Hasil untuk "Plant culture"

S. Mante

H. Hammond, H. Street

Erin van Liemt, Renee Shelby, Andrew Smart et al.

There is a lack of empirical evidence about global attitudes around whether and how GenAI should represent cultures. This paper assesses understandings and beliefs about culture as it relates to GenAI from a large-scale global survey. We gathered data about what culture means to different groups, and about how GenAI should approach the representation of cultural artifacts, concepts, or values. We distill working definitions of culture directly from these communities to build an understanding of its conceptual complexities and how they relate to representations in Generative AI. We survey from across parts of Europe, North and South America, Asia, and Africa. We conclude with a set of recommendations for Culture and GenAI development. These include participatory approaches, prioritizing specific cultural dimensions beyond geography, such as religion and tradition, and a sensitivity framework for addressing cultural ``redlines''.

Jian Li, He-Nan Bao, Ke-Yu Li et al.

The rose, often referred to as the queen of flowers, is one of the four primary cut flowers; however, its growth is susceptible to high-temperature stress. Furthermore, with the advent of global warming, extreme high temperatures are becoming increasingly frequent, presenting significant challenges to the normal growth of roses. High temperatures have emerged as a limiting factor in rose cultivation. In this study, transcriptomics combined with lipid determination was employed to reveal that high temperatures resulted in a significant enrichment of genes within the α-linolenic acid metabolic pathway. Subsequent lipid determination analyses indicated that, following high-temperature treatment of the rose variety 'Hi-Ohgi', the content of α-linolenic acid increased, while there was a notable decrease in the content of the chloroplast lipid components monogalactosyldiacylglycerol (MGDG) and digalactosyldiacylglycerol (DGDG), alongside an increase in jasmonic acid content. In comparison to the heat-susceptible variety 'Scarlet Bonica', the heat-resistant rose variety 'Hi-Ohgi' exhibited lower levels of MGDG and DGDG, but higher levels of α-linolenic acid and jasmonic acid, with this trend becoming more pronounced under high-temperature conditions. Additionally, pretreatment of suspension cells from 'Scarlet Bonica' with α-linolenic acid or jasmonic acid significantly inhibited the burst of reactive oxygen species induced by high temperatures. This suggests that roses enhance the production of α-linolenic acid and jasmonic acid through lipid remodeling as a response to high-temperature stress. This research provides a theoretical foundation and precise targets for the cultivation of heat-resistant rose varieties.

J. Reinert, Y. Bajaj

Hadrien Oliveri, Christophe Godin, Ibrahim Cheddadi

Plant morphogenesis relies on dynamic growth deformations at the cell and tissue scales driven by osmotic fluxes. A mechanistic understanding of this phenomenon demands a physical framework that integrates cell imbibition, tissue mechanics, and water fluxes, as well as their biophysical and molecular regulations, within a theory of plant active matter capturing the open-system and out-of-equilibrium properties of tissues. Building on historical insights into growth geometry, physics, and mechanics, combined with recent experimental results, we outline the key challenges in modelling plant growth and propose steps towards a unified physical theory of plant morphogenesis, in which biological regulation, mechanical forces, and water fluxes interact to shape biological form through the fundamental principles of living matter.

Herve Goeau, Alexis Joly, Pierre Bonnet et al.

The LifeCLEFs plant identification task provides a testbed for a system-oriented evaluation of plant identification about 500 species trees and herbaceous plants. Seven types of image content are considered: scan and scan-like pictures of leaf, and 6 kinds of detailed views with unconstrained conditions, directly photographed on the plant: flower, fruit, stem & bark, branch, leaf and entire view. The main originality of this data is that it was specifically built through a citizen sciences initiative conducted by Tela Botanica, a French social network of amateur and expert botanists. This makes the task closer to the conditions of a real-world application. This overview presents more precisely the resources and assessments of task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results. With a total of ten groups from six countries and with a total of twenty seven submitted runs, involving distinct and original methods, this fourth year task confirms Image & Multimedia Retrieval community interest for biodiversity and botany, and highlights further challenging studies in plant identification.

