Three-Dimensional Magnetic Page Memory

The increasing need to store large amounts of information with an ultra-dense, reliable, low power and low cost memory device is driving aggressive efforts to improve upon current perpendicular magnetic recording technology. However, the difficulties in fabricating small grain recording media while maintaining thermal stability and a high signal-to-noise ratio motivate development of alternative methods, such as the patterning of magnetic nano-islands and utilizing energy-assist for future applications. In addition, both from sensor and memory perspective three-dimensional spintronic devices are highly desirable to overcome the restrictions on the functionality in the planar structures. Here we demonstrate a three-dimensional magnetic-memory (magnetic page memory) based on thermally assisted and stray-field induced transfer of domains in a vertical stack of magnetic nanowires with perpendicular anisotropy. Using spin-torque induced domain shifting in such a device with periodic pinning sites provides additional degrees of freedom by allowing lateral information flow to realize truly three-dimensional integration

Synergistic effects of zinc borate and aluminiumtrihydroxide on flammability behaviour of aerospaceepoxy system

The flame retardancy of mono-component epoxy resin (RTM6), widely used for aerospace composites, treated with zinc borate (ZB), aluminium trihydroxide (ATH) and their mixtures at different concentrations have been investigated by morphological and thermal characterization. Cone calorimeter data reveal that combustion behaviour, heat release rate peak (PHRR) and heat release rate average (HRR Average) of RTM6 resin decrease substantially when synergistic effects of zinc borate and aluminium trihydroxide intervene. Thermogravimetric (TGA) results and analysis of the residue show that addition higher than 20% w/w of ZB, ATH, and their mixture greatly promotes RTM6 char formation acting as a barrier layer for the fire development. Depending upon the different used flame additives, SEM micrographs indicate that the morphology of residual char could vary from a compact amalgam-like structure, for the RTM6+ZB system, to a granular structure, characterized by very small particles of degraded resin and additive for the AT

Assessment of a calibration procedure to estimate soil water content with Sentek Diviner 2000 capacitance probe

In irrigated systems, soil water content is a major factor determining plant growth. Irrigation scheduling criteria are often related to measurements of soil water content or matric potential. Strategies to manage irrigation can be used to optimize irrigation water use or to maximize crop yield and/or quality, in order to increase the net return for the farmer. Of course, whatever criterion is adopted to schedule irrigation and in particular when crop water stress conditions are considered, the accurate monitoring of the water content in the soil profile, could allow to verify the exact irrigation timing, defined according to the crop response to water stress. Currently many methods are available for determining soil water content on a volume basis (m3m-3) or a tension basis (MPa), as described by Robinson (2008). Recently, distributed fiber optic temperature measurement, has been assessed as a new technique for indirect and precise estimation of soil water contents. Over the past decade Frequency Domain Reflectometry (FDR) probes, allowing to measure the apparent dielectric constant of the soil (K), indirectly related to the volumetric water content (θv), have been improved, due to the good potentiality of capacitance based sensors to in situ measurements of soil water content. However, due to the high variability of K with soil minerals and dry plants tissues, it necessary to proceed to a specific calibration of the sensor for each soil (Baumhardt et al., 2000), even to take into account the effect of soil temperature, bulk density and water salinity (Al Ain et al., 2009). . According to Paltineanu and Starr (1997), the precision of the calibration equation, obtained with in situ measurements, mainly depends on the errors related to the sampling of the soil volume investigated by the sensor, that must be done accurately. For swelling/shrinking soils, the changes of soil bulk volume with water content cause modifications in the geometry of some if not all the soil pores, affecting the bulk density/water content relationship (Allbrook, 1992). Field experiments in shrinking-swelling clay soils evidenced that soil water content can be affect by errors of 20-30% if the soil shrinkage curve is not considered (Fares et al., 2004). The main objective of the paper was to propose a practical calibration procedure for FDR sensor using minilysimeter containing undisturbed soil, allowing to take in to account the possible variations of the bulk density with the soil water content. Moreover, the possibility of using disturbed soil samples for determining the sensor calibration curve was also investigated, in order to simplify the proposed methodology. Experiments were carried out on three different soil, two of which containing a percentage of clay higher than 40%, in order to compare the specific calibration curves with that suggested by the manufactures. The investigation showed how for swelling/shrinkage soils it is necessary the knowledge of the actual soil bulk density and also that using disturbed soil sample is not possible to consider the effects of the soil shrinkage consequent to the soil water content reductions

RNomics: a computational search for box C/D snoRNA genes in the D. melanogaster genome.

