Genomic approaches to unveil the physiological pathways activated in Arabidopsis treated with plant-derived raw extracts

DNA microarrays can be used to obtain a fingerprint of the transcriptional status of the plant or cell under a given condition and may be useful for characterising which genes respond, either by induction or repression, to novel stimuli or specific treatments. An in-depth bioinformatical analysis of all the data produced by microarrays can further highlight the metabolic or functional pathways most affected by the treatment. This approach has been used to investigate the effects induced by the treatment of different plant-derived raw materials, provided by Valagro SpA, on Arabidopsis seedlings. A clear example is represented by treatment with a raw plant-derived protein extract (VAL-P01). In this case the treatment induced genes related to ABA and osmotic stress treatment. We therefore demonstrated that VAL-P01 was able to mimic in planta the same pattern of responses linked to ABA treatment or osmotic stress, making the plant stronger against possible further stresses. Another plant extract, VAL-P02, was shown to be significantly altering the transcription of senescence genes, making it an ideal candidate adjuvant for the prolonged shelf-life of vegetal products

A General Mathematical Formulation for the Determination of Differential Leakage Factors in Electrical Machines with Symmetrical and Asymmetrical Full or Dead-Coil Multiphase Windings

This paper presents a simple and general mathematical formulation for the determination of the differential leakage factor for both symmetrical and asymmetrical full and dead-coil windings of electrical machines. The method can be applied to all multiphase windings and considers Görges polygons in conjunction with masses geometry in order to find an easy and affordable way to compute the differential leakage factor, avoiding the adoption of traditional methods that refer to the Ossanna's infinite series, which has to be obviously truncated under the bound of a predetermined accuracy. Moreover, the method described in this paper allows the easy determination of both the minimum and maximum values of the differential leakage factor, as well as its average value and the time trend. The proposed method, which does not require infinite series, is validated by means of several examples in order to practically demonstrate the effectiveness and the easiness of application of this procedure

Electron structure, ultra-dense hydrogen and low energy nuclear reactions

In this paper, a simple Zitterbewegung electron model, proposed in a previous work, is presented from a different perspective based on the principle of mass- frequency equivalence. A geometric- electromagnetic interpretation of mass, relativistic mass, De Broglie wavelength, Proca, Klein- Gordon, Dirac and Aharonov- Bohm equations in agreement with the model is proposed. A non-relativistic, Zitterbewegung interpretation of the 3.7 keV deep hydrogen level found by J. Naudts is presented. According to this perspective, ultra-dense hydrogen can be conceived as a coherent chain of bosonic electrons with protons or deuterons located in the center of their Zitterbewegung orbits. This approach suggests a possible role of ultra-dense hydrogen in some aneutronic and many-body low energy nuclear reactions. © 2019 ISCMNS. All rights reserved

Transcript profiling of chitosan-treated Arabidopsis seedlings

In nature, plants can recognize potential pathogens, thus activating intricate networks of defense signals and reactions. Inducible defense is often mediated by the detection of microbe or pathogen associated molecular pattern elicitors, such as flagellin and chitin. Chitosan, the deacetylated form of chitin, plays a role in inducing protection against pathogens in many plant species. We evaluated the ability of chitosan to confer resistance to Botrytis cinerea in Arabidopsis leaves. We subsequently treated Arabidopsis seedlings with chitosan and carried out a transcript profiling analysis using both ATH1 GeneChip microarrays and quantitative RT-PCR. The results showed that defense response genes, including camalexin biosynthesis genes, were up-regulated by chitosan, both in wild-type and in the chitin-insensitive cerk1 mutant, indicating that chitosan is perceived through a CERK1-independent pathway

Real-Time RGB-D Camera Pose Estimation in Novel Scenes using a Relocalisation Cascade

Camera pose estimation is an important problem in computer vision. Common techniques either match the current image against keyframes with known poses, directly regress the pose, or establish correspondences between keypoints in the image and points in the scene to estimate the pose. In recent years, regression forests have become a popular alternative to establish such correspondences. They achieve accurate results, but have traditionally needed to be trained offline on the target scene, preventing relocalisation in new environments. Recently, we showed how to circumvent this limitation by adapting a pre-trained forest to a new scene on the fly. The adapted forests achieved relocalisation performance that was on par with that of offline forests, and our approach was able to estimate the camera pose in close to real time. In this paper, we present an extension of this work that achieves significantly better relocalisation performance whilst running fully in real time. To achieve this, we make several changes to the original approach: (i) instead of accepting the camera pose hypothesis without question, we make it possible to score the final few hypotheses using a geometric approach and select the most promising; (ii) we chain several instantiations of our relocaliser together in a cascade, allowing us to try faster but less accurate relocalisation first, only falling back to slower, more accurate relocalisation as necessary; and (iii) we tune the parameters of our cascade to achieve effective overall performance. These changes allow us to significantly improve upon the performance our original state-of-the-art method was able to achieve on the well-known 7-Scenes and Stanford 4 Scenes benchmarks. As additional contributions, we present a way of visualising the internal behaviour of our forests and show how to entirely circumvent the need to pre-train a forest on a generic scene.Comment: Tommaso Cavallari, Stuart Golodetz, Nicholas Lord and Julien Valentin assert joint first authorshi

Modeling of Mid-IR Amplifier Based on an Erbium-Doped Chalcogenide Microsphere

An optical amplifier based on a tapered fiber and an Er3+-doped chalcogenide microsphere is designed and optimized. A dedicated 3D numerical model, which exploits the coupled mode theory and the rate equations, is used. The main transitions among the erbium energy levels, the amplified spontaneous emission, and the most important secondary transitions pertaining to the ion-ion interactions have been considered. Both the pump and signal beams are efficiently injected and obtained by a suitable design of the taper angle and the fiber-microsphere gap. Moreover, a good overlapping between the optical signals and the rare-earth-doped region is also obtained. In order to evaluate the amplifier performance in reduced computational time, the doped area is partitioned in sectors. The obtained simulation results highlight that a high-efficiency midinfrared amplification can be obtained by using a quite small microsphere

Rotor bar pre-fault detection in the squirrel cage induction motors

The paper deals with a diagnosis technique to detect and monitor incipient faults in the rotor bars of squirrel gage induction motors. The failure mode analysis is performed monitoring the motor axial vibrations. To accomplish the task, the authors present a mathematical model that allows relating the occurrence and the severity of the faults to the presence and the magnitude of some frequency components of the axial vibration spectrum. To validate the proposed approach, the results obtained by applying the mathematical model are compared with the ones obtained by experimental tests done on both healthy and faulty motors

Sensorless variable speed single-phase induction motor drive system based on direct rotor flux orientation

The single-phase induction motor (SPIM) is one of the electrical machines more used in the World, and can be found in several fractional and sub-fractional horsepower applications in houses, offices, shoppings, farms, and industries. The introduction of more sophisticated applications has required the use of variable speed drives for SPIM, where the adoption of sensorless techniques is the more reasonable option for speed control due to the low cost of this electrical machine. A proposal for sensorless variable speed SPIM drive based on direct rotor field orientation techniques is presented in this paper. None transformation is used in order to eliminate the asymmetry of the stator windings of the SPIM. The rotor speed is estimated from an flux observer, which is based on two independent linear feedback control systems. The speed and flux estimatives are used in two control loop based on PID regulators, which determine the voltages to be applied to the SPIM windings by a three-legs VSI inverter. Using computer simulations, two situations are considered in order to demonstrate the satisfactory performance of the proposed sensorless speed control for SPIM drives: variations on rotor speed reference and the application of mechanical load