Hasil untuk "Natural history (General)"

Jasmine Ferrario, Clara B. Giachetti, Katherine A. Dafforn et al.

O Mandrik, S Whyte, N Kunst et al.

Introduction: The potential for multi-cancer early detection (MCED) tests to detect cancer at earlier stages is currently being evaluated in screening clinical trials. Once trial evidence becomes available, modelling will be necessary to predict impacts on final outcomes (benefits and harms), account for heterogeneity in determining clinical and cost-effectiveness, and explore alternative screening programme specifications. The natural history of disease (NHD) component of a MCED model will use statistical, mathematical or calibration methods. Methods: Modelling approaches for MCED screening that include an NHD component were identified from the literature, reviewed and critically appraised. Purposively selected (non-MCED) cancer screening models were also reviewed. The appraisal focussed on the scope, data sources, evaluation approaches and the structure and parameterisation of the models. Results: Five different MCED NHD models were identified and reviewed, alongside four additional (non-MCED) models. The critical appraisal highlighted several features of this literature. In the absence of trial evidence, MCED effects are based on predictions derived from test accuracy. These predictions rely on simplifying assumptions with unknown impacts, such as the stage-shift assumption used to estimate mortality impacts from predicted stage-shifts. None of the MCED models fully characterised uncertainty in the NHD or examined uncertainty in the stage-shift assumption. Conclusion: MCED technologies are developing rapidly, and large and costly clinical studies are being designed and implemented across the globe. Currently there is no modelling approach that can integrate clinical study evidence and therefore, in support of policy, it is important that similar efforts are made in the development of MCED models that make best use of the available data on benefits and harms.

Toheeb Aduramomi Jimoh, Tabea De Wille, Nikola S. Nikolov

Natural Language Processing (NLP) is becoming a dominant subset of artificial intelligence as the need to help machines understand human language looks indispensable. Several NLP applications are ubiquitous, partly due to the myriad of datasets being churned out daily through mediums like social networking sites. However, the growing development has not been evident in most African languages due to the persisting resource limitations, among other issues. Yorùbá language, a tonal and morphologically rich African language, suffers a similar fate, resulting in limited NLP usage. To encourage further research towards improving this situation, this systematic literature review aims to comprehensively analyse studies addressing NLP development for Yorùbá, identifying challenges, resources, techniques, and applications. A well-defined search string from a structured protocol was employed to search, select, and analyse 105 primary studies between 2014 and 2024 from reputable databases. The review highlights the scarcity of annotated corpora, the limited availability of pre-trained language models, and linguistic challenges like tonal complexity and diacritic dependency as significant obstacles. It also revealed the prominent techniques, including rule-based methods, among others. The findings reveal a growing body of multilingual and monolingual resources, even though the field is constrained by socio-cultural factors such as code-switching and the desertion of language for digital usage. This review synthesises existing research, providing a foundation for advancing NLP for Yorùbá and in African languages generally. It aims to guide future research by identifying gaps and opportunities, thereby contributing to the broader inclusion of Yorùbá and other under-resourced African languages in global NLP advancements.

Shannon P. Finnegan, William Dunker, Nathan J. Svoboda et al.

Abstract Telemetry studies allow scientists to track animal movements and study species ecology without direct visual observation. Fitting telemetry devices requires physical or chemical capture and restraint of animals. Ground darting is a commonly used technique to capture cervids but locating animals to dart and finding individuals post induction remains a challenge. Here we present an application of using thermal imaging drones to help locate, ground dart, and monitor target animals to ensure safe immobilization. We immobilized 10 free‐ranging Sitka black‐tailed deer (Odocoileus hemionus sitkensis), 8 of which were captured with the assistance of the thermal drone. The utilization of drones in wildlife ground darting operations can increase safety and efficiency, and reduce risk to researchers and study subjects.

Maxim V. Vinarski, Jean-Pierre Pointier

William V. DeLuca, Nathaniel E. Seavy, Joanna Grand et al.