Motivation: In eukaryotes, the family of non-coding RNA genes includes a number of genes encoding small nucleolar RNAs (mainly C/D and H/ACA snoRNAs), which act as guides in the maturation or post-transcriptional modifications of target RNA molecules. Since in Drosophila melanogaster (Dm) only few examples of snoRNAs have been identified so far by cDNA libraries screening, integration of the molecular data with in silico identification of these types of genes could throw light on their organization in the Dm genome. Results: We have performed a computational screening of the Dm genome for C/D snoRNA genes, followed by experimental validation of the putative candidates. Few of the 26 confirmed snoRNAs had been recognized by cDNA library analysis. Organization of the Dm genome was also found to be more variegated than previously suspected, with snoRNA genes nested in both the introns and exons of protein-coding genes. This finding suggests that the presence of additional mechanisms of snoRNA biogenesis based on the alternative production of overlapping mRNA/snoRNA molecules. Availability: Additional information is available at http://www. bioinformatica.unito.it/bioinformatics/snoRNA

Enhancing Coexistence in the Unlicensed Band with Massive MIMO

We consider cellular base stations (BSs) equipped with a large number of antennas and operating in the unlicensed band. We denote such system as massive MIMO unlicensed (mMIMO-U). We design the key procedures required to guarantee coexistence between a cellular BS and nearby Wi-Fi devices. These include: neighboring Wi-Fi channel covariance estimation, allocation of spatial degrees of freedom for interference suppression, and enhanced channel sensing and data transmission phases. We evaluate the performance of the so-designed mMIMO-U, showing that it allows simultaneous cellular and Wi-Fi transmissions by keeping their mutual interference below the regulatory threshold. The same is not true for conventional listen-before-talk (LBT) operations. As a result, mMIMO-U boosts the aggregate cellular-plus-Wi-Fi data rate in the unlicensed band with respect to conventional LBT, exhibiting increasing gains as the number of BS antennas grows.Comment: To appear in Proc. IEEE ICC 201

Indoor Massive MIMO Deployments for Uniformly High Wireless Capacity

Providing consistently high wireless capacity is becoming increasingly important to support the applications required by future digital enterprises. In this paper, we propose Eigen-direction-aware ZF (EDA-ZF) with partial coordination among base stations (BSs) and distributed interference suppression as a practical approach to achieve this objective. We compare our solution with Zero Forcing (ZF), entailing neither BS coordination or inter-cell interference mitigation, and Network MIMO (NeMIMO), where full BS coordination enables centralized inter-cell interference management. We also evaluate the performance of said schemes for three sub-6 GHz deployments with varying BS densities -- sparse, intermediate, and dense -- all with fixed total number of antennas and radiated power. Extensive simulations show that: (i) indoor massive MIMO implementing the proposed EDA-ZF provides uniformly good rates for all users; (ii) indoor network densification is detrimental unless full coordination is implemented; (iii) deploying NeMIMO pays off under strong outdoor interference, especially for cell-edge users

Modeling Quality and Machine Learning Pipelines through Extended Feature Models

The recently increased complexity of Machine Learning (ML) methods, led to the necessity to lighten both the research and industry development processes. ML pipelines have become an essential tool for experts of many domains, data scientists and researchers, allowing them to easily put together several ML models to cover the full analytic process starting from raw datasets. Over the years, several solutions have been proposed to automate the building of ML pipelines, most of them focused on semantic aspects and characteristics of the input dataset. However, an approach taking into account the new quality concerns needed by ML systems (like fairness, interpretability, privacy, etc.) is still missing. In this paper, we first identify, from the literature, key quality attributes of ML systems. Further, we propose a new engineering approach for quality ML pipeline by properly extending the Feature Models meta-model. The presented approach allows to model ML pipelines, their quality requirements (on the whole pipeline and on single phases), and quality characteristics of algorithms used to implement each pipeline phase. Finally, we demonstrate the expressiveness of our model considering the classification problem