Energy harvesting from hydroelectric systems for remote sensors

Hydroelectric systems are well-known for large scale power generation. However, there are virtually no studies on energy harvesting with these systems to produce tens or hundreds of milliwatts. The goal of this work was to study which design parameters from large-scale systems can be applied to small-scale systems. Two types of hydro turbines were evaluated. The first one was a Pelton turbine which is suitable for high heads and low flow rates. The second one was a propeller turbine used for low heads and high flow rates. Several turbine geometries and nozzle diameters were tested for the Pelton system. For the propeller, a three-bladed turbine was tested for different heads and draft tubes. The mechanical power provided by these turbines was measured to evaluate the range of efficiencies of these systems. A small three-phase generator was developed for coupling with the turbines in order to evaluate the generated electric power. Selected turbines were used to test battery charging with hydroelectric systems and a comparison between several efficiencies of the systems was made. Keywords

Efficient wireless coverage of in-building environments with low electromagnetic impact

The city of tomorrow is a major integrating stake, which crosses a set of major broad spectrum domains. One of these areas is the instrumentation of this city and the ubiquity of the exchange of data, which will give the pulse of this city (sensors) and its breathing in a hyper-connected world within indoor and outdoor dense areas (data exchange, 5G and 6G). Within this context, the proposed doctorate project has the objective to realize cost- and energy- effective, short-range communication systems for the capillary wireless coverage of in-door environments with low electromagnetic impact and for highly dense outdoor networks. The result will be reached through the combined use of: 1) Radio over Fiber (RoF) Technology, to bring the Radio Frequency (RF) signal to the different areas to be covered. 2) Beamforming antennas to send in real time the RF power just in the direction(s) where it is really necessary.

Design and characterization of wideband Hall current sensors in BCD technology for smart power and metering applications

Power electronic circuits are moving towards higher switching frequencies, exploiting the capabilities of novel devices to shrink the dimension of passive components. This trend demands sensors capable enough to operate at such high frequencies. This thesis aims to demonstrate through experimental characterization, the broadband capability of a fully integrated CMOS X-Hall current sensor in current mode interfaced with a transimpedance amplifier (TIA), chip CH09, realized in CMOS technology for power electronics applications such as power converters. The system exploits a common-mode control system to operate the dual supply system, 5-V for the X-Hall probe and 1.2-V for the readout. The developed prototype achieves a maximum acquisition bandwidth of 12 MHz, a power consumption of 11.46 mW, resolution of 39 mArms, a sensitivity of 8 % /T, and a FoM of 569-MHz/A2mW, significantly higher than current state-of-the-art. Further enhancements were proposed to CH09 as a new chip CH100, aiming for accuracy levels prerequisite for a real-time power electronic application. The TIA was optimized for a wider bandwidth of 26.7 MHz with nearly 30% reduction of the integrated input referred noise of 26.69 nArms at the probe-AFE interface in the frequency band of DC-30 MHz, and a 10% improvement in the dynamic range. The expected input range is 5-A. The chip incorporates a dual sensing chain for differential sensing to overcome common mode interferences. A novel offset cancellation technique is proposed that would require switching of polarity of bias currents. Thermal gain drift was improved by a factor of 8 and will be digitally calibrated utilizing a new built-in temperature sensor with a post calibration measurement accuracy greater than 1%. The estimated power consumption of the entire system is 55.6 mW. Both prototypes have been implemented through a 90-nm microelectronic process from STMicroelectronics and occupy a silicon area of 2.4 mm2.

Study of low grade temperature CCHP systems for the realization of zero power buildings

Combined Cooling Heat and Power Generation (CCHP) or trigeneration has been considered worldwide as a suitable alternative to traditional energy systems in terms of significant energy saving and environmental conservation. The development and evaluation of a solar driven micro-CCHP system based on a ORC cogenerator and an Adsorption Chiller (AC) experimental prototypes has been the focus of this PhD research. The specific objectives of the overall project are: • To design, construct and evaluate an innovative Adsorption Chiller in order to improve the performances of the AC technology. • To thermodynamically model the proposed micro-scale solar driven CHP system and to prove that the concept of trigeneration through solar energy combined with an organic Rankine turbine cycle (ORC) and an adsorption chiller (AC) is suitable for residential applications.

