| 1. |
- Di Fatta, G., et al.
(author)
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Preface
- 2011
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In: IEEE International Conference on Data Mining. Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). - 1550-4786. ; , s. xlviii-xlvix
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Journal article (peer-reviewed)
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| 2. |
- D’Aniello, G., et al.
(author)
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Situation Awareness in the Cloud-Edge Continuum
- 2024
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In: Lecture Notes on Data Engineering and Communications Technologies. - : Springer Science and Business Media Deutschland GmbH. ; , s. 307-316
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Book chapter (other academic/artistic)abstract
- Edge Computing is becoming a promising computing paradigm that addresses the limitations of cloud computing concerning latency, autonomy, and costs. To facilitate more intelligent applications made possible by the Edge Computing paradigm, it is essential to integrate intelligence and adaptability into devices located at the network’s edge. The paper explores the potential integration of Situation Awareness (SA) capabilities into the Cloud-Edge continuum. This integration aims to empower smarter applications while effectively managing challenges related to low latency, high autonomy, and cost-effective solutions. Within our illustrative example in healthcare, we showcase how the proposed SA cloud-edge continuum architecture enables efficient data processing and decision-making.
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| 3. |
- Fortino, V, et al.
(author)
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Biomarkers of nanomaterials hazard from multi-layer data
- 2022
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 3798-
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Journal article (peer-reviewed)abstract
- There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them in multiple independent datasets. We find that models based on combinations of omics-derived features and material intrinsic properties display significantly improved predictive accuracy as compared to physicochemical properties alone.
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| 7. |
- Federico, A, et al.
(author)
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The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis
- 2022
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In: Human genomics. - : Springer Science and Business Media LLC. - 1479-7364. ; 16:1, s. 62-
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Journal article (peer-reviewed)abstract
- In recent years, a growing interest in the characterization of the molecular basis of psoriasis has been observed. However, despite the availability of a large amount of molecular data, many pathogenic mechanisms of psoriasis are still poorly understood. In this study, we performed an integrated analysis of 23 public transcriptomic datasets encompassing both lesional and uninvolved skin samples from psoriasis patients. We defined comprehensive gene co-expression network models of psoriatic lesions and uninvolved skin. Moreover, we curated and exploited a wide range of functional information from multiple public sources in order to systematically annotate the inferred networks. The integrated analysis of transcriptomics data and co-expression networks highlighted genes that are frequently dysregulated and show aberrant patterns of connectivity in the psoriatic lesion compared with the unaffected skin. Our approach allowed us to also identify plausible, previously unknown, actors in the expression of the psoriasis phenotype. Finally, we characterized communities of co-expressed genes associated with relevant molecular functions and expression signatures of specific immune cell types associated with the psoriasis lesion. Overall, integrating experimental driven results with curated functional information from public repositories represents an efficient approach to empower knowledge generation about psoriasis and may be applicable to other complex diseases.
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| 8. |
- Lv, Zhihan, Dr. 1984-, et al.
(author)
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Behavioral Modeling and Prediction in Social Perception and Computing : A Survey
- 2023
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In: IEEE Transactions on Computational Social Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 2329-924X. ; 10:4, s. 2008-2021
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Journal article (peer-reviewed)abstract
- More data are generated through interaction between cyber space, physical space, and social space thanks to mobile network technology, giving birth to the so-called cyber–physical social intelligent ecosystem (C&P-SIE). This survey studies the development of physical social intelligence. First, it classifies and discusses the behavior modeling, learning, and adaptation applications of C&P-SIE from intelligent transportation, healthcare, public service, economy, and social networking. Then, it prospects the application of behavior modeling in the C&P-SIE from the perspectives of information security, data-driven techniques, and modeling learning under cooperative artificial intelligence technologies. The research provides a theoretical basis and new opportunities for the digital and intelligent development of smart cities and social systems. IEEE
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| 11. |
- Tranvik, Lars J., et al.
(author)
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Lakes and reservoirs as regulators of carbon cycling and climate
- 2009
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In: Limnology and Oceanography. - : Wiley. - 0024-3590 .- 1939-5590. ; 54:6:2, s. 2298-2314
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Research review (peer-reviewed)abstract
- We explore the role of lakes in carbon cycling and global climate, examine the mechanisms influencing carbon pools and transformations in lakes, and discuss how the metabolism of carbon in the inland waters is likely to change in response to climate. Furthermore, we project changes as global climate change in the abundance and spatial distribution of lakes in the biosphere, and we revise the estimate for the global extent of carbon transformation in inland waters. This synthesis demonstrates that the global annual emissions of carbon dioxide from inland waters to the atmosphere are similar in magnitude to the carbon dioxide uptake by the oceans and that the global burial of organic carbon in inland water sediments exceeds organic carbon sequestration on the ocean floor. The role of inland waters in global carbon cycling and climate forcing may be changed by human activities, including construction of impoundments, which accumulate large amounts of carbon in sediments and emit large amounts of methane to the atmosphere. Methane emissions are also expected from lakes on melting permafrost. The synthesis presented here indicates that (1) inland waters constitute a significant component of the global carbon cycle, (2) their contribution to this cycle has significantly changed as a result of human activities, and (3) they will continue to change in response to future climate change causing decreased as well as increased abundance of lakes as well as increases in the number of aquatic impoundments.
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| 12. |
- Zhang, H., et al.
(author)
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Low-Cost and Confidential ECG Acquisition Framework Using Compressed Sensing and Chaotic Systems for Wireless Body Area Network
- 2022
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In: IEEE journal of biomedical and health informatics. - : IEEE. - 2168-2194 .- 2168-2208. ; 26:12, s. 5783-5792
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Journal article (peer-reviewed)abstract
- Recent years have witnessed an increasing popularity of wireless body area network (WBAN), with which continuous collection of physiological signals can be conveniently performed for healthcare monitoring. Energy consumption is a critical issue because it directly affects the duration of the equipped sensors. In this paper, we propose a low-cost and confidential electrocardiogram (ECG) acquisition approach for WBAN. The compressed sensing (CS) is employed for low-cost signal acquisition, and its cryptographic features are exploited for promoting the framework's confidentiality. In particular, the RIPless measurement matrix is used to give CS the resistance against plaintext attack, while the first-order $\Sigma \Delta$ quantizer is employed to embed the cryptographic diffusion feature into the whole system. Two chaotic systems are employed for generating the required secret elements for the acquisition and encryption. Experiment results well demonstrate the signal reconstruction and security performance of the proposed framework.
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