0.05). Appropriately increasing the energy level of the diet and improving the energy structure of the feed (increasing the level of fats and oils) will benefit Songliao black fattening pigs by increasing their energy use efficiency and at the same time reducing greenhouse gas CO<sub>2</sub> emissions, and these changes are more pronounced in cold environments.
Current image-based keypoint detection methods for animal (including human) bodies and faces are generally divided into full-supervised and few-shot class-agnostic approaches. The former typically relies on laborious and time-consuming manual annotations, posing considerable challenges in expanding keypoint detection to a broader range of keypoint categories and animal species. The latter, though less dependent on extensive manual input, still requires necessary support images with annotation for reference during testing. To realize zero-shot keypoint detection without any prior annotation, we introduce the Open-Vocabulary Keypoint Detection (OVKD) task, which is innovatively designed to use text prompts for identifying arbitrary keypoints across any species. In pursuit of this goal, we have developed a novel framework named Open-Vocabulary Keypoint Detection with Semantic-feature Matching (KDSM). This framework synergistically combines vision and language models, creating an interplay between language features and local keypoint visual features. KDSM enhances its capabilities by integrating Domain Distribution Matrix Matching (DDMM) and other special modules, such as the Vision-Keypoint Relational Awareness (VKRA) module, improving the framework's generalizability and overall performance.Our comprehensive experiments demonstrate that KDSM significantly outperforms the baseline in terms of performance and achieves remarkable success in the OVKD task.Impressively, our method, operating in a zero-shot fashion, still yields results comparable to state-of-the-art few-shot species class-agnostic keypoint detection methods.We will make the source code publicly accessible.
Jessica K. Hodgins, Wayne L. Wooten, David C. Brogan
et al.
This paper describes algorithms for the animation of men and women performing three dynamic athletic behaviors: running, bicycling, and vaulting. We animate these behaviors using control algorithms that cause a physically realistic model to perform the desired maneuver. For example, control algorithms allow the simulated humans to maintain balance while moving their arms, to run or bicycle at a variety of speeds, and to perform a handspring vault. Algorithms for group behaviors allow a number of simulated bicyclists to ride as a group while avoiding simple patterns of obstacles. We add secondary motion to the animations with spring-mass simulations of clothing driven by the rigid-body motion of the simulated human. For each simulation, we compare the computed motion to that of humans performing similar maneuvers both qualitatively through the comparison of real and simulated video images and quantitatively through the comparison of simulated and biomechanical data.
Perception of offensiveness is inherently subjective, shaped by the lived experiences and socio-cultural values of the perceivers. Recent years have seen substantial efforts to build AI-based tools that can detect offensive language at scale, as a means to moderate social media platforms, and to ensure safety of conversational AI technologies such as ChatGPT and Bard. However, existing approaches treat this task as a technical endeavor, built on top of data annotated for offensiveness by a global crowd workforce without any attention to the crowd workers' provenance or the values their perceptions reflect. We argue that cultural and psychological factors play a vital role in the cognitive processing of offensiveness, which is critical to consider in this context. We re-frame the task of determining offensiveness as essentially a matter of moral judgment -- deciding the boundaries of ethically wrong vs. right language within an implied set of socio-cultural norms. Through a large-scale cross-cultural study based on 4309 participants from 21 countries across 8 cultural regions, we demonstrate substantial cross-cultural differences in perceptions of offensiveness. More importantly, we find that individual moral values play a crucial role in shaping these variations: moral concerns about Care and Purity are significant mediating factors driving cross-cultural differences. These insights are of crucial importance as we build AI models for the pluralistic world, where the values they espouse should aim to respect and account for moral values in diverse geo-cultural contexts.
We introduce seven foundational principles for creating a culture of constructive criticism in computational legal studies. Beginning by challenging the current perception of papers as the primary scholarly output, we call for a more comprehensive interpretation of publications. We then suggest to make these publications computationally reproducible, releasing all of the data and all of the code all of the time, on time, and in the most functioning form possible. Subsequently, we invite constructive criticism in all phases of the publication life cycle. We posit that our proposals will help form our field, and float the idea of marking this maturity by the creation of a modern flagship publication outlet for computational legal studies.
Niamh Mimnagh, Iuri Ferreira, Luciano Verdade
et al.
We propose a modelling framework which allows for the estimation of abundances from trace counts. This indirect method of estimating abundance is attractive due to the relative affordability with which it may be carried out, and the reduction in possible risk posed to animals and humans when compared to direct methods for estimating animal abundance. We assess these methods by performing simulations which allow us to examine the accuracy of model estimates. The models are then fitted to several case studies to obtain abundance estimates for collared peccaries in Brazil, kit foxes in Arizona, red foxes in Italy and sika deer in Scotland. Simulation results reveal that these models produce accurate estimates of abundance at a range of sample sizes. In particular, this modelling framework produces accurate estimates when data is very scarce. The use of vestige counts in estimating abundance allows for the monitoring of species which may otherwise go undetected due to their reclusive nature. Additionally, the efficacy of these models when data is collected at very few transects will allow for the use of small-scale data collection programmes which may be carried out at reduced cost, when compared to larger-scale data collection.
We consider minimal-perimeter lattice animals, providing a set of conditions which are sufficient for a lattice to have the property that inflating all minimal-perimeter animals of a certain size yields (without repetitions) all minimal-perimeter animals of a new, larger size. We demonstrate this result on the two-dimensional square and hexagonal lattices. In addition, we characterize the sizes of minimal-perimeter animals on these lattices that are not created by inflating members of another set of minimal-perimeter animals.
