An ellipsoidal off-line MPC scheme for uncertain polytopic discrete-time systems

An off-line Model Predictive Control (MPC) method based on ellipsoidal calculus and viability theory is described in order to address control problems in the presence of state and input constraints for uncertain polytopic linear plants subject to persistent disturbances. In order to reduce the computational burdens and conservativeness of traditional polytopic MPC schemes, the present approach carries out off-line most of the computations and it makes use of closed-loop predictions to improve the control performance. This is done by recursively pre-computing suitable ellipsoidal inner approximations of the exact controllable sets and solving on-line a simple and numerically low-demanding optimization problem subject to a set-membership constraint. Comparisons with three other recent off-line MPC approaches are also provided in the final example.     

H∞ generalized minimum sensitivity control design

This paper presents a two-stage approach to the H_∞ generalized sensitivity minimization problem (H_∞-GSM) for SISO, continuous-time plants. Besides some possible advantages in the control law evaluation with respect to alternative polynomial methods, the proposed approach provides a direct link with the solution of an underlying generalized minimum variance (H₂-GMV) problem and allows one to identify the class of the joint H₂/H_∞-GMV (equalizing H₂-GMV) optimal controllers.     

A Network Protocol Stack in Standard ML

The FoxNet is an implementation of the standard TCP/IP networking protocol stack using the Standard ML (SML) language. SML is a type-safe programming language with garbage collection, a unique and advanced module system, and machine-independent semantics. The FoxNet is a user-space implementation of TCP/IP that is built in SML by composing modular protocol elements; each element independently implements one of the standard protocols. One specific combination of these elements implements the standard TCP/IP stack. Other combinations are also possible and can be used to easily and conveniently build custom, non-standard networking stacks. This paper describes in detail the final design and implementation of the FoxNet, including many of the details that are crucially affected by the choice of SML as the programming language.     

Role of miRNA-19a in Cancer Diagnosis and Poor Prognosis

Cancer is a multifactorial disease that affects millions of people every year and is one of the most common causes of death in the world. The high mortality rate is very often linked to late diagnosis; in fact, nowadays there are a lack of efficient and specific markers for the early diagnosis and prognosis of cancer. In recent years, the discovery of new diagnostic markers, including microRNAs (miRNAs), has been an important turning point for cancer research. miRNAs are small, endogenous, non-coding RNAs that regulate gene expression. Compelling evidence has showed that many miRNAs are aberrantly expressed in human carcinomas and can act with either tumor-promoting or tumor-suppressing functions. miR-19a is one of the most investigated miRNAs, whose dysregulated expression is involved in different types of tumors and has been potentially associated with the prognosis of cancer patients. The aim of this review is to investigate the role of miR-19a in cancer, highlighting its involvement in cell proliferation, cell growth, cell death, tissue invasion and migration, as well as in angiogenesis. On these bases, miR-19a could prove to be truly useful as a potential diagnostic, prognostic, and therapeutic marker.     

Lung Microbiome in Idiopathic Pulmonary Fibrosis and Other Interstitial Lung Diseases

Interstitial lung diseases represent a heterogeneous and wide group of diseases in which factors leading to disease initiation and progression are not fully understood. Recent evidence suggests that the lung microbiome might influence the pathogenesis and progression of interstitial lung diseases. In recent years, the utilization of culture-independent methodologies has allowed the identification of complex and dynamic communities of microbes, in patients with interstitial lung diseases. However, the potential mechanisms by which these changes may drive disease pathogenesis and progression are largely unknown. The aim of this review is to discuss the role of the altered lung microbiome in several interstitial lung diseases. Untangling the host–microbiome interaction in the lung and airway of interstitial lung disease patients is a research priority. Thus, lung dysbiosis is a potentially treatable trait across several interstitial lung diseases, and its proper characterization and treatment might be crucial to change the natural history of these diseases and improve outcomes.     

Preferential CO oxidation over Pt/3A zeolite catalysts in H2-rich gas for fuel cell application

Even traces of CO in the hydrogen-rich gas fed to proton exchange membrane fuel cells (PEMFC) poison the platinum anode electrode and dramatically decrease the cell power output. In this work, several 1%Pt catalysts, all on 3A-type zeolite support, were prepared starting from different precursors and employing different methods: cation exchange (CE), wet impregnation (WI) and incipient wetness impregnation (IWI). The catalysts were characterised in terms of platinum dispersion and tested under realistic conditions in the quest of a catalyst for the removal of CO via the CO preferential oxidation (CO-PROX) reaction. The best catalytic performance was shown by the 1%Pt–3A catalyst prepared by IWI starting from Pt(NH₃)₄Cl₂ as a precursor, thanks to its highest platinum dispersion.     

