A Satisfiability Modulo Theory Approach to Secure State Reconstruction in Differentially Flat Systems Under Sensor Attacks

We address the problem of estimating the state of a differentially flat system from measurements that may be corrupted by an adversarial attack. In cyber-physical systems, malicious attacks can directly compromise the system's sensors or manipulate the communication between sensors and controllers. We consider attacks that only corrupt a subset of sensor measurements. We show that the possibility of reconstructing the state under such attacks is characterized by a suitable generalization of the notion of s-sparse observability, previously introduced by some of the authors in the linear case. We also extend our previous work on the use of Satisfiability Modulo Theory solvers to estimate the state under sensor attacks to the context of differentially flat systems. The effectiveness of our approach is illustrated on the problem of controlling a quadrotor under sensor attacks.Comment: arXiv admin note: text overlap with arXiv:1412.432

In situ polymerization of soil organic matter by oxidative biomimetic catalysis.

Background: Agricultural practices that enhance organic matter content in soil can play a central role in sequestering soil organic carbon (SOC) and reducing greenhouse gases emissions. Methods: We used a water-soluble iron-porphyrin to catalyze directly in situ oxidative polymerization of soil organic matter in the presence of H2O2 oxidant, with the aim to enhance OC stabilization, and, consequently, reduce CO2 emissions from soil. The occurred SOC stabilization was assessed by monitoring soil aggregate stability, OC distribution in water-soluble aggregates, soil respiration, and extraction yields of humic and fulvic acids. Results: Soil treatment with H2O2 and iron-porphyrin increased the physical stability of water-stable soil aggregates and the total OC content in small aggregates, thereby suggesting that the catalyzed oxidative polymerization increased OC in soil and induced a soil physical improvement. The significant reduction of CO2 respired by the catalyst- and H2O2-treated soil indicated an enhanced resistance of polymerized SOC to microbial mineralization. The catalyzed oxidative polymerization of SOC also significantly decreased the extraction yields of humic and fulvic acids from soil. Conclusions: The oxidative catalytic technology described here may become an efficient agricultural practice for OC sequestration in soils and contribute to mitigate global changes

Autonomous Light Management in Flexible Photoelectrochromic Films Integrating High Performance Silicon Solar Microcells

Commercial smart window technologies for dynamic light and heat management in building and automotive environments traditionally rely on electrochromic (EC) materials powered by an external source. This design complicates building-scale installation requirements and substantially increases costs for applications in retrofit construction. Self-powered photoelectrochromic (PEC) windows are an intuitive alternative wherein a photovoltaic (PV) material is used to power the electrochromic device, which modulates the transmission of the incident solar flux. The PV component in this application must be sufficiently transparent and produce enough power to efficiently modulate the EC device transmission. Here, we propose Si solar microcells (μ-cells) that are i) small enough to be visually transparent to the eye, and ii) thin enough to enable flexible PEC devices. Visual transparency is achieved when Si μ-cells are arranged in high pitch (i.e. low-integration density) form factors while maintaining the advantages of a single-crystalline PV material (i.e., long lifetime and high performance). Additionally, the thin dimensions of these Si μ-cells enable fabrication on flexible substrates to realize these flexible PEC devices. The current work demonstrates this concept using WO₃ as the EC material and V₂O₅ as the ion storage layer, where each component is fabricated via sol-gel methods that afford improved prospects for scalability and tunability in comparison to thermal evaporation methods. The EC devices display fast switching times, as low as 8 seconds, with a modulation in transmission as high as 33%. Integration with two Si μ-cells in series (affording a 1.12 V output) demonstrates an integrated PEC module design with switching times of less than 3 minutes, and a modulation in transmission of 32% with an unprecedented EC:PV areal ratio

Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications

We address the problem of diagnosing and repairing specifications for hybrid systems formalized in signal temporal logic (STL). Our focus is on the setting of automatic synthesis of controllers in a model predictive control (MPC) framework. We build on recent approaches that reduce the controller synthesis problem to solving one or more mixed integer linear programs (MILPs), where infeasibility of a MILP usually indicates unrealizability of the controller synthesis problem. Given an infeasible STL synthesis problem, we present algorithms that provide feedback on the reasons for unrealizability, and suggestions for making it realizable. Our algorithms are sound and complete, i.e., they provide a correct diagnosis, and always terminate with a non-trivial specification that is feasible using the chosen synthesis method, when such a solution exists. We demonstrate the effectiveness of our approach on the synthesis of controllers for various cyber-physical systems, including an autonomous driving application and an aircraft electric power system

Inflammatory mediators as biomarkers in brain disorders.