Bayeta Senbata Wakjira,1 Edilu Jorga,2 Matios Lakew,1 Abebe Olani,1 Biniam Tadesse,1 Getachew Tuli,1 Redeat Belaineh,1 Shubisa Abera,1 Getachew Kinfe,1 Solomon Gebre1 1Animal Health Institute, Sebeta, Ethiopia; 2Ambo University, College of Agriculture and Veterinary Science, Ambo, EthiopiaCorrespondence: Bayeta Senbata Wakjira, Email didigabruma@gmail.comIntroduction: Brucellosis is a neglected bacterial zoonosis with serious veterinary and public health importance throughout the world. A cross-sectional study on animal brucellosis was conducted aiming to estimate seroprevalence and molecular detection.Methods: Blood samples were collected from a total of 4274 individual animals (cattle, small ruminants and camel) from 241 herds/flocks for serology and PCR. Serum samples were tested using multispecies I-ELISA. Blood clots from seropositive animals were also tested for brucellosis via PCR. Additionally, 13 vaginal swab samples were collected from animals (2 from bovine and 11 from small ruminants) with recent abortion history for bacterial isolation and molecular detection.Results: The overall individual animal and herd level seroprevalence was 3.95% (169/4274) and 18.26% (44/241) respectively. The animal level seroprevalence at species level was 1.58% (47/2982), 8.89% (97/1091) and 12.44% (25/201) in bovine, small ruminants (sheep and goat) and camel, respectively. Herd level seroprevalence were 5.43% (10/184), 52.08% (25/48) and 100% (9/9) in bovine, small ruminant and camel, respectively. The animal level seroprevalence of bovine from intensive and extensive systems was 1.10% (31/2808) and 2.87% (5/174) respectively. Blood clots tested for brucellosis via PCR were negative by RT-PCR. Brucella species was isolated from 6/13 (46.15%) vaginal swab samples cultured on Brucella selective agar, and shown to be B. melitensis using Real-Time PCR.Conclusion: Overall, seropositivity for camels was higher than what has been reported previously. Also, there was a notable difference in this study in cattle seroprevalence when comparing extensive with intensive systems, with the extensive system having much greater seropositivity.Keywords: Brucella melitensis, neglected bacterial diseases, camel, zoonosis
Isa Mohammed Alkali, Suleiman Omeiza Asuku, Martina Colombo
et al.
Populations of many galliform species have declined mainly due to habitat loss and over-hunting, notably the Congo peacock, which has been classified as a vulnerable species by the International Union for Conservation of Nature (IUCN). The domestic turkey, being a species of least concern, which has been reported to be closely related to peacocks, could serve as a model for the optimization of assisted reproductive technologies for the Congo peacock. This study was aimed at developing a suitable turkey semen extender for artificial insemination in field conditions. Semen was collected using the dorso-abdominal massage technique from seven turkey toms and analyzed. Ejaculates with >70% motility and >80% live spermatozoa were pooled and divided into four aliquots (four treatments). Each of the four treatments was extended in a soybean-based extender or an egg yolk-based extender, with or without L-ascorbic acid. Two liquid preservation protocols (ambient temperature (35 °C) and chilled (4 °C)) were employed, and quality parameters including motility, viability and morphology were evaluated. The results show that the two extenders were similar with regard to semen quality parameters, and L-ascorbic acid supplementation of the turkey semen extenders improved semen quality during liquid storage.
This paper illustrates the intergenerational transmission of the gender gap in education among first and second-generation immigrants. Using the Current Population Survey (1994-2018), we find that the difference in female-male education persists from the home country to the new environment. A one standard deviation increase of the ancestral country female-male difference in schooling is associated with 17.2% and 2.5% of a standard deviation increase in the gender gap among first and second generations, respectively. Since gender perspective in education uncovers a new channel for cultural transmission among families, we interpret the findings as evidence of cultural persistence among first generations and partial cultural assimilation of second generations. Moreover, Disaggregation into country-groups reveals different paths for this transmission: descendants of immigrants of lower-income countries show fewer attachments to the gender opinions of their home country. Average local education of natives can facilitate the acculturation process. Immigrants residing in states with higher education reveal a lower tendency to follow their home country attitudes regarding the gender gap.
Mei-Ling E. Feng, Olukunle O. Owolabi, Toryn L. J. Schafer
et al.
Animal-related outages (AROs) are a prevalent form of outages in electrical distribution systems. Animal-infrastructure interactions vary across focal species and regions, underlining the need to study the animal-outage relationship in more species and diverse systems. Animal activity has been used as an indicator of reliability in the electrical grid system and to describe temporal patterns in AROs. However, these ARO models have been limited by a lack of available estimates of species activity, instead approximating activity based on seasonal and weather patterns in animal-related outage records and characteristics of broad taxonomic groups, e.g., squirrels. We highlight publicly available resources to fill the ecological data gap that is limiting joint analyses between ecology and energy sectors. Species distribution models (SDMs), a common technique to model the distribution of a species across geographic space and time, paired with data sourced from eBird, a community science database for bird observations, provided us with species-specific estimates of activity to model spatio-temporal patterns of AROs. These flexible, species-specific estimates can allow future animal-indicators of grid reliability to be investigated in more diverse regions and ecological communities, providing a better understanding of the variation that exists in animal-outage relationship. AROs were best modeled by accounting for multiple outage-prone species activity patterns and their unique relationships with seasonality and habitat availability. Different species were important for modeling outages in different landscapes and seasons depending on their distribution and migration behavior. We recommend that future models of AROs include species-specific activity data that account for the diverse spectrum of spatio-temporal activity patterns that outage-prone animals exhibit.