Efficient and low-computational predictive models for spectral sensors

Spectral sensors are a wide class of devices that are extremely useful for detecting essential information of the environment and materials with high degree of selectivity. Recently, they have achieved high degrees of integration and low implementation cost to be suited for fast, small, and non-invasive monitoring systems. However, the useful information is hidden in spectra and it is difficult to decode. So, mathematical algorithms are needed to infer the value of the variables of interest from the acquired data. Between the different families of predictive modeling, Principal Component Analysis and the techniques stemmed from it can provide very good performances, as well as small computational and memory requirements. For these reasons, they allow the implementation of the prediction even in embedded and autonomous devices. In this thesis, I will present 4 practical applications of these algorithms to the prediction of different variables: moisture of soil, moisture of concrete, freshness of anchovies/sardines, and concentration of gasses. In all of these cases, the workflow will be the same. Initially, an acquisition campaign was performed to acquire both spectra and the variables of interest from samples. Then these data are used as input for the creation of the prediction models, to solve both classification and regression problems. From these models, an array of calibration coefficients is derived and used for the implementation of the prediction in an embedded system. The presented results will show that this workflow was successfully applied to very different scientific fields, obtaining autonomous and non-invasive devices able to predict the value of physical parameters of choice from new spectral acquisitions.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

Burden Of Focal Cryoablation Versus Brachytherapy Versus Active Surveillance In The Treatment Of Very Low-risk Prostate Cancer: A Preliminary Head-to-head Comprehensive Assessment.

Focal cryoablation (FC), brachytherapy (B) and active surveillance (AS) were offered to patients diagnosed with very low-risk prostate cancer (VLRPC) in an equal access protocol. Comprehensive validated self-report questionnaires accessed patients' erectile (IIEF-5) and voiding (IPSS) functions, Beck scales measured anxiety (BAI), hopelessness (BHS) and depression (BDI), SF-36 reflected patients' quality of life added to the emotional thermometers including five visual analogue scales (distress, anxiety, depression, anger and need for help). Kruskal-Wallis or ANOVA tests and Spearman's correlations were obtained among groups and studied variables. Thirty patients were included, median follow-up 18 months (15-21). Those on AS (n = 11) were older, presented higher hopelessness (BHS) and lower general health perceptions (SF-36) scores than patients opting for FC (n = 10) and B (n = 9), P = 0.0014, P = 0.0268 and P = 0.0168 respectively. Patients on B had higher IPSS scores compared to those under FC and AC, P = 0.0223. For all 30 included patients, Spearman's correlation (rs ) was very strong between BHS and general health perceptions (rs  = -0.800, P < 0.0001), and weak/moderate between age and BHS (rs  = 0.405, P = 0.026) and age and general health perceptions (rs  = -0.564, P = 0.001). The sample power was >60%. To be considered in patients' counselling and care, current study supports the hypothesis that even VLRPC when untreated undermines psychosocial domains.

Tradução, adaptação cultural e validação do questionário Body image After Breast Cancer para a língua portuguesa do Brasil

Universidade Estadual de Campinas . Faculdade de Educação Física

Mensuração da potência mecânica em esforços de alta intensidade na condição laboratorial de corrida atada e na condição de campo em corrida semi-atada e livre

Universidade Estadual de Campinas . Faculdade de Educação Física

Decision theory applied to image quality control in radiology

Background: The present work aims at the application of the decision theory to radiological image quality control ( QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films. Methods: Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations. Results: Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center. Conclusion: The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.

Effects of Low-Level Laser Therapy on Pain and Scar Formation After Inguinal Herniation Surgery: A Randomized Controlled Single-Blind Study

Objective: The aim of this study was to investigate the efficacy of an infrared GaAlAs laser operating with a wavelength of 830 nm in the postsurgical scarring process after inguinal-hernia surgery. Background: Low-level laser therapy (LLLT) has been shown to be beneficial in the tissue-repair process, as previously demonstrated in tissue culture and animal experiments. However, there is lack of studies on the effects of LLLT on postsurgical scarring of incisions in humans using an infrared 830-nm GaAlAs laser. Method: Twenty-eight patients who underwent surgery for inguinal hernias were randomly divided into an experimental group (G1) and a control group (G2). G1 received LLLT, with the first application performed 24 h after surgery and then on days 3, 5, and 7. The incisions were irradiated with an 830-nm diode laser operating with a continuous power output of 40 mW, a spot-size aperture of 0.08 cm(2) for 26 s, energy per point of 1.04 J, and an energy density of 13 J/cm(2). Ten points per scar were irradiated. Six months after surgery, both groups were reevaluated using the Vancouver Scar Scale (VSS), the Visual Analog Scale, and measurement of the scar thickness. Results: G1 showed significantly better results in the VSS totals (2.14 +/- 1.51) compared with G2 (4.85 +/- 1.87); in the thickness measurements (0.11 cm) compared with G2 (0.19 cm); and in the malleability (0.14) compared with G2 (1.07). The pain score was also around 50% higher in G2. Conclusion: Infra-red LLLT (830 nm) applied after inguinal-hernia surgery was effective in preventing the formation of keloids. In addition, LLLT resulted in better scar appearance and quality 6 mo postsurgery.

