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Global warming is reducing food availability in many aquatic systems, raising questions about the combined effects of higher temperatures and lower food availability on fish life histories. In ectotherms, higher temperatures accelerate growth and promote an earlier onset of reproduction. However, when fish have less food during development, resource depletion might constrain these temperature-driven processes. We investigated how water temperature (24 or 28°C) and early-life food availability (control or restricted) affected adult life-history traits in female guppies (Poecilia reticulata).

Research data related to the ​​Department of Psychology of the University of Milano - Bicocca

AttiFood Picture Database

Synthetic nanobodies—also called sybodies—have proven valuable for stabilizing conformations of purified proteins, advancing structural and functional studies for example of transmembrane protein complexes. However, their utility in modulating protein function in living cells has remained less well explored. Structural Maintenance of Chromosomes (SMC) complexes facilitate chromosome organization by DNA loop extrusion, a fundamental process in all domains of life. In this study, we target the bacterial SMC complex, Smc-ScpAB, in Bacillus subtilis with synthetic nanobodies, with the aim to identify key functional regions of the protein complex in a largely unbiased manner. We first isolate sybodies that specifically bind purified Smc-ScpAB and then express them in B. subtilis to select binders capable of disrupting Smc-ScpAB function, leading to chromosome segregation defects and cell death. Mapping and biochemical characterization show that the fourteen disruptive sybodies belong to one of three library designs, target the Smc subunit near the same coiled coil arm interface and modulate its ATPase activity in two principal ways, highlighting the mid-region of Smc coiled coil as critical feature of the DNA folding process. These findings underscore the potential of sybodies—and, by extension, designed binders—as versatile tools for probing dynamic protein function in living cells, with potentially broad applications in cell and synthetic biology.

Este conjunto de dados acompanha a tese de doutorado “O periodismo científico no Brasil do século XIX: o caso d’O Auxiliador da Indústria Nacional”, que investiga o papel dos periódicos científicos na circulação de saberes, na construção da nação e na formulação de políticas públicas durante o Império do Brasil. A tese tem como objetivo geral estudar O Auxiliador da Indústria Nacional e, por meio dele, analisar o principal meio de comunicação científica de massa do período: o periodismo científico. A partir desses aspectos peculiares, o objetivo geral deste trabalho é estudar o periódico e, por meio dele, analisar o principal meio de comunicação científica de massa do período no Brasil: o periodismo científico. Três hipóteses específicas orientam a investigação: a primeira é a de que o periódico integrou o fenômeno transnacional do periodismo científico oitocentista, caracterizando-se como uma publicação institucional, profissional e científica; a segunda propõe que a publicação exerceu uma dupla função na dinâmica política do Brasil oitocentista, sendo ao mesmo tempo instrumentalizada pelo Governo Imperial como ferramenta de modernização da agricultura e utilizada pela associação como meio de influência sobre as políticas públicas; e a terceira sustenta que o periódico foi amplamente dependente de conteúdos técnicos e científicos produzidos em outros contextos, especialmente estrangeiros. Os resultados revelam que o periódico desempenhou um papel fundamental na articulação de uma visão de progresso nacional atrelada à agricultura, ao trabalho livre e à política pública, embora enfrentasse limitações institucionais, restrições orçamentárias e uma redução progressiva das trocas internacionais. O conjunto de dados permite a outros pesquisadores explorar padrões de política editorial, estrutura institucional e discurso científico no Brasil oitocentista. O conjunto inclui quatro arquivos em formato Excel: (1) uma indexação e classificação de mais de 6.000 artigos publicados no periódico O Auxiliador da Indústria Nacional, cobrindo o período de 1833 até 1892, com edições extras em 1896 e 1903; (2) a composição do conselho administrativo e das comissões técnicas da Sociedade Auxiliadora da Indústria Nacional, entre 1831 e 1904; (3) dados orçamentários e de balanço da associação, de 1839 a 1892; (4) listas de associados publicadas entre 1838 e 1877; (5) histórico do financiamento do Governo Imperial para a Sociedade Auxiliadora da Indústria Nacional, entre 1838 e 1906. Os dados acima foram coletados a partir da digitalização das edições do periódico disponíveis em bibliotecas e acervos físicos e digitais. Todos os arquivos estão disponíveis em formato .xlsx e podem ser abertos com softwares de planilha.