Abstract The conservation of migratory birds poses a fundamental challenge, their conservation requires coordinated action across the hemisphere, but those actions must be designed and implemented locally. To address this challenge, we describe a multilevel framework for linking broad‐scale, full annual cycle prioritizations to local conservation actions for migratory birds. We developed hemisphere‐scale spatial prioritizations for the full annual cycle of migratory birds that breed in six different ecosystems in North America. The full annual cycle prioritizations provide a hemispheric context within which regional priorities can be identified. Finer resolution, regional prioritizations can then inform local conservation actions more effectively. We describe the importance of local conservation practitioner contributions at each level of the process and provide two examples of regional spatial prioritizations that were developed to guide local action. The first example focused on coastal North and South Carolina, USA, and used information on marsh birds, shorebirds, ecological integrity, and co‐benefits for people to identify Cape Romain, South Carolina as a high‐priority site for conservation action. The second example in Colombia used information on migrant and resident birds to identify the Cauca Valley as a high‐priority site. The multilevel conceptual framework we describe is one pathway for identifying sites for implementation of local conservation actions that are guided by conservation priorities for migratory birds across their full annual cycle.

Kaichen Zhang, Zixuan Yuan, Hui Xiong

Generative artificial intelligence (AI) exhibits the capability to generate creative content akin to human output with greater efficiency and reduced costs. This groundbreaking capability, however, has ignited a debate regarding its potential to displace human creators. In light of these discussions, this paper empirically investigates the impact of generative AI on market equilibrium, in the context of China's leading art outsourcing platform. We overcome the challenge of causal inference by identifying an unanticipated and sudden leak of an advanced image-generative AI as a natural experiment. This leak precipitated a notable reduction in the production costs of anime-style images compared to other genres, thereby providing a unique opportunity for difference-in-differences comparisons. Our analysis shows that the advent of generative AI led to a 64% reduction in average prices, yet it simultaneously spurred a 121% increase in order volume and a 56% increase in overall revenue. This growth is primarily driven by the rising demand for "low-end" personal orders, rather than commercial orders. Moreover, incumbent creators retain the majority of the market share and reap the most benefits of generative AI. Our research highlights the potential of generative AI to benefit all stakeholders across the platform economy, yielding both scholarly contributions and practical implications.

Xiaoxin Dai, Lijun Qiu, Han Zhang et al.

The plasticizer bisphenol A, a typical endocrine disrupting chemical, is widely present in the environment. Previous studies demonstrated that exposure to bisphenol A can cause reproductive toxicity, abnormal fertilization, and infertility. However, the mechanisms of low-concentration bisphenol A on the reproductive system and treatment measures have not been fully determined. In this study, we explored the transcriptomic profiles of female zebrafish ovaries. The transcriptomic data revealed that mitochondrial NADH dehydrogenase (mt-Nd) genes were significantly decreased in the bisphenol A-exposed group, while the co-administration of tea polyphenols remarkably elevated the expression of mt-Nd genes. To further explore the expression pattern of the mt-Nd, we analyzed the expression of six mt-Nd genes on different days by qRT-PCR in control, bisphenol A-exposed, and bisphenol A-tea polyphenols ovaries. Here, we found that 0.1 mg/L bisphenol A exposure adversely affects the mitochondrial respiratory chain in ovaries and may lead to reproductive disorders. Finally, our study demonstrated that tea polyphenols play a protective role in ovarian mitochondrial dysfunction in low-concentration bisphenol A-exposed female zebrafish.

He Liping, Jian Ji

[Objective] The temporal and spatial variation characteristics of vegetation coverage in Sichuan Province from 2009 to 2020 were monitored and analyzed, in order to provide important basic research data for quantitative assessment of the regional ecological environment, and scientific references for urban planning and sustainable urban development. [Methods] Landsat images of Sichuan Province from 2009 to 2020 were acquired from the Google Earth Engine cloud computing platform, and the vegetation coverage area was quantitatively estimated by the binary pixel model. [Results] ① In the 11 years from 2009 to 2020, Sichuan Province was mainly dominated by high and medium high vegetation coverage, accounting for 80% of the province's area, while the proportion of low and medium low vegetation coverage was less than 10%. ② From the perspective of spatial distribution, the spatial difference of fractional vegetative cover (FVC) in Sichuan Province was obvious. The areas with low FVC were mainly located in the Chengdu Plain Economic Zone and some areas in Western Sichuan Province. ③ From the analysis of spatial change characteristics, FVC in the study area showed a basically stable trend (44.39%) from 2009 to 2020. The area of FVC improvement (30.78%) was larger than that of FVC degradation (24.82%), and the area of obvious degradation accounted for the least proportion (only 4.96% of the province's area). [Conclusion] On the whole, vegetation coverage in Sichuan Province from 2009 to 2020 was in good condition, mainly with high and medium high vegetation coverage. The vegetation coverage showed a basically stable trend. From 2009 to 2020, the area of Sichuan Province was mainly dominated by high and medium high FVC levels that accounted for 80% of the province's area, while the area of low and medium low FVC accounted for less than 10% of the area.

