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Polymer-derived ceramic aerogels as sorbent materials for the removal of organic dyes from aqueous solutions
No full textCorrelation of elastic and mechanical properties of consolidated granular media during microstructure evolution induced by damage and repair
No full textEvolving cracks in consolidated granular media cause a modification of the microstructure in the area surrounding the damaged zone. As a consequence, the mechanical properties (flexural strength) and the elastic characteristics (linear modulus and nonlinear parameters) change as well. The same happens during repair, which could be considered as the symmetric counterpart of mechanical damaging. Starting from ultrasonicmeasurements of the resonance and nonlinear properties of concrete prisms during progression of damage and repair, we propose a description of the microstructure evolution, which allows to predict the observed phenomenology. Also, we demonstrate the existence of a correlation between ultrasonic elastic parameters and mechanical properties of the samples at each damage/repair state, pointing out symmetries and differences observed in the two processe
The Autogram: An effective approach for selecting the optimal demodulation band in rolling element bearings diagnosis
No full textEnvelope analysis is one of the most advantageous methods for rolling element bearing diagnostics but finding a suitable frequency band for demodulation has been a substantial challenge for a long time. Introduction of the Spectral Kurtosis (SK) and Kurtogram mostly solved this problem but in situations where signal to noise ratio is very low or in presence of non-Gaussian noise these methods will fail. This major drawback may noticeably decrease their effectiveness and goal of this paper is to overcome this problem. Vibration signals from rolling element bearings exhibit high levels of second-order cyclostationarity, especially in the presence of localized faults. The autocovariance function of a 2nd order cyclostationary signal is periodic and the proposed method, named Autogram, takes advantage of this property to enhance the conventional Kurtogram. The method computes the kurtosis of the unbiased Autocorrelation (AC) of the squared envelope of the demodulated signal, rather than the kurtosis of the filtered time signal. Moreover, to take advantage of unique features of the lower and upper portions of the AC, two modified forms of kurtosis are introduced and the resulting colormaps are called Upper and Lower Autogram. In addition, a thresholding method is also proposed to enhance the quality of the frequency spectrum analysis. A new indicator, Combined Squared Envelope Spectrum, is employed to consider all the frequency bands with valuable diagnostic information and to improve the fault detectability of the Autogram. The proposed method is tested on experimental data and compared with literature results so to assess its performances in rolling element bearing diagnostics
Bloch surface wave enhanced biosensor for the direct detection of Angiopoietin-2 tumor biomarker in human plasma
No full textPromoting TOD through regional planning. A comparative analysis of two European approaches
No full textInternet of Things Applications and Artificial Neural Networks in Smart Agriculture
No full textInternet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex systems and it is becoming a great tool to acquire data from particular environment to the cloud. Data that are acquired from Wireless Sensor Nodes(WSN) could be predicted using Artificial Neural Network(ANN) models. One of the use case fields of IoT is smart agriculture and there are still issues on developing low cost and power efficient WSN using advanced radio technologies for short and long-range applications and implementation of prediction tools. This is the reason why the target of this thesis is to develop a low cost and power efficient WSN and IoT based control system and analyze the best predictive model for such systems. With this purpose, we developed BLESensor node for short-range IoT applications and Internet of Plant(IoP) for long distance smart agriculture applications. A non-linear prediction model is developed in order to forecast acquired data from sensor nodes. BLESensor node Experimental test results reveal that newly developed BLESensor node has a good impact on the improved lifetime and applications could possibly make this emerging technological area more useful. The Android software has been tested on Samsung Galaxy SM-T311, running Android 4.4.2 and it works without any issues and it is supposed to work on all other Android devices equipped with BLE. The working temperature range of the BLESensor node is supposed to work goes from -20 °C to 70 °C due to battery temperature limits. The system has been tested in the climatic chamber (Challenge 250 from Angelantoni) present at the Neuronica Lab, which allowed the sensor to be software calibrated. Several measurements have been proven that each node offers an uncertainty of 1.2 °C for temperature. These values are acceptable for the type of application for which they are intended. The power consumption has been measured directly from scope analysis and simulating the code step by step and calculations resulted that the lifetime of the node lasts for a month. Considering a normal use of these sensors with a reasonable sampling time the lifetime could be increased. IoP node IoP node is a prototype device that works with WiFi protocol and collects temperature, humidity and soil moisture data of plants to the cloud. For IoP node, we have implemented a firmware, tested a prototype device and designed the PCB in OrCAD software and generated a Gerber file and developed an android application. Prediction model Comparisonofthreenon-linearmodelswithOakdatasetresultedinbetterperformance of NNARX model and we used NNARX model to predict 10 days step ahead maximum and minimum temperature and described the results of performances. The performance given by trained models in terms of Mean Square Error (MSE) for maximum temperature prediction provided an error of 0.8826 on unseen data for the month of September. Similarly, the performance of model predicting minimum temperature was tested and it resulted in an error value of 0.944. In conclusion, this work must be intended only as a proof-of-concept, although, the developed BLESensor system, IoP prototype device and predictive models showed expected optimum results, both in terms of functionalities and usability
