Patterning molecular scale paramagnets at Au Surface: A root to Magneto-Molecular-Electronics

Few examples of the exploitation of molecular magnetic properties in molecular electronics are known to date. Here we propose the realization of Self assembled monolayers (SAM) of a particular stable organic radical. This radical is meant to be used as a standard molecule on which to prove the validity of a single spin reading procedure known as ESR-STM. We also discuss a range of possible applications, further than ESR-STM, of magnetic monolayers of simple purely organic magnetic molecule.Comment: This preprint is currently partially under revisio

Old Age and Aerobic Microorganisms of Patients Affected by Clostridium difficile Infection are Associated Primarily with the Intestinal Presence of Clostridium difficile

Clostridium difficile infection in human occurs when the organism is present and germinating in the bowel. Old age of patients\u2019 and particular microorganisms in stools are identified as risk factors for the disease onset. We aimed to investigate if risk factors for C. difficile infections in a large Italian hospital were connected to C. difficile intestinal presence or to germination. Toxin B positivity was linked with age over 65 years (P=0.03), medical hospitalization (P=0.015) and growth of Enterobacteriaceae (P=0.029) and Enterococcus (P=0.05) from the same stools. The presence of tcdB was even more strictly linked with old age (P=0.005), medicine hospitalization (P=0.012) and growth of Enterobacteriaceae (P=0.003) and Enterococcus (P=0.04). Our results indicated that the presence of C. difficile in stools, irrespective of being spore or vegetative form, is reliably associated with old age of subjects and fecal presence of viable Enterobacteriaceae and Enterococcus

Effect of vine vigour of Vitis vinifera cv. Nebbiolo clones on wine acidity and quality

The grapevine cv. Nebbiolo grown in northern Italy produces high-quality red wines, of which Barolo and Barbaresco are the best known. During a clonal selection project, clones of this variety were assessed for their agronomical and enological value. Different degrees of vegetative vigour were found among them, and this was related to modifications of must and wine composition, with particular respect to the acidity. Over 4 years of observations, vigorous clones produced musts and wines of higher pH, regardless of the amount of titratable acidity. This was associated with a higher malic acid content in the juice and with a higher concentration of potassium in the wine. In addition, wines from vigorous clones showed an unbalanced ratio of colour components. They ranked at the lowest score in the sensory evaluation tests

On-Street Parking Search Time Estimation Using FCD Data

Abstract This paper focuses on modelling on-street parking search time by using FCD data coming from probe vehicles. It is based on data detected by probe vehicles, which allow to identify the typical spiral around the destination that vehicles perform in the final part of the trip to find a parking place. The proposed model is suitable to be used either in real-time to support user information and dynamic routing, or off-line for a better assessment of transport plans. A real-size application to the city of Rome is presented to show the promising results obtained for the estimation of parking search time in urban areas

Patterned monolayers of nitronyl nitroxide radicals

We report here the results of the preliminary characterization of the monolayer obtained both by self-assembling and microcontact printing of a di-alkyl sulfide nitronyl nitroxide derivative, 11-decyl sulfanyl-undecanyl nitronyl nitroxide of which we describe the synthesis. The sulfide unit has been introduced in order to allow the grafting of the molecule to the gold surface as well as to improve the stability of the organic radical with respect to different grafting agents like thiols, whereas the two long alkyl chains have been introduced to enhance the packing order of the molecules in a self assembled monolayer structure. X-band ESR was used to demonstrate the persistence of the paramagnetic character of the radical in the self-assembled monolayers, and to study its relatively large mobility. The microcontact printed monolayer was characterized by AFM, suggesting a non-negligible mobility of the molecules on the surfaces and a strong tilting of the molecules on the surface

Spintronic magnetic anisotropy

An attractive feature of magnetic adatoms and molecules for nanoscale applications is their superparamagnetism, the preferred alignment of their spin along an easy axis preventing undesired spin reversal. The underlying magnetic anisotropy barrier --a quadrupolar energy splitting-- is internally generated by spin-orbit interaction and can nowadays be probed by electronic transport. Here we predict that in a much broader class of quantum-dot systems with spin larger than one-half, superparamagnetism may arise without spin-orbit interaction: by attaching ferromagnets a spintronic exchange field of quadrupolar nature is generated locally. It can be observed in conductance measurements and surprisingly leads to enhanced spin filtering even in a state with zero average spin. Analogously to the spintronic dipolar exchange field, responsible for a local spin torque, the effect is susceptible to electric control and increases with tunnel coupling as well as with spin polarization.Comment: 6 pages with 4 figures + 26 pages of Supplementary Informatio

Inertial Sensor Based Modelling of Human Activity Classes: Feature Extraction and Multi-sensor Data Fusion Using Machine Learning Algorithms

Wearable inertial sensors are currently receiving pronounced interest due to applications in unconstrained daily life settings, ambulatory monitoring and pervasive computing systems. This research focuses on human activity recognition problem, in which inputs are multichannel time series signals acquired from a set of body-worn inertial sensors and outputs are automatically classified human activities. A general-purpose framework has been presented for designing and evaluating activity recognition system with six different activities using machine learning algorithms such as support vector machine (SVM) and artificial neural networks (ANN). Several feature selection methods were explored to make the recognition process faster by experimenting on the features extracted from the accelerometer and gyroscope time series data collected from a number of volunteers. In addition, a detailed discussion is presented to explore how different design parameters, for example, the number of features and data fusion from multiple sensor locations - impact on overall recognition performance