Yen-hsuan Tseng

This paper presents a comprehensive analysis of power plant performance using the inverse Gaussian (IG) distribution framework. We combine theoretical foundations with practical applications, focusing on both combined cycle and nuclear power plant contexts. The study demonstrates the advantages of the IG distribution in modeling right-skewed industrial data, particularly in power generation. Using the UCI Combined Cycle Power Plant Dataset, we establishthe superiority of IG-based models over traditional approaches through rigorous statistical testing and model validation. The methodology developed here extends naturally to nuclear power plant applications, where similar statistical patterns emerge in operational data. Our findings suggest that IG-based models provide more accurate predictions and better capture the underlying physical processes in power generation systems.

Konstantinos Bertsouklis, Eireni Dima, Konstantina-Stamatina Arfani et al.

Employing rare or threatened species in ornamental horticulture offers a dual benefit by promoting climate adaptation and enhancing species conservation. <i>Kosteletzkya pentacarpos</i>, an endangered halophytic species, holds potential for introduction into the nursery industry, but efficient propagation methods are lacking. The present study investigated the in vitro propagation of the species using nodal explants excised from aseptic seedlings. A two-stage in vitro culture system was tested with thidiazuron (TDZ) promoting shoot initiation at low concentrations, while higher levels induced callus formation. Transferring micro-shoots to hormone free-, Murashige and Skoog medium (MS) promoted the highest shoot multiplication and elongation. The effect of sodium chloride (NaCl) on in vitro culture was also assessed, with MS media containing up to 5.0 g L⁻¹ NaCl supporting successful culture establishment. Spontaneous rooting was observed during various stages of the culture process. Micro-shoots were rooted at 100.0% on half strength MS medium with or without indole-3-butyric acid, and all plantlets were successfully acclimatized in a peat–perlite substrate (1/1, <i>v</i>/<i>v</i>). Thus, the present protocol provides an efficient system for the large-scale propagation of <i>K. pentacarpos</i> serving as a valuable tool for its conservation and the potential use in the nursery industry.

Valentina Alberti, Cinzia Cocco, Sergio Consoli et al.

Cultural gems is a web application conceived by the European Commission's Joint Research Centre (DG JRC), which aims at engaging people and organisations across Europe to create a unique repository of cultural and creative places. The main goal is to provide a vision of European culture in order to strengthen a sense of identity within a single European cultural realm. Cultural gems maps more than 130,000 physical places in over 300 European cities and towns, and since 2020 it also lists online cultural initiatives. The new release aims, among other, to increase the interoperability of the application. At this purpose, we provide an overview on the current development of an ontology for Cultural gems used to map cultural heritage in European cities by using Linked Open Data (LOD) standards, and making the data FAIR, that is Findable, Accessible, Interoperable, and Reusable. We provide an overview of the methodology, presenting the structure of the ontology, and the services and tools we are currently building on top.

Mohamed Debbagh, Yixue Liu, Zhouzhou Zheng et al.

A plant growth simulation can be characterized as a reconstructed visual representation of a plant or plant system. The phenotypic characteristics and plant structures are controlled by the scene environment and other contextual attributes. Considering the temporal dependencies and compounding effects of various factors on growth trajectories, we formulate a probabilistic approach to the simulation task by solving a frame synthesis and pattern recognition problem. We introduce a sequence-informed plant growth simulation framework (SI-PGS) that employs a conditional generative model to implicitly learn a distribution of possible plant representations within a dynamic scene from a fusion of low-dimensional temporal sensor and context data. Methods such as controlled latent sampling and recurrent output connections are used to improve coherence in the plant structures between frames of prediction. In this work, we demonstrate that SI-PGS is able to capture temporal dependencies and continuously generate realistic frames of plant growth.

Hadrien Oliveri, Derek E. Moulton, Heather A. Harrington et al.