Keratin Based Material For Perspective Bio-Application
No full textKeratin has natural characteristic for applying in biomaterial field as a biocompatible matrix like tissue regeneration, proliferation, and cell adhesion or drug career in the shape of microcapsules or microsphere. Because of the amino acid inherent structure, keratin extraction needs to be well designed to meet the particular requirement for applying in desired applications such as integrate with different molecules, drug releases, wound healing or biocompatible film. Keratinous sources such as wool, feathers are valuable by-products that abundantly present in nature. Although wool has valuable material in especially in textile industry, massive amount of low-grade wool cannot be utilized in textile and inevitably end up as a waste stream. Because of high cystine content of keratin, solubilization and extraction of keratin is a problematic process compared with other natural polymers such as collagen and chitosan. Using keratin in different level especially in large-scale requires understanding final properties of keratin which is strongly depends on producing procedure.. The interest towards drug career and microcapsules based on non-toxic, biodegradable and biocompatible polymers, such as proteins, is increasing considerably. In this work, keratin from wool fibers was extracted with oxidation, reduction, sulfitolysis, and superheated water hydrolysis methods. The effect of each method on obtained keratin properties are discussed and particularly reported how each extracted keratin influenced by the extraction process. In particular, all different samples of extracted keratin were characterized by molecular weight determination, FT-IR and NIR spectroscopy, amino acid analysis, and thermal behavior and the archived data were compared with reporting of previous studies with the emphasis of advantage and limitation of each extraction method. In the other part of the study, special attention are given to produce microcapsule and film from keratin-based material in line with biomaterial application. Microcapsules were prepared using water-soluble keratin, known as keratoses, with the aim of encapsulating hydrophilic molecules. The obtained keratin via oxidizing extraction of pristine wool, were utilized as shell part of the microcapsules which produced by sonication method. Production of the microcapsules was carried out by a sonication method. The microencapsulation and dye encapsulation yields were obtained by UV-spectroscopy. In addition, morphological structure of microcapsules was studied by light microscopy, SEM, and AFM and thermal properties of microcapsules were investigated by DSC. The molecular weights of proteins analyzed with gel-electrophoresis indicates the extracted keratoses has suitable molecular weight range for bio-application, and also the results confirmed that the hydrophilic dye (Telon Blue) was introduced inside the keratoses shells. The final microcapsules diameter ranged from 0.5 to 4 µm. One part of the experimental work is dedicated to producing keratin blend film with polyvinyl alcohol (PVA). PVA has been chosen because of its biocompatible and biodegradable properties which make this polymer as a promising candidate in the bio-field area. Blend of Polyvinyl alcohol (PVA) and keratoses were prepared with the aim of producing bio-compatible material proper for film and fiber structure mainly to improve the mechanical properties of obtained keratoses. Aqueous solution of keratoses and PVA was prepared for solution casting method. Blended films were characterized by, SEM, FT-IR spectroscopy and Differential scanning colorimetry and tensile properties
Assessing urban quality: a proposal for a MCDA evaluation framework
No full textThe paper focuses on the assessment of urban design quality and sustainable urban spaces. In particular, the study is concentrated on the evaluation of urban quality provided by a good design of open spaces, including green areas, walkable areas and squares. In fact, despite the advancement of research during the past two decades and empirical evidence about the relationship among quality of life, quality of open spaces and urban sustainability, there is still a lack of studies on urban quality assessment. This paper brings forward a multidimensional methodology for assessing the quality of open spaces. More precisely, the contribution of this research is the proposal of a multidimensional and multi-methodological framework for assigning a numerical score to the quality of open spaces. The Multi-Attribute Value Theory has been used for addressing the problem under investigation with the aim of defining a synthetic index for the measurement of the urban quality of open spaces on the basis of different attributes, namely (a) accessibility; (b) liveability; (c) vitality and (d) identity. The methodology has been applied on a recently renovated district in the city of Milan, Italy. The proposed multi-methodological framework provides a robust basis for running different kind of analysis and for supporting policy and investment decisions both in the private and in the public sector