Luz A. deWit, Brendan Fisher, Robin Naidoo et al.

Abstract The wildlife trade drives biodiversity loss and zoonotic disease emergence, and the health and economic impacts of COVID‐19 have sparked discussions over stricter regulation of the wildlife trade. Yet regulation for conservation and health purposes is at odds with the economic incentives provided by this multibillion‐dollar industry. To understand why the wildlife trade persists despite associated biodiversity and global health threats, we used a benefit–cost approach using simple calculations to compare the economic benefits of the wildlife trade at the individual, national, and global scales to the costs of COVID‐19, severe acute respiratory syndrome (SARS), and Ebola disease across scenarios of epidemic frequency. For COVID‐19, benefits of the wildlife trade outweigh costs at individual scales, but costs far exceed benefits at national and global scales, particularly if epidemics were to become frequent. For SARS and Ebola, benefits outweigh costs at all scales, except if Ebola‐like epidemics were to become frequent. The wildlife trade produces net benefits for people who depend on wildlife for food and income but incurs net costs on stakeholders at larger scales from increased epidemic risk. While our analysis omits a variety of costs and benefits that are difficult to quantify and contrast, our analysis is meant to illustrate the distributional outcomes across stakeholder groups that could result from increased wildlife trade regulation. Importantly, the feasibility of trade regulatory policies will depend on how these benefits and costs compare across groups and would therefore need to involve accessible and attractive alternative sources of food and livelihoods for those who depend on the wildlife trade.

Young-Ho Kim, Sungdong Kim, Minsuk Chang et al.

Current natural language interaction for self-tracking tools largely depends on bespoke implementation optimized for a specific tracking theme and data format, which is neither generalizable nor scalable to a tremendous design space of self-tracking. However, training machine learning models in the context of self-tracking is challenging due to the wide variety of tracking topics and data formats. In this paper, we propose a novel NLP task for self-tracking that extracts close- and open-ended information from a retrospective activity log described as a plain text, and a domain-agnostic, GPT-3-based NLU framework that performs this task. The framework augments the prompt using synthetic samples to transform the task into 10-shot learning, to address a cold-start problem in bootstrapping a new tracking topic. Our preliminary evaluation suggests that our approach significantly outperforms the baseline QA models. Going further, we discuss future application domains toward which the NLP and HCI researchers can collaborate.

Liao Ouyang, Yan Liu, Huirong Chen et al.

Algicidal bacteria offer an eco-friendly and promising approach for controlling harmful algae blooms (HABs). In this study, repeated batch fermentation of immobilized algicidal bacterium Vibrio brasiliensis H115 was preformed to enhance the productivity of the algicidal compounds. The highest algicidal efficiency of the fermentation products against Akashiwo sanguinea (100%) was achieved when the fermentation time was decreased from 24 to 14 h. The cell-free fermentation broth was then spray-dried and floating microcapsules were prepared from the dried powder. The optimum preparation conditions for floating microcapsules were: sodium alginate (SA), 3%; CaCO3: SA (mass ratio), 3:4; CaCl2, 3%; citric acid, 4%; ethylcellulose, 2%; crosslinking time, 30 min. Under the optimal conditions, the floating microcapsules displayed efficient A. sanguinea cell lysis ability and the algicidal efficiency increased from 10.62% (4 h) to 100% (24 h). These results suggest that the floating microcapsules could potentially be practically used for controlling the outbreaks of A. sanguinea.

