The use of frameworks and components has been shown to be effective in improving software productivity and quality. However, the results in terms of reuse and standardization show a dearth of portability either of designs or of component-based implementations. This paper, which is based on the model driven software development paradigm, presents an approach that separates the description of component-based applications from their possible implementations for different platforms. This separation is supported by automatic integration of the code obtained from the input models into frameworks implemented using object-oriented technology. Thus, the approach combines the benefits of modeling applications from a higher level of abstraction than objects, with the higher levels of code reuse provided by frameworks. In order to illustrate the benefits of the proposed approach, two representative case studies that use both an existing framework and an ad hoc framework, are described. Finally, our approach is compared with other alternatives in terms of the cost of software development.
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http://dx.doi.org/10.1155/2014/687346 | DOI Listing |
Adv Sci (Weinh)
January 2025
DP Technology, Beijing, 100080, China.
Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse-grained level. The more difficult and important task of fine-grained crystal structure prediction from PXRD remains unaddressed.
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January 2025
PKUCare Lu'an Hospital, 046204, Shanxi, China.
Periodontitis, a common chronic inflammatory condition caused by bacteria, leads to loss of attachment, resorption of alveolar bone, and ultimately tooth loss. Therefore, reducing bacterial load and fostering alveolar bone regeneration are essential components in the treatment of periodontitis. In this study, we prepared smaller-sized Ag-Metal Organic Frameworks (Ag@MOF) and loaded with sodium alginate (Alg) hydrogel for periodontitis treatment.
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January 2025
College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
The scientific establishment of the Ecological Security Pattern (ESP) is crucial for fostering the synergistic development of ecological and recreational functions, thereby enhancing urban ecological protection, recreational development, and sustainable growth. This study aimed to propose a novel method of constructing ESP considering both ecological and recreational functions, and to reconstruct ESP by weighing the relationship between ecological protection and recreational development. Utilizing Fuzhou City as a case study, a comprehensive application of methodologies including Morphological Spatial Pattern Analysis (MSPA), landscape connectivity analysis, ArcGIS spatial analysis, social network analysis (SNA), and circuit theory is employed to develop both the ESP and the Recreational Spatial Pattern (RSP).
View Article and Find Full Text PDFEur Geriatr Med
January 2025
School of Medicine, Trinity College Dublin, Dublin, Ireland.
Purpose: As the global population of older adults rises, the United Nations Decade of Healthy Ageing (2021-2030) advocates for disease prevention, management, and enhancing overall wellbeing in older adults. We reviewed the MEDLINE literature under the MeSH term "music therapy" (MT), for its role in promoting healthy ageing.
Methods: A systematic search of the MEDLINE biomedical database (Ovid) was conducted using "MT" and "Ageing" as keywords, retrieving relevant full-text studies in English.
BioData Min
January 2025
School of Computer Science, Fudan University, Shanghai, China.
This survey explores the transformative impact of foundation models (FMs) in artificial intelligence, focusing on their integration with federated learning (FL) in biomedical research. Foundation models such as ChatGPT, LLaMa, and CLIP, which are trained on vast datasets through methods including unsupervised pretraining, self-supervised learning, instructed fine-tuning, and reinforcement learning from human feedback, represent significant advancements in machine learning. These models, with their ability to generate coherent text and realistic images, are crucial for biomedical applications that require processing diverse data forms such as clinical reports, diagnostic images, and multimodal patient interactions.
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