Neurodegenerative diseases such as Alzheimer, Parkinson, amyotrophic lateral sclerosis, and Huntington are incurable and debilitating conditions that result in progressive death of the neurons. The definite diagnosis of a neurodegenerative disorder is disadvantaged by the difficulty in obtaining biopsies and thereby to validate the clinical diagnosis with pathological results. Biomarkers are valuable indicators for detecting different phases of a disease such as prevention, early onset, treatment, progression, and monitoring the effect of pharmacological responses to a therapeutic intervention. Inflammation occurs in neurodegenerative diseases, and identification and validation of molecules involved in this process could be a strategy for finding new biomarkers. The ideal inflammatory biomarker needs to be easily measurable, must be reproducible, not subject to wide variation in the population, and unaffected by external factors. Our review summarizes the most important inflammation biomarkers currently available, whose specificity could be utilized for identifying and monitoring distinctive phases of different neurodegenerative diseases

Micro-optical Tandem Luminescent Solar Concentrators

Traditional concentrating photovoltaic (CPV) systems utilize multijunction cells to minimize thermalization losses, but cannot efficiently capture diffuse sunlight, which contributes to a high levelized cost of energy (LCOE) and limits their use to geographical regions with high direct sunlight insolation. Luminescent solar concentrators (LSCs) harness light generated by luminophores embedded in a light-trapping waveguide to concentrate light onto smaller cells. LSCs can absorb both direct and diffuse sunlight, and thus can operate as flat plate receivers at a fixed tilt and with a conventional module form factor. However, current LSCs experience significant power loss through parasitic luminophore absorption and incomplete light trapping by the optical waveguide. Here we introduce a tandem LSC device architecture that overcomes both of these limitations, consisting of a PLMA polymer layer with embedded CdSe/CdS quantum dot (QD) luminophores and InGaP micro-cells, which serve as a high bandgap absorber on top of a conventional Si photovoltaic. We experimentally synthesize CdSe/CdS QDs with exceptionally high quantum-yield (99%) and ultra-narrowband emission optimally matched to fabricated III-V InGaP micro-cells. Using a Monte Carlo ray-tracing model, we show the radiative limit power conversion efficiency for a module with these components to be 30.8% diffuse sunlight conditions. These results indicate that a tandem LSC-on-Si architecture could significantly improve upon the efficiency of a conventional Si photovoltaic module with simple and straightforward alterations of the module lamination steps of a Si photovoltaic manufacturing process, with promise for widespread module deployment across diverse geographical regions and energy markets

A study of gas contaminants and interaction with materials in RPC closed loop systems

Resistive Plate Counters (RPC) detectors at the Large Hadron Collider (LHC) experiments use gas recirculation systems to cope with large gas mixture volumes and costs. In this paper a long-term systematic study about gas purifiers, gas contaminants and detector performance is discussed. The study aims at measuring the lifetime of purifiers with unused and used cartridge material along with contaminants release in the gas system. During the data-taking the response of several RPC double-gap detectors was monitored in order to characterize the correlation between dark currents, filter status and gas contaminants

Identification of subgroups of early breast cancer patients at high risk of nonadherence to adjuvant hormone therapy: results of an italian survey.

The aim of this study was the identification of subgroups of patients at higher risk of nonadherence to adjuvant hormone therapy for breast cancer. Using recursive partitioning and amalgamation (RECPAM) analysis, the highest risk was observed in the group of unmarried, employed women, or housewives. This result might be functional in designing tailored intervention studies aimed at improvement of adherence. Background: Adherence to adjuvant endocrine therapy (HT) is suboptimal among breast cancer patients. A high rate of nonadherence might explain differences in survival between clinical trial and clinical practice. Tailored interventions aimed at improving adherence can only be implemented if subgroups of patients at higher risk of poor adherence are identified. Because no data are available for Italy, we undertook a large survey on adherence among women taking adjuvant HT for breast cancer. Patients and Methods: Patients were recruited from 10 cancer clinics in central Italy. All patients taking HT for at least 1 year were invited, during one of their follow-up visit, to fill a confidential questionnaire. The association of sociodemographic and clinical characteristics of participants with adherence was assessed using logistic regression. The RECPAM method was used to evaluate interactions among variables and to identify subgroups of patients at different risk of nonadherence. Results: A total of 939 patients joined the study and 18.6% of them were classified as nonadherers. Among possible predictors, only age, working status, and switching from tamoxifen to an aromatase inhibitor were predictive of nonadherence in multivariate analysis. RECPAM analysis led to the identification of 4 classes of patients with a different likelihood of nonadherence to therapy, the lowest being observed in retired women with a low level of education, the highest in the group of unmarried, employed women, or housewives. Conclusion: The identification of these subgroups of “real life” patients with a high prevalence of nonadherers might be functional in designing intervention studies aimed at improving adherenc