Plants are a paradigm for active shape control in response to stimuli. For instance, it is well-known that a tilted plant will eventually straighten vertically, demonstrating the influence of both an external stimulus, gravity, and an internal stimulus, proprioception. These effects can be modulated when a potted plant is additionally rotated along the plant's axis, as in a rotating clinostat, leading to intricate shapes. We use a morphoelastic model for the response of growing plants to study the joint effect of both stimuli at all rotation speeds. In the absence of rotation, we identify a universal planar shape towards which all shoots eventually converge. With rotation, we demonstrate the existence of a stable family of three-dimensional dynamic equilibria where the plant axis is fixed in space. Further, the effect of axial growth is to induce steady behaviors, such as solitary waves. Overall, this study offers new insight into the complex out-of-equilibrium dynamics of a plant in three dimensions and further establishes that internal stimuli in active materials are key for robust shape control.

Natalie Violetta Frank, Maria Eletta Negretti, Joel Sommeria et al.

The physical growth of wind energy over several decades, caused a re-investigation mesoscale effects on wind plant dynamics. At a large scale operation, understanding the interactions between atmospheric phenomena and wind plant wakes is crucial to improving models. Within a wind plant, wakes are generated by individual turbines and the summation of individual wakes is the global plant wake. In both cases, the dynamics are sensitive to atmospheric conditions; one of interest to wind and atmospheric scientists is the Coriolis force. Current research noted spatial and temporal influences on the global plant wakes caused by the Coriolis force. Due to the presence of wind veer in the atmospheric boundary layer, field research is notoriously difficult. As a result, investigations have been lead by numerical simulations. This proved helpful for initial queries, established the significance of the Coriolis force as a non trivial parameter of wind plant dynamics. This works presents a novel experimental study of the impact of the Coriolis force on the dynamics of a scaled wind plant. The experiments show that for a single turbine the wake deflection is insignificant. Additionally, the results show that the global plant wake deflects in the anti-clockwise direction in the Northern hemisphere. The outcomes of this work yield unique experimental methods for research in wind energy, and provide a new basis for the fundamental dynamics of a wind plant under influence of the Coriolis force for future wind plant models causing influence on the global expansion of wind energy.

Bingshuai Liu, Longyue Wang, Chenyang Lyu et al.

One challenge in text-to-image (T2I) generation is the inadvertent reflection of culture gaps present in the training data, which signifies the disparity in generated image quality when the cultural elements of the input text are rarely collected in the training set. Although various T2I models have shown impressive but arbitrary examples, there is no benchmark to systematically evaluate a T2I model's ability to generate cross-cultural images. To bridge the gap, we propose a Challenging Cross-Cultural (C3) benchmark with comprehensive evaluation criteria, which can assess how well-suited a model is to a target culture. By analyzing the flawed images generated by the Stable Diffusion model on the C3 benchmark, we find that the model often fails to generate certain cultural objects. Accordingly, we propose a novel multi-modal metric that considers object-text alignment to filter the fine-tuning data in the target culture, which is used to fine-tune a T2I model to improve cross-cultural generation. Experimental results show that our multi-modal metric provides stronger data selection performance on the C3 benchmark than existing metrics, in which the object-text alignment is crucial. We release the benchmark, data, code, and generated images to facilitate future research on culturally diverse T2I generation (https://github.com/longyuewangdcu/C3-Bench).

Abdul Sittar, Dunja Mladenic

We present a methodology to support the analysis of culture from text such as news events and demonstrate its usefulness on categorizing news events from different categories (society, business, health, recreation, science, shopping, sports, arts, computers, games and home) across different geographical locations (different places in 117 countries). We group countries based on the culture that they follow and then filter the news events based on their content category. The news events are automatically labelled with the help of Hofstedes cultural dimensions. We present combinations of events across different categories and check the performances of different classification methods. We also presents experimental comparison of different number of features in order to find a suitable set to represent the culture.

Yeeun Kang, Kwanuk Lee, Ken Hoshikawa et al.