The data inventory (Data_HI2) includes harmonized data at 0.25 degree resolution for human interventions encompassing reservoirs, irrigation, inter-basin water transfers, and water supply for municipal, industrial, and thermoelectric cooling. The inventory would be updated periodically as more data on human interventions becomes available. This dataset also includes all code used to set-up, run, and evaluate the large-scale hydrological models described in 'A Diagnostic Framework and Data Inventory to Analyze Human Intervention on Streamflow' Commented code is provided with serial numbers in the root folder. Running the code in order from 1 to 25 will create files in the "Processed_Data" and "Results" folders. Files in the "Processed_Data" folder are in .rda format for efficient access in R. "Functions" contains all the functions that would be required by code in the root folder. Scripts to prepare figures describing the study area and supplementary results are also included; file names for these scripts begin with "S" Raw Data from sources mentioned in 'A Diagnostic Framework and Data Inventory to Analyze Human Intervention on Streamflow' must be downloaded and stored in a folder named "Raw_Data" prior to running code included in this dataset.

Figure 1. Flow diagram outlines the identification, screening, and inclusion of studies in the literature review, following PRISMA guidelines.

This dataset is a comprehensive collection of Bottle Gourd, Zucchini, and Papaya leaf disease images, developed at Daffodil International University, Dhaka, Bangladesh, to support research in machine learning, deep learning, and computer vision–based plant disease detection. A total of 2,144 original leaf images were collected from local agricultural fields and university research plots under natural lighting conditions between January 13, 2024, and October 22, 2024. All images were captured using smartphone and DSLR cameras and standardized to a resolution of 512 × 512 pixels in RGB format. The dataset covers multiple disease categories across three crops: Bottle Gourd (Alternaria Leaf Blight, Angular Leaf Spot, Anthracnose, Downy Mildew, Early Alternaria Leaf Blight, Fungal Damage, Healthy, and Mosaic Virus), Zucchini (Angular Leaf Spot, Anthracnose, Downy Mildew, Dry Leaf, Healthy, Insect Damage, Iron Chlorosis Damage, Xanthomonas Leaf Spot, and Yellow Mosaic Virus), and Papaya (Bacterial Blight, Carica Insect Hole, Curled Yellow Spot, Healthy Leaf, Pathogen Symptoms, and Yellow Necrotic Spots). To improve class balance and model generalization, extensive data augmentation techniques—such as rotation, flipping, brightness and contrast adjustment, zooming, and cropping—were applied, expanding the dataset to 23,000 augmented images. Each image preserves distinct disease features, making it highly suitable for training and testing machine learning and deep learning models for plant disease classification, detection, and recognition. This dataset serves as a valuable resource for advancing research in precision agriculture, smart farming, and AI-based crop health monitoring, and is freely available for academic and research purposes with proper acknowledgment to the creators and Daffodil International University.

This dataset contains high-resolution images of sunflower plants (Helianthus annuus), collected from Daffodil Smart City, Bangladesh. The sunflower is an economically important crop globally, valued for its edible oil, seeds, and ecological contributions. Accurate monitoring of sunflower plant health and growth stages is vital for optimizing agricultural yield, enhancing crop management practices, and supporting precision farming technologies. The primary purpose of this dataset is to facilitate machine learning and deep learning-based classification, detection, and monitoring of various growth stages and general health conditions of sunflower plants. Unlike disease detection datasets, this collection focuses on capturing the natural developmental phases and health states of sunflowers under normal growth environments. The dataset is organized into five visually distinct classes representing key growth stages and health conditions: EarlyBloom (1055 images) Healthy (1199 images) MatureBud (827 images) Wilted (1023 images) YoungBud (1009 images) Total Images: 5,113 Image Details: Original Resolution: 3000 × 4000 pixels Compressed Resolution: 560 × 420 pixels Image Format: jpg

Overview. The following is a database of experimental results for solution spun CNT fibers, provided by Rice University (Prof. Matteo Pasquali’s group) and Dexmat. Each tab represents a different experiment or physical property, as detailed below in a table of contents. In general, there are cryogenic measurements where 4-wire resistance, specific conductivity anisotropy, and Hall voltage are measured as a function of temperature, magnetic field strength, and magnetic field angle. This is primarily accomplished with our physical property measurement system (PPMS) at Wright Patterson AFB in Dayton Ohio were the lowest temperature possible was 1.9 K and maximum magnetic field was 9 T. We received supplemental measurements for high magnetic field (up to 60 T) al the National High Magnetic Field Laboratory at Los Alamos National Laboratory (LANL) and particularly low temperature (<65 mK) at the University of California Santa Barbra (Prof. Stefan Wilson’s group). In addition to cryogenic measurements, we included room temperature measurements of density, specific conductivity, conductivity, and aspect ratio of CNT materials. While peripheral to this study, we have also included a Raman database to include the raw spectra as well as specific Raman metrics. Finally, there are tabs that show 1) the numerical fits of cryogenic MR data to various transport models; 2) correlation tables of various material properties; 3) and a referenced compendium of applicable MR transport mechanisms in literature.