Phenology, seasonal abundance and stage-structure of spittlebug (Hemiptera: Aphrophoridae) populations in olive groves in Italy

Spittlebugs (Hemiptera: Aphrophoridae) are the dominant xylem-sap feeders in the Mediterranean area and the only proven vectors of Xylella fastidiosa ST53, the causal agent of the olive dieback epidemic in Apulia, Italy. We have investigated the structured population phenology, abundance and seasonal movement between crops and wild plant species of both the nymphal and adult stages of different spittlebug species in olive groves. Field surveys were conducted during the 2016–2018 period in four olive orchards located in coastal and inland areas in the Apulia and Liguria regions in Italy. The nymphal population in the herbaceous cover was estimated using quadrat samplings. Adults were collected through sweep nets on three different vegetational components: herbaceous cover, olive canopy and wild woody plants. Philaenus spumarius was the most abundant species; its nymphs were collected from early March and reached a peak around mid-April, when the 4th instar was prevalent. Spittlebug adults were collected from late April until late autumn. P. spumarius adults were abundant on the herbaceous cover and olive trees in late spring, and they then dispersed to wild woody hosts during the summer and returned to the olive groves in autumn when searching for oviposition sites in the herbaceous cover. A relatively high abundance of P. spumarius was observed on olive trees during summer in the Liguria Region. The present work provides a large amount of data on the life cycle of spittlebugs within an olive agroecosystem that can be used to design effective control programmes against these vectors in infected areas and to assess the risk of the establishment and spread of X. fastidiosa to Xylella-free areas

A Reconfigurable Inductor Based on Vanadium Dioxide Insulator-to-Metal Transition

This letter introduces a reconfigurable planar square-coil-shaped inductor exploiting as the tuning mechanism the insulator-to-metal transition (IMT) of a vanadium dioxide (VO2) switch placed in the interwinding space in an unprecedented manner. The VO2 thin-film bar-shaped switch is electrically connected to provide a temperature-selective current path that effectively short-circuits a part of the inductor coil changing the inductance of the device. The inductor is fabricated on a high-resistivity silicon substrate using a CMOS-compatible 2-D planar low-cost technology (four photolithography steps). The design, optimized to work in the 4-10-GHz range, provides measured inductances at 5 GHz of 2.1 nH at 20 degrees C and 1.35 nH at 100 degrees C with good stability in the entire frequency band (4-10 GHz) resulting in a reconfiguration ratio of 55%. The quality factor (Q-factor) at 7 GHz is about 8 at 20 degrees C (off state) and 3 at 100 degrees C (on state), outperforming tunable inductors employing VO2 with 2 orders of magnitude higher Q-factor and a smaller footprint. This represents an advancement for the state of the art of 2-D CMOS-compatible inductors in the considered frequency range

Vanadium Oxide Bandstop Tunable Filter for Ka Frequency Bands Based on a Novel Reconfigurable Spiral Shape Defected Ground Plane CPW

This paper proposes and validates a new principle in coplanar waveguide (CPW) bandstop filter tuning by shortcutting defected ground plane (DGS) inductor shaped spirals to modify the resonant frequency. The tunable filter is fabricated on a high-resistivity silicon substrate based on a CMOS compatible technology using a 1 μm x 10 μm long and 300 nm thick vanadium oxide (VO2) switch by exploiting its insulator to metal transition. The filter is designed to work in Ka band with tunable central frequencies ranging from 28.2 GHz to 35 GHz. The measured results show a tuning range of more than 19 %, a low insertion loss in the neighboring frequency bands (below 2 dB at 20 GHz and 40 GHz in on/off-states) while a maximum rejection level close to 18 dB in off-state, limited by the no RF-ideal CMOS compatible substrate. The filter has a footprint of only 0.084 · λ0 x 0.037 · λ0 (where λ0 represents the free space wavelength at the highest resonance frequency) thus making it the most compact configuration using CPW DGS structures for the Ka frequency band. In addition, a more compact filter concept based on the Peano space filling curve is introduced to increase the tuning range while minimizing the DGS area

