Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

Embedded AM-FM Signal Decomposition Algorithm for Continuous Human Activity Monitoring

AM-FM decomposition techniques have been successfully used for extracting significative features from a large variety of signals, helping realtime signal monitoring and pattern recognition, since they represent signals as a simultaneous composition of amplitude modulation and frequency modulation, where the carriers, amplitude envelopes, and the instantaneous frequencies are the features to be estimated. Human activities often involve repetitive movements, such as in running or cycling, where sinusoidal AM-FM decompositions of signals have already demonstrated to be useful to extract compact features to aid monitoring, classification, or detection. In this work we thus present the challenges and results of implementing the iterated coherent Hilbert decomposition (ICHD), a particularly effective algorithm to obtain an AM-FM decomposition, within a resource-constrained and low-power ARM Cortex-M4 microcontroller that is present in a wearable sensor we developed. We apply ICHD to the gyroscope data acquired from an inertial measurement unit (IMU) that is present in the sensor. Optimizing the implementation allowed us to achieve real-time performance using less then 16 % of the available CPU time, while consuming only about 5.4 mW of power, which results in a run-time of over 7 days using a small 250 mAh rechargeable cell

Special Topics in Information Technology

This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

Duplex specific nuclease-amplified detection of microRNA using compact quantum dot-DNA conjugates

Advances in nanotechnology have provided new opportunities for the design of next-generation nucleic acid biosensors and diagnostics. Indeed, combining advances in functional nanoparticles, DNA nanotechnology, and nuclease-enzyme-based amplification can give rise to new assays with advantageous properties. In this work, we developed a microRNA (miRNA) assay using bright fluorescent quantum dots (QDs), simple DNA probes, and the enzyme duplex-specific nuclease. We employed an isothermal target-recycling mechanism, where a single miRNA target triggers the cleavage of many DNA signal probes. The incorporation of DNA-functionalized QDs enabled a quantitative fluorescent readout, mediated by Förster resonance energy transfer (FRET)-based interaction with the DNA signal probes. Our approach splits the reaction in two, performing the enzyme-mediated amplification and QD-based detection steps separately such that each reaction could be optimized for performance of the active components. Target recycling gave ca. 3 orders of magnitude amplification, yielding highly sensitive detection with a limit of 42 fM (or 1.2 amol) of miR-148, with excellent selectivity versus mismatched sequences and other miRNAs. Furthermore, we used an alternative target (miR-21) and FRET pair for direct and absolute quantification of miR-21 in RNA extracts from human cancer and normal cell lines

The fate of bone marrow-derived cells carrying a polycystic kidney disease mutation in the genetically normal kidney

Polycystic Kidney Disease (PKD) is a genetic condition in which dedifferentiated and highly proliferative epithelial cells form renal cysts and is frequently treated by renal transplantation. Studies have reported that bone marrow-derived cells give rise to renal epithelial cells, particularly following renal injury as often occurs during transplantation. This raises the possibility that bone marrow-derived cells from a PKD-afflicted recipient could populate a transplanted kidney and express a disease phenotype. However, for reasons that are not clear the reoccurrence of PKD has not been reported in a genetically normal renal graft. We used a mouse model to examine whether PKD mutant bone marrow-derived cells are capable of expressing a disease phenotype in the kidney

Macroporous silicon filters, a versatile platform for NDIR spectroscopic gas sensing in the MIR

© The Author(s) 2019. Published by ECS. This is an open access article distributed under the terms of the Creative CommonsAttribution 4.0 License (CC BY,http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse of the work in anymedium, provided the original work is properly cited.This paper describes the spectroscopic detection of gases using macroporous silicon photonic crystals as narrow filters. The study begins by demonstrating the feasibility of photoelectrochemical etching to fabricate narrow filters along the mid infrared band. Next, we focus on the filter centered on the carbon dioxide fingerprint. The filter response is described for three different cell lengths and concentrations below 1%. Results show a concordance with the reformulated Beer-Lambert law. This can be used to predict the response of the filter for longer path lengths and higher concentrations, showing broad working ranges and compact sizes for CO2. In addition, optical robustness to external variations and long-term stability are also reported. Results are extrapolated to other macroporous silicon filters centered on the absorption spectra of N2O, OCS, NO2 and SO2. Finally, high sensitivity and selectivity is demonstrated by comparing them with some commercial filters.Postprint (published version