Low-Level Laser Therapy on the Viability of Skin Flap in Rats Subjected to Deleterious Effect of Nicotine

Objective: The purpose of this study was to evaluate the effect of 830-nm laser in blocking the action of nicotine on the viability of skin flap. Background data: The authors have analyzed the deleterious effect of cigarette smoke or nicotine on the skin flap alone with evidence of increased skin necrosis in the flap. Materials and methods: Twenty-four Wistar-albino rats were divided into three groups of eight animals each: Group 1 (control), subjected to a surgical technique to obtain a flap for cranial base, laser irradiation simulation, and a subcutaneous injection of saline; Group 2, similar to Group 1, with subcutaneous injection of nicotine (2mg/kg/day) for a period of 1 week before and 1 week after surgery; and Group 3, similar to Group 2, with skin flaps subjected to a lambda 830-nm laser irradiation. The laser parameters used were: power 30 mW, beam area 0.07cm(2), irradiance 429 mW/cm(2), irradiation time 84 sec, total energy 2.52J, and energy density 36J/cm(2). The laser was used immediately after surgery and for 4 consecutive days, in one point at 2.5 cm of the flap cranial base. The areas of necrosis were examined by two macroscopic analyses: paper template and Mini-Mop (R). The pervious blood vessels were also counted. Results: The results were statistically analyzed by ANOVA and post-test contrast orthogonal method (multiple comparisons), showing that the laser decreased the area of necrosis in flaps subjected to nicotine, and consequently, increased the number of blood vessels (p < 0.05). Conclusions: The laser proved to be an effective way to decrease the area of necrosis in rats subjected to nicotine, making them similar to the control group.

Differential expression of HIF-1 alpha in CD44(+)CD24(-/) (low) breast ductal carcinomas

Background: Cancer stem cell (CSC) hypothesis postulates that tumors are maintained by a self-renewing CSC population that is also capable of differentiating into non-self-renewing cell populations that constitute the bulk of tumor. Stem cells renewal and differentiation can be directly influenced by the oxygen levels of determined tissues, probably by the reduction of oxidative DNA damage in hypoxic regions, thus leading to a friendlier microenvironment, regarding to clonal expansion and for resistance to chemotherapeutic regimens. Furthermore, there have been strong data indicating a pivotal role of hypoxic niche in cancer stem cells development. There are evidence that hypoxia could drive the maintenance of CSC, via HIF-1 alpha expression, but it still to be determined whether hypoxia markers are expressed in breast tumors presenting CD44(+)CD24(-/low) immunophenotype. Methods: Immunohistochemical analysis of CD44(+)CD24(-/low) expression and its relationship with hypoxia markers and clinical outcome were evaluated in 253 samples of breast ductal carcinomas. Double-immunolabeling was performed using EnVision Doublestain System (Dako, Carpinteria, CA, USA). Slides were then scanned into high-resolution images using Aperio ScanScope XT and then, visualized in the software Image Scope (Aperio, Vista, CA, USA). Results: In univariate analysis, CD44(+)CD24(-/low) expression showed association with death due to breast cancer (p = 0.035). Breast tumors expressing CD44(+)CD24(-/low) immunophenotype showed relationship with HIF-1 alpha (p = 0.039) and negativity for HER-2 (p = 0.013). Conclusion: Considering that there are strong evidences that the fraction of a tumour considered to be cancer stem cells is plastic depending upon microenvironmental signals, our findings provide further evidence that hypoxia might be related to the worse prognosis found in CD44(+)CD24(-/low) positive breast tumors.

Low-Level Laser Therapy in Burning Mouth Syndrome Patients: A Pilot Study

Objective: The aim of this study was to investigate the effect of low-level laser therapy (LLLT) on the treatment of burning mouth syndrome (BMS). In addition, the laser effect was compared on the different affected oral sites. Materials and Methods: Eleven subjects with a total of 25 sites (tongue, lower lip, upper lip, and palate) affected by a burning sensation were selected. The affected areas were irradiated once a week for three consecutive weeks with an infrared laser (lambda = 790 nm). The probe was kept in contact with the tissue, and the mucosal surface was scanned during the irradiation. The exposure time was calculated based on the fluence of 6 J/cm(2), the output power of 120 mW, and the area to be treated. Burning intensity was recorded through a visual analog scale before and after the treatment and at the 6-week follow-up. The percentage of the improvement in symptoms was also obtained. Results: Burning intensity at the end of the laser therapy was statistically lower than at the beginning (p < 0.01). Patients reported an 80.4% reduction in the intensity of symptoms after laser treatment. There was no statistical difference between the end of the treatment and the 6-week follow-up, except for the tongue site. Conclusion: Under the investigated parameters, infrared LLLT proved to be a valuable alternative for BMS treatment, providing a significant and lasting reduction in symptoms.