Neuromorphic computing using non-volatile memory

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems. We first review recent advances in the application of NVM devices to three computing paradigms: spiking neural networks (SNNs), deep neural networks (DNNs), and ‘Memcomputing’. In SNNs, NVM synaptic connections are updated by a local learning rule such as spike-timing-dependent-plasticity, a computational approach directly inspired by biology. For DNNs, NVM arrays can represent matrices of synaptic weights, implementing the matrix–vector multiplication needed for algorithms such as backpropagation in an analog yet massively-parallel fashion. This approach could provide significant improvements in power and speed compared to GPU-based DNN training, for applications of commercial significance. We then survey recent research in which different types of NVM devices – including phase change memory, conductive-bridging RAM, filamentary and non-filamentary RRAM, and other NVMs – have been proposed, either as a synapse or as a neuron, for use within a neuromorphic computing application. The relevant virtues and limitations of these devices are assessed, in terms of properties such as conductance dynamic range, (non)linearity and (a)symmetry of conductance response, retention, endurance, required switching power, and device variability.11Yscopu

Tunable RF phase shifters based on Vanadium Dioxide metal insulator transition

This paper presents the design, fabrication, and electrical characterization of a reconfigurable RF capacitive shunt switch that exploits the electro-thermally triggered vanadium dioxide (VO2) insulator to metal phase transition. The RF switch is further exploited to build wide-band RF true-time delay tunable phase shifters. By triggering the VO2 switch insulator to metal transition (IMT), the total capacitance can be reconfigured from the series of two metal-insulator-metal (MIM) capacitors to a single MIM capacitor. The effect of bias voltage on losses and phase shift is investigated, explained, and compared to the state of the art in the field. We report thermal actuation of the devices by heating the devices above VO2 IMT temperature. By cascading multiple stages a maximum of 40° per dB loss close to 7 GHz were obtained

Cardiovascular risk in chronic autoimmune thyroiditis and subclinical hypothyroidism patients. A cluster analysis

Background Subclinical hypothyroidism (SCH) and chronic autoimmune thyroiditis (CAT) are linked to an increased risk of atherosclerosis and coronary heart disease (CHD). The aim of this study was to look for positive markers of CHD and correlations with thyroid blood tests in patients with SCH or CAT, but no symptoms of CHD, so as to identify CHD risk conditions that otherwise would likely be missed. Methods We measured a series of thyroid, clinical-metabolic and cardiovascular parameters in 30 consecutive endocrinology patients enrolled in our ambulatory endocrinological referral center of “Sapienza” University of Rome. (19 with CAT, 11 with SCH) from January 2015 to March 2015. 13 asymptomatic subjects were enrolled as controls. In each patient, we measured a series of 34 thyroid, clinical-metabolic and cardiovascular parameters. Results in the statistical analysis of collected data, the oblique principal components clustering procedure (OPC) revealed the presence of an interesting mixed cluster, composed of a thyroid parameter (TPO-Ab), a metabolic parameter (homocysteine level) and a cardiovascular parameter (MAPSE), in which we assessed the relationships between the single components. Our preliminary results indicate that in both groups of patients elevated TPO-Ab, when accompanied by reduced MAPSE and increased IMT and homocysteine values, may be taken to indicate the presence of clinically unrecognized CHD. Conclusions Confirmation of these results in larger series of patients could justify hormone therapy for prevention of CHD in these thyroid patients versus placebo treatmentBackground Subclinical hypothyroidism (SCH) and chronic autoimmune thyroiditis (CAT) are linked to an increased risk of atherosclerosis and coronary heart disease (CHD). The aim of this study was to look for positive markers of CHD and correlations with thyroid blood tests in patients with SCH or CAT, but no symptoms of CHD, so as to identify CHD risk conditions that otherwise would likely be missed. Methods We measured a series of thyroid, clinical-metabolic and cardiovascular parameters in 30 consecutive endocrinology patients enrolled in our ambulatory endocrinological referral center of “Sapienza” University of Rome. (19 with CAT, 11 with SCH) from January 2015 to March 2015. 13 asymptomatic subjects were enrolled as controls. In each patient, we measured a series of 34 thyroid, clinical-metabolic and cardiovascular parameters. Results in the statistical analysis of collected data, the oblique principal components clustering procedure (OPC) revealed the presence of an interesting mixed cluster, composed of a thyroid parameter (TPO-Ab), a metabolic parameter (homocysteine level) and a cardiovascular parameter (MAPSE), in which we assessed the relationships between the single components. Our preliminary results indicate that in both groups of patients elevated TPO-Ab, when accompanied by reduced MAPSE and increased IMT and homocysteine values, may be taken to indicate the presence of clinically unrecognized CHD. Conclusions Confirmation of these results in larger series of patients could justify hormone therapy for prevention of CHD in these thyroid patients versus placebo treatmen

Bidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part I: Al/Mo/Pr_0.7Ca_0.3MnO₃ Material Improvements and Device Measurements

We report on material improvements to non-filamentary RRAM devices based on Pr0.7Ca0.3MnO3 by introducing an MoOx buffer layer together with a reactive Al electrode, and on device measurements designed to help gauge the performance of these devices as bidirectional analog synapses for on-chip acceleration of the backpropagation algorithm. Previous Al/PCMO devices exhibited degraded LRS retention due to the low activation energy for oxidation of the Al electrode, and Mo/PCMO devices showed low conductance contrast. To control the redox reaction at the metal/PCMO interface, we introduce a 4-nm interfacial layer of conducting MoOx as an oxygen buffer layer. Due to the controlled redox reaction within this Al/Mo/PCMO device, we observed improvements in both retention and conductance on/off ratio. We confirm bidirectional analog synapse characteristics and measure “jump-tables” suitable for large scale neural network simulations that attempt to capture complex and stochastic device behavior [see companion paper]. Finally, switching energy measurements are shown, illustrating a path for future device research toward smaller devices, shorter pulses and lower programming voltages

Reducing circuit design complexity for neuromorphic machine learning systems based on Non-Volatile Memory arrays

Machine Learning (ML) is an attractive application of Non-Volatile Memory (NVM) arrays [1,2]. However, achieving speedup over GPUs will require minimal neuron circuit sharing and thus highly area-efficient peripheral circuitry, so that ML reads and writes are massively parallel and time-multiplexing is minimized [2]. This means that neuron hardware offering full `software-equivalent' functionality is impractical. We analyze neuron circuit needs for implementing back-propagation in NVM arrays and introduce approximations to reduce design complexity and area. We discuss the interplay between circuits and NVM devices, such as the need for an occasional RESET step, the number of programming pulses to use, and the stochastic nature of NVM conductance change. In all cases we show that by leveraging the resilience of the algorithm to error, we can use practical circuit approaches yet maintain competitive test accuracies on ML benchmarks

Accelerating Machine Learning with Non-Volatile Memory: exploring device and circuit tradeoffs

Large arrays of the same nonvolatile memories (NVM) being developed for Storage-Class Memory (SCM) such as Phase Change Memory (PCM) and Resistance RAM (ReRAM) - can also be used in non-Von Neumann neuromorphic computational schemes, with device conductance serving as synaptic "weight." This allows the all-important multiply-accumulate operation within these algorithms to be performed efficiently at the weight data. In contrast to other groups working on Spike-Timing Dependent Plasticity (STDP), we have been exploring the use of NVM and other inherently-analog devices for Artificial Neural Networks (ANN) trained with the backpropagation algorithm. We recently showed a large-scale (165,000 two-PCM synapses) hardware-software demo (IEDM 2014, [1], [2]) and analyzed the potential speed and power advantages over GPU-based training (IEDM 2015, [3]). In this paper, we extend this work in several useful directions. We assess the impact of undesired, time-varying conductance change, including drift in PCM and leakage of analog CMOS capacitors. We investigate the use of non-filamentary, bidirectional ReRAM devices based on PrCaMnO, with an eye to developing material variants that provide suitably linear conductance change. And finally, we explore tradeoffs in designing peripheral circuitry, balancing simplicity and area-efficiency against the impact on ANN performance