Ishana Shukla, A. Marm Kilpatrick, Roxanne S. Beltran

Abstract Mammals must carefully balance rest with other behaviors that influence fitness (e.g., foraging, finding a mate) while minimizing predation risk. However, factors influencing resting strategies and the degree to which resting strategies are driven by the activities of predators and/or prey remain largely unknown. Our goal was to examine how mammalian resting strategies varied with trophic level, body mass, and habitat. We reviewed findings from 127 publications and classified the resting strategies of terrestrial and aquatic mammalian species into three categories: social (e.g., resting in groups), temporal (e.g., resting during the day), or spatial (e.g., resting in burrows). Temporal strategies were most common (54% of cases), but the prevalence of strategies varied with body mass and among trophic levels. Specifically, lower trophic levels and smaller species such as rodents and lagomorphs used more spatial and social resting strategies, whereas top predators and larger species used mostly temporal resting strategies. Resting strategies also varied among habitat types (e.g., rainforest vs. grassland), but this was primarily because closely related species shared both habitats and resting strategies. Human presence also affected resting strategies at all trophic levels but most strongly influenced top predators through shifts in rest timing. Human‐induced behavioral changes in rest patterns cascade to modify behaviors across multiple trophic levels. These findings advance our fundamental understanding of natural history and ecology in wild animals and provide a roadmap for future comparative studies.

Vignav Ramesh, Anton Kolonin

Many current artificial general intelligence (AGI) and natural language processing (NLP) architectures do not possess general conversational intelligence--that is, they either do not deal with language or are unable to convey knowledge in a form similar to the human language without manual, labor-intensive methods such as template-based customization. In this paper, we propose a new technique to automatically generate grammatically valid sentences using the Link Grammar database. This natural language generation method far outperforms current state-of-the-art baselines and may serve as the final component in a proto-AGI question answering pipeline that understandably handles natural language material.

Donald Salisbury

The main focus is on the Hamilton-Jacobi techniques in classical general relativity that were pursued by Peter Bergmann and Arthur Komar in the 1960's and 1970's. They placed special emphasis on the ability to construct the factor group of canonical transformations, where the four-dimensional diffeomorphism phase space transformations were factored out. Equivalence classes were identified by a set of phase space functions that were invariant under the action of the four-dimensional diffeomorphism group. This is contrasted and compared with approaches of Paul Weiss, Julian Schwinger, Richard Arnowitt, Stanley Deser, Charles Misner, Karel Kuchar - and especially the geometrodynamical program of John Wheeler and Bryce DeWitt where diffeomorphism symmetry is replaced by a notion of multifingered time. The origins of all of these approaches are traced to Elie Cartan's invariant integral formulation of classical dynamics. A related correspondence concerning the thin sandwich dispute is also documented.

Changbiao Wang

The positive mass theorem in general relativity states that in an asymptotically flat spacetime, if the momentum--energy tensor is divergence-free and satisfies a dominant energy condition, then a total momentum--energy four-vector can be formed, of which the energy component is nonnegative. In this paper, we take the wave four-tensor of a plane light wave in free space as a counterexample to show that there is no guarantee that a total four-vector can be formed. Thus the theoretical framework for the positive mass theorem is flawed. In addition, it is also shown as well that the Lorentz covariance of Dirac wave equation is not compatible with Einstein mass--energy equivalence.

Silva, João Figueira, Almeida, João Rafael, Matos, Sérgio

BackgroundElectronic health records store large amounts of patient clinical data. Despite efforts to structure patient data, clinical notes containing rich patient information remain stored as free text, greatly limiting its exploitation. This includes family history, which is highly relevant for applications such as diagnosis and prognosis. ObjectiveThis study aims to develop automatic strategies for annotating family history information in clinical notes, focusing not only on the extraction of relevant entities such as family members and disease mentions but also on the extraction of relations between the identified entities. MethodsThis study extends a previous contribution for the 2019 track on family history extraction from national natural language processing clinical challenges by improving a previously developed rule-based engine, using deep learning (DL) approaches for the extraction of entities from clinical notes, and combining both approaches in a hybrid end-to-end system capable of successfully extracting family member and observation entities and the relations between those entities. Furthermore, this study analyzes the impact of factors such as the use of external resources and different types of embeddings in the performance of DL models. ResultsThe approaches developed were evaluated in a first task regarding entity extraction and in a second task concerning relation extraction. The proposed DL approach improved observation extraction, obtaining F1 scores of 0.8688 and 0.7907 in the training and test sets, respectively. However, DL approaches have limitations in the extraction of family members. The rule-based engine was adjusted to have higher generalizing capability and achieved family member extraction F1 scores of 0.8823 and 0.8092 in the training and test sets, respectively. The resulting hybrid system obtained F1 scores of 0.8743 and 0.7979 in the training and test sets, respectively. For the second task, the original evaluator was adjusted to perform a more exact evaluation than the original one, and the hybrid system obtained F1 scores of 0.6480 and 0.5082 in the training and test sets, respectively. ConclusionsWe evaluated the impact of several factors on the performance of DL models, and we present an end-to-end system for extracting family history information from clinical notes, which can help in the structuring and reuse of this type of information. The final hybrid solution is provided in a publicly available code repository.