The effects of the climate change including an increase in the average global temperatures, and abnormal weather events such as frequent and severe heatwaves are emerging as a worldwide ecological concern due to their impacts on plant vegetation and crop productivity. In this review, the molecular processes of plants in response to heat stress—from the sensing of heat stress, the subsequent molecular cascades associated with the activation of heat shock factors and their primary targets (heat shock proteins), to the cellular responses—have been summarized with an emphasis on the classification and functions of heat shock proteins. Vegetables contain many essential vitamins, minerals, antioxidants, and fibers that provide many critical health benefits to humans. The adverse effects of heat stress on vegetable growth can be alleviated by developing vegetable crops with enhanced thermotolerance with the aid of various genetic tools. To achieve this goal, a solid understanding of the molecular and/or cellular mechanisms underlying various responses of vegetables to high temperature is imperative. Therefore, efforts to identify heat stress-responsive genes including those that code for heat shock factors and heat shock proteins, their functional roles in vegetable crops, and also their application to developing vegetables tolerant to heat stress are discussed.

Uno Fang, Jianxin Li, Xuequan Lu et al.

Current annotation for plant disease images depends on manual sorting and handcrafted features by agricultural experts, which is time-consuming and labour-intensive. In this paper, we propose a self-supervised clustering framework for grouping plant disease images based on the vulnerability of Kernel K-means. The main idea is to establish a cross iterative under-clustering algorithm based on Kernel K-means to produce the pseudo-labeled training set and a chaotic cluster to be further classified by a deep learning module. In order to verify the effectiveness of our proposed framework, we conduct extensive experiments on three different plant disease datatsets with five plants and 17 plant diseases. The experimental results show the high superiority of our method to do image-based plant disease classification over balanced and unbalanced datasets by comparing with five state-of-the-art existing works in terms of different metrics.

E. C. Tredenick, G. D. Farquhar

Food production needs to increase significantly in 30 years, and water loss from plants may hold one key, especially relevant in a time of climate change. The plant leaf cuticle is the final defence of leaves in drought and at night, and so by understanding water movement in the leaf with mathematical modelling techniques, we can move towards future proofing our crops and native plant ecology. We identify new mechanisms of water movement properties of plant cuticles and utilise this understanding to create a novel mathematical model. We model water sorption in astomatous isolated cuticles, utilising three separate pathways of cellulose, aqueous pores and lipophilic. The results of the model compare well to data both over time and increasing humidity. The sensitivity analysis shows that the grouping of parameters influencing plant species variations has the largest effect on sorption, the parameters influencing cellulose are very influential, and aqueous pores less so but still relevant. Cellulose is important to include in a water transport model for plant cuticles, as it plays a significant role in diffusion and adsorption in the cuticle and the cuticle surfaces.

Ratna Sariyatun, Florence, Hiroyuki Kajiura et al.

Plant cell cultures have emerged as a promising platform for the production of biopharmaceutics due to their cost-effectiveness, safety, ability to control the cultivation, and secrete products into culture medium. However, the use of this platform is hindered by the generation of plant-specific N-glycans, the inability to produce essential N-glycans for cellular delivery of biopharmaceutics, and low productivity. In this study, an alternative acid-alpha glucosidase (GAA) for enzyme replacement therapy of Pompe disease was produced in a glycoengineered Arabidopsis alg3 cell culture. The N-glycan composition of the GAA consisted of a predominantly paucimannosidic structure, Man3GlcNAc2 (M3), without the plant-specific N-glycans. Supplementing the culture medium with NaCl to a final concentration of 50 mM successfully increased GAA production by 3.8-fold. GAA from an NaCl-supplemented culture showed a similar N-glycan profile, indicating that the NaCl supplementation did not affect N-glycosylation. The results of this study highlight the feasibility of using a glycoengineered plant cell culture to produce recombinant proteins for which M3 or mannose receptor-mediated delivery is desired.

T. Gaspar, C. Kevers, C. Penel et al.