Radio planning and coverage optimization of 3G cellular networks

Radio planning and coverage optimization are critical issues for service providers and vendors that are deploying third generation mobile networks and need to control coverage as well as the huge costs involved. Due to the peculiarities of the Code Division Multiple Access (CDMA) scheme used in 3G cellular systems like UMTS and CDMA2000, network planning cannot be based only on signal predictions, and the approach relying on classical set covering formulations adopted for second generation systems is not appropriate. In this paper we investigate mathematical programming models for supporting the decisions on where to install new base stations and how to select their configuration (antenna height and tilt, sector orientations, maximum emission power, pilot signal, etc.) so as to find a trade-off between maximizing coverage and minimizing costs. The overall model takes into account signal-quality constraints in both uplink and downlink directions, as well as the power control mechanism and the pilot signal. Since even small and simplified instances of this NP-hard problem are beyond the reach of state-of-the-art techniques for mixed integer programming, we propose a Tabu Search algorithm which provides good solutions within a reasonable computing time. Computational results obtained for realistic instances, generated according to classical propagation models, with different traffic scenarios (voice and data) are reported and discussed. Preliminary results have been presented in [5, 7, 8]. This work has been supported by the “Progetto Cofinanziato 2001–2003” of the Italian Ministry of Education, University and Scientific Research (MIUR), Optimization models and methods for telecommunication network design and management. Edoardo Amaldi received the “Diplome” in Mathematical Engineering from the Swiss Federal Institute of Technology at Lausanne (EPFL) in 1988. After one year in the Computational and Neural Systems program, California Institute of Technology, USA, he came back at EPFL where he earned the “Doctoratés Sciences” (PhD) in October 1994. He then joined the School of Operations Research and Industrial Engineering, Cornell University, USA, where he did research and taught graduate courses in mathematical programming. Since 1998 he is with the Dipartimento di Elettronica e Informazione (DEI), Politecnico di Milano, Italy, where he is currently an Associate Professor in Operations Research. His main research interests are in discrete optimization, the design and analysis of algorithms, and computational complexity with applications in telecommunications, image/signal processing, machine learning, and computational biology/finance. In 2005 he received an IBM Faculty Award for his work on the maximum feasible subsystem problem. He serves on the Program Committees of several international workshops and conferences (including the European Symposium on Algorithms, International Network Optimization Conference, International Workshop on Efficient and Experimental Algorithms–WEA) and since 2005 he is on the Steering Committee of WEA. Antonio Capone is an Associate Professor at the Dipartimento di Elettronica e Informazione of the Technical University of Milan (Politecnico di Milano). His expertise is on networking and main research activities include protocol design (MAC and routing) and performance evaluation of wireless access and multi-hop networks, traffic management and quality of service issues in IP networks, and network planning and optimization. He received the M.S. and Ph.D. degrees in electrical engineering from the Politecnico di Milano in 1994 and 1998, respectively. In 2000 he was a visiting professor at UCLA, Computer Science department. He currently serves as editor of the Wiley Journal of Wireless Communications and Mobile Computing. He served in the technical program committee of several international conferences and he is a regular reviewer of the main journals in the networking area. He is currently involved in the scientific and technical activities of several national and European research projects, and he leads several industrial projects. He is a Senior Member of the IEEE. Federico Malucelli (Ferrara, 7/4/62) got a Laurea in Computer Science and Ph.D. in Computer Science both from Universita’ di Pisa in 1988 and 1993 respectively. Since 2003 he is full professor of Operations Research at the Politecnico di Milano. In 1998–2002 he was associate professor of Operations Research at the Politecnico of Milano, and from 1992 to 1998 research associate at Pisa and Perugia Universities. He has visited several foreign universities and research laboratories, including HP Laboratories, Palo Alto (USA), Universite’ de Montreal (Canada) and Linkoping Universitet (Sweden). He has served as research unit coordinator for several nationwide MIUR and CNR research projects on optimization in telecommunications networks and transportation systems. His main research interests include: models and algorithms for combinatorial optimization problems, with applications in particular to telecommunications, transportations, logistics, and electronic circuit design. He has published more than 30 articles on international scietific journals.     

Artificial Cilia–Bridging the Gap with Nature

Human ingenuity has found a multitude of ways to manipulate fluids across different applications. However, the fundamentals of fluid propulsion change when moving from the macro- to the microscale. Viscous forces dominate inertial forces rendering successful methods at the macroscale ineffective for microscale fluid propulsion. Nature however has found a solution; microscopic active organelles protruding from cells that feature intricate beating patterns: cilia. Cilia succeed in propelling fluids at small dimensions; hence they have served as a source of inspiration for microfluidic applications. Mimicking biological cilia however remains challenging due to their small size and the required kinematic complexity. Recent advances have pushed artificial cilia technology forward, yet discrepancies with natural cilia still exists. This study identifies this gap by analyzing artificial cilia technology and benchmarking them to natural cilia, to pinpoint the remaining design and manufacturing challenges that lay at the basis of the disparity with nature.     

A LoRa-based protocol for connecting IoT edge computing nodes to provide small-data-based services

Data is becoming increasingly personal. Individuals regularly interact with a variety of structured data, ranging from SQLite databases on the phone to personal sensors and open government data. The “digital traces left by individuals through these interactions” are sometimes referred to as “small data”. Examples of “small data” include driving records, biometric measurements, search histories, weather forecasts and usage alerts. In this paper, we present a flexible protocol called LoRaCTP, which is based on LoRa technology that allows data “chunks” to be transferred over large distances with very low energy expenditure. LoRaCTP provides all the mechanisms necessary to make LoRa transfer reliable by introducing a lightweight connection setup and allowing the ideal sending of an as-long-as necessary data message. We designed this protocol as communication support for small-data edge-based IoT solutions, given its stability, low power usage, and the possibility to cover long distances. We evaluated our protocol using various data content sizes and communication distances to demonstrate its performance and reliability.