Mariano Bonomo, Julio Cezar Rubin de Rubin

Los ríos de las Tierras Bajas han sido espacios claves para entender problemas suprarregionales de la antropología de América del Sur, tales como: el poblamiento americano, la cronología y dispersión de innovaciones tecnológico-culturales como la arquitectura en tierra, la alfarería o la agricultura de la mandioca y el maíz, las migraciones y expansiones de poblaciones indígenas y familias lingüísticas, la interacción de grupos cazadores-recolectores entre sí y con horticultores, el surgimiento de la complejidad social y las desigualdades hereditarias, entre otros. Teniendo en cuenta estos problemas generales, en el último World Archaeological Congress (WAC-8, Kyoto) surgió la idea de organizar este dossier entre el Instituto Goiano de Pré-História e Antropologia da Pontifícia Universidade Católica de Goiás y la División Arqueología del Museo de La Plata, Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata. Se sugirió a las autoras y los autores invitados abordar el estado del arte de las investigaciones arqueológicas en cada uno de los ríos o cuencas en las que trabajan, según algunos de los siguientes ejes: a) los procesos de formación de sitio y la transformación humana del paisaje fluvial; b) la existencia o no de adaptaciones fluviales; c) la caza, la pesca y la recolección: tecnologías originarias y estrategias de obtención de los recursos acuáticos. Los ríos en la producción agrícola; d) los ríos como marcadores de fronteras culturales y a la vez generadores de interacción social. Los ríos como vías naturales que guiaron la movilidad pedestre y la navegación y e) significados simbólicos y actividades rituales efectuadas en los ríos como, por ejemplo: áreas preferenciales para entierros humanos, los recursos acuáticos y la identidad de género, iconografía, entre otros temas. El presente dossier de la Revista del Museo de La Plata reúne catorce artículos que muestran el estado actual del conocimiento arqueológico en veinte ríos que han sido protagonistas  de la larga historia indígena de las Tierras Bajas sudamericanas (Figura 1). Estos cursos corren por ocho países: Colombia, Ecuador, Perú, Bolivia, Brasil, Paraguay, Uruguay y Argentina. En el volumen están representadas las dos mayores cuencas hidrográficas de América del Sur, la del Amazonas y la del Plata, que entre ambas abarcan más de diez millones de kilómetros cuadrados. Se aborda tanto la arqueología del río Amazonas, el más largo y caudaloso del mundo, como también la del Ribeira de Iguape, con dimensiones mucho menores. Se sintetiza la arqueología de ríos que, al atravesar cientos o miles de kilómetros generalmente sin grandes barreras físicas, funcionaron como activos corredores norte-sur-norte ?Araguaia, Tocantins, Paraguay, Paraná y Uruguay?, oeste-este-oeste ?Caquetá, Napo, Pastaza, Salado (de la provincia de Buenos Aires), Dulce, Salado (de Santiago del Estero), Pilcomayo y Bermejo? o en ambos sentidos como el Upano. Se incluyen cursos que surcan el norte tropical del continente, como el río Magdalena, hasta el sur frío y árido de la Patagonia, con los ríos Chubut, Negro y Colorado. A continuación se comentan los artículos contenidos en el dossier siguiendo un sentido, norte-sur/oeste-este.

The 'Oumuamua ISSI Team

The discovery of the first interstellar object passing through the Solar System, 1I/2017 U1 ('Oumuamua), provoked intense and continuing interest from the scientific community and the general public. The faintness of 'Oumuamua, together with the limited time window within which observations were possible, constrained the information available on its dynamics and physical state. Here we review our knowledge and find that in all cases the observations are consistent with a purely natural origin for 'Oumuamua. We discuss how the observed characteristics of 'Oumuamua are explained by our extensive knowledge of natural minor bodies in our Solar System and our current knowledge of the evolution of planetary systems. We highlight several areas requiring further investigation.

S. Forbes