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Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.
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http://dx.doi.org/10.1111/2041-210X.13583 | DOI Listing |
Sci Prog
September 2025
School of International Finance and Trade, Shanghai International Studies University, Shanghai, China.
To explore the alleviating effect of digital supply chain finance (DSCF) on financing constraints experienced by small- and medium-sized enterprises (SMEs), with a view to promoting the digital transformation of enterprises. This observational study utilizes data from Chinese listed enterprises. The study's primary focus is on a selection of SRDI (abbreviation for "specialized, refined, distinctive, and innovative") enterprises in the electronics and machinery industries from 2013 to 2020.
View Article and Find Full Text PDFEcol Evol
September 2025
Department of Hydrobiology, Institute of Biology University of Szczecin Szczecin Poland.
Physical habitat gradients in small rivers and streams profoundly influence aquatic community structure. These ecosystems are critical for biodiversity conservation, serving as refugia and nurseries for numerous species. Effective freshwater conservation necessitates tailored strategies addressing specific anthropogenic pressures and each habitat type's unique geomorphological and hydrological characteristics.
View Article and Find Full Text PDFJ Control Release
September 2025
Jiangsu Key Laboratory of Druggability of Biopharmaceuticals, Department of Pharmaceutics, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, PR China. Electronic address:
The tumor microenvironment (TME) is a complex and dynamic ecosystem that significantly influences tumor progression, immune modulation, and therapeutic response. A key component of the TME is the tumor-associated microbiota, which has emerged as an important player in cancer biology, affecting tumor metastasis, immune evasion, and resistance to treatments. The recent advent of high-throughput sequencing technologies has revolutionized our understanding of the microbiome, revealing distinct microbial communities across various tumor types.
View Article and Find Full Text PDFbioRxiv
August 2025
Department of Computational Medicine and Biology, University of Michigan Medicine, Ann Arbor, MI 48109, USA.
With the increasing volume of biomedical experimental data, standardizing, sharing, and integrating heterogeneous experimental data across domains has become a major challenge. To address this challenge, we have developed an ontology-supported Study-Experiment-Assay (SEA) common data model (CDM), which includes 10 core and 3 auxiliary classes based on object-oriented modeling. SEA CDM uses interoperable ontologies for data standardization and knowledge inference.
View Article and Find Full Text PDFAnn Med
December 2025
Department of Urology, The Second Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, People's Republic of China.
Background: Bladder cancer (BLCA) is a prevalent malignancy with substantial consequences for patient health. This study aimed to elucidate the underlying mechanisms of BLCA through integrated multi-omics analysis.
Methods: Tumor and adjacent tissues from BLCA patients underwent transcriptomic, whole-exome sequencing, metabolomic, and intratumoral microbiome analyses.