A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Global scale investigation of cirrus clouds properties using active and passive sensors

A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts.

Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Solid state micro and nanopore sensors for single entity detection

A general description of the work presented in this thesis can be divided into three areas of interest: micropore fabrication, nanopore modification, and their applications. The first part of the thesis is related to the novel, reliable, cost-effective, potable, mass-productive, robust, and ease of use micropore flowcell that works based on the RPS technique. Based on our first goal, which was finding an alternate materials and processes that would shorten production times while lowering costs and improving signal quality, the polyimide film was used as a substrate to create precise pores by femtosecond laser, and the resulting current blockades of different sizes of the nanoparticles were recorded. Based on the results, the device can detecting nano-sized particles by changing the current level. The experimental and theoretical investigation, scanning electron microscopy, and focus ion beam were performed to explain the micropore's performance. The second goal was design and fabrication of a leak-free, easy-to-assemble, and portable polymethyl methacrylate flowcell for nanopore experiments. Here, ion current rectification was studied in our nanodevice. We showed a self-assembly-based, controllable, and monitorable in situ Poly(l-lysine)- g-poly(ethylene glycol) coating method under voltage-driven electrolyte flow and electrostatic interaction between nanopore walls and PLL backbones. Using designed nanopore flowcell and in situ monolayer PLL-g-PEG functionalized 20±4 nm SiN nanopores, we observed non-sticky α-1 anti-trypsin protein translocation. additionally, we could show the enhancement of translocation events through this non-sticky nanopore, and also, estimate the volume of the translocated protein. In this study, by comparing the AAT protein translocation results from functionalized and non-functionalized nanopore we demonstrated the 105 times dwell time reduction (31-0.59ms), 25% amplitude enhancement (0.24-0.3 nA), and 15 times event’s number increase (1-15events/s) after functionalization in 1×PBS at physiological pH. Also, the AAT protein volume was measured, close to the calculated AAT protein hydrodynamic volume and previous reports.

Temperature Variation Aware Energy Optimization in Heterogeneous MPSoCs

Thermal effects are rapidly gaining importance in nanometer heterogeneous integrated systems. Increased power density, coupled with spatio-temporal variability of chip workload, cause lateral and vertical temperature non-uniformities (variations) in the chip structure. The assumption of an uniform temperature for a large circuit leads to inaccurate determination of key design parameters. To improve design quality, we need precise estimation of temperature at detailed spatial resolution which is very computationally intensive. Consequently, thermal analysis of the designs needs to be done at multiple levels of granularity. To further investigate the flow of chip/package thermal analysis we exploit the Intel Single Chip Cloud Computer (SCC) and propose a methodology for calibration of SCC on-die temperature sensors. We also develop an infrastructure for online monitoring of SCC temperature sensor readings and SCC power consumption. Having the thermal simulation tool in hand, we propose MiMAPT, an approach for analyzing delay, power and temperature in digital integrated circuits. MiMAPT integrates seamlessly into industrial Front-end and Back-end chip design flows. It accounts for temperature non-uniformities and self-heating while performing analysis. Furthermore, we extend the temperature variation aware analysis of designs to 3D MPSoCs with Wide-I/O DRAM. We improve the DRAM refresh power by considering the lateral and vertical temperature variations in the 3D structure and adapting the per-DRAM-bank refresh period accordingly. We develop an advanced virtual platform which models the performance, power, and thermal behavior of a 3D-integrated MPSoC with Wide-I/O DRAMs in detail. Moving towards real-world multi-core heterogeneous SoC designs, a reconfigurable heterogeneous platform (ZYNQ) is exploited to further study the performance and energy efficiency of various CPU-accelerator data sharing methods in heterogeneous hardware architectures. A complete hardware accelerator featuring clusters of OpenRISC CPUs, with dynamic address remapping capability is built and verified on a real hardware.

Transport Properties and Novel Sensing Applications of Organic Semiconducting Crystals

The present thesis is focused on the study of Organic Semiconducting Single Crystals (OSSCs) and crystalline thin films. In particular solution-grown OSSC, e.g. 4-hdroxycyanobenzene (4HCB) have been characterized in view of their applications as novel sensors of X-rays, gamma-rays, alpha particles radiations and chemical sensors. In the field of ionizing radiation detection, organic semiconductors have been proposed so far mainly as indirect detectors, i.e. as scintillators or as photodiodes. I first study the performance of 4HCB single crystals as direct X-ray detector i.e. the direct photon conversion into an electrical signal, assessing that they can operate at room temperature and in atmosphere, showing a stable and linear response with increasing dose rate. A dedicated study of the collecting electrodes geometry, crystal thickness and interaction volume allowed us to maximize the charge collection efficiency and sensitivity, thus assessing how OSSCs perform at low operating voltages and offer a great potential in the development of novel ionizing radiation sensors. To better understand the processes generating the observed X-ray signal, a comparative study is presented on OSSCs based on several small-molecules: 1,5-dinitronaphthalene (DNN), 1,8-naphthaleneimide (NTI), Rubrene and TIPS-pentacene. In addition, the proof of principle of gamma-rays and alpha particles has been assessed for 4HCB single crystals. I have also carried out an investigation of the electrical response of OSSCs exposed to vapour of volatile molecules, polar and non-polar. The last chapter deals with rubrene, the highest performing molecular crystals for electronic applications. We present an investigation on high quality, millimeter-sized, crystalline thin films (10 – 100 nm thick) realized by exploiting organic molecular beam epitaxy on water-soluble substrates. Space-Charge-Limited Current (SCLC) and photocurrent spectroscopy measurements have been carried out. A thin film transistor was fabricated onto a Cytop® dielectric layer. The FET mobility exceeding 2 cm2/Vs, definitely assess the quality of RUB films.