We report the detection of a transiting Earth-size planet around GJ 357, a nearby M2.5 V star, using data from the Transiting Exoplanet Survey Satellite (TESS). GJ 357 b (TOI-562.01) is a transiting, ...hot, Earth-sized planet (Teq = 525 ± 11 K) with a radius of Rb = 1.217 ± 0.084 R⊕ and an orbital period of Pb = 3.93 d. Precise stellar radial velocities from CARMENES and PFS, as well as archival data from HIRES, UVES, and HARPS also display a 3.93-day periodicity, confirming the planetary nature and leading to a planetary mass of Mb = 1.84 ± 0.31 M⊕. In addition to the radial velocity signal for GJ 357 b, more periodicities are present in the data indicating the presence of two further planets in the system: GJ 357 c, with a minimum mass of Mc = 3.40 ± 0.46 M⊕ in a 9.12 d orbit, and GJ 357 d, with a minimum mass of Md = 6.1 ± 1.0 M⊕ in a 55.7 d orbit inside the habitable zone. The host is relatively inactive and exhibits a photometric rotation period of Prot = 78 ± 2 d. GJ 357 b isto date the second closest transiting planet to the Sun, making it a prime target for further investigations such as transmission spectroscopy. Therefore, GJ 357 b represents one of the best terrestrial planets suitable for atmospheric characterization with the upcoming JWST and ground-based ELTs.
Partial discharge (PD) measurements are an important tool for assessing the health of power equipment. Different sources of PD have different effects on the insulation performance of power apparatus. ...Therefore, discrimination between PD sources is of great interest to both system utilities and equipment manufacturers. This paper investigates the use of a wide bandwidth PD on-line measurement system consisting of a radio frequency current transducer (RFCT) sensor, a digital storage oscilloscope and a high performance personal computer to facilitate automatic PD source identification. Three artificial PD models were used to simulate typical PD sources which may exist within power system apparatus. Wavelet analysis was applied to pre-process measurement data obtained from the wide bandwidth PD sensor. This data was then processed using correlation analysis to cluster the discharges into different groups. A machine learning technique, namely the support vector machine (SVM) was then used to identify between the different PD sources. The SVM is trained to differentiate between the inherent features of each discharge source signal. Laboratory experiments where the trained SVM was tested using measurement data from the RFCT as opposed to conventional measurement data indicate that this approach has a robust performance and has great potential for use with field measurement data.
Graphene oxide (GO) was produced using acidic graphite oxidation and dispersed within an epoxy matrix using a solvent-based technique, to give nanocomposites containing up to 2 wt% of GO. ...Transmission and scanning electron microscopy revealed a fine dispersion of graphitic sheets which alters the nanocomposite’s fractured surface morphology, while Fourier transform infrared spectroscopy revealed an excess of epoxide groups in the system, which are associated with the included GO. These additional moieties react with hardener amine groups and, consequently, displace the reaction stoichiometry away from the optimum. The result of this is a change in the network architecture and, in particular, the introduction of epoxy-terminated branches, which modify the dielectric
γ
relaxation. During post-curing, hydroxyl groups on the GO surface react with residual epoxide groups through etherification reactions, to give a marked increase in the glass transition temperature. These reactions lead to increased interfacial interactions between the GO and the matrix, which contribute to an increase in tensile performance. In addition, post-curing also reduces the defect content within the GO lattice which, in turn, increases the electrical conductivity, dielectric permittivity and low frequency losses of the system. Associated chemical pathways are proposed.
Partial discharge (PD) signals generated within electrical power equipment can be used to assess the condition of the insulation. In practice, testing often results in multiple PD sources. In order ...to assess the impact of individual PD sources, signals must first be discriminated from one another. This paper presents a procedure for the identification of PD signals generated by multiple sources. Starting with the assumption that different PD sources will display unique signal profiles this will be manifested in the distribution of energies with respect to frequency and time. Therefore the technique presented is based on the comparison of signal energies associated with particular wavelet-decomposition levels. Principal component analysis is adopted to reduce the dimensionality of the data, whilst minimizing lost information in the data concentration step. Physical parameters are extracted from individual PD pulses and projected into 3-dimensional space to allow clustering of data from specific PD sources. The density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm is chosen for its ability to discover clusters of arbitrary shape in n-dimension space. PD data from individual clusters can then be further analyzed by projecting the clustered data with respect to the original phase relationship. Results and analysis of the technique are compared for experimentally measured PD data from a range of sources commonly found in three different types of high voltage (HV) equipment; ac synchronous generators, induction motors and distribution cables. These experiments collect data using varied test arrangements including sensors with different bandwidths to demonstrate the robustness and indicate the potential for wide applicability of the technique to PD analysis for a range of insulation systems.
Low-altitude high-resolution aerial photographs allow for the reconstruction of structural properties of shallow coral reefs and the quantification of their topographic complexity. This study shows ...the scope and limitations of two-media (air/water) Structure from Motion—Multi-View Stereo reconstruction method using drone aerial photographs to reconstruct coral height. We apply this method in nine different sites covering a total area of about 7000 m
2
, and we examine the suitability of the method to obtain topographic complexity estimates (i.e., seafloor rugosity). A simple refraction correction and survey design allowed reaching a root mean square error of 0.1 m for the generated digital models of the seafloor (without the refraction correction the root mean square error was 0.2 m). We find that the complexity of the seafloor extracted from the drone digital models is slightly underestimated compared to the one measured with a traditional in situ survey method.
Mechanical stresses affect the electrical performance of solid-solid interfaces in high-voltage cable joints. This paper assesses the influence of insulation material mechanical properties and ...temperature on interface pressure. Based on a hyper-elastic model, the mechanical stresses inside silicone rubber joint tube were determined. Circumferential stresses can reach 50% of the silicone rubber tensile strength at normal pre-operation expansion ratios. An analytical method to determine the thermally induced mechanical stress during operation is presented and its accuracy is confirmed using finite element method. This method is modified to account for the variation of the mechanical properties with temperature. This paper shows that circumferential stresses at the interface increase as temperature drops, which may have a significant impact on the electrical performance of the interface during operation.
Individuals with an evening chronotype prefer to sleep later at night, wake up later in the day and perform best later in the day as compared to individuals with morning chronotype. Thus, college ...students without ADHD symptoms with evening chronotypes show reduced cognitive performance in the morning relative to nighttime (i.e., desynchrony effect). In combination with symptoms presented in attention deficit hyperactivity disorder (ADHD), we predicted that having evening chronotype renders impairment in attention during the morning, when students require optimal performance, amplifying desynchrony.
Four hundred college students were surveyed for evening chronotype and symptoms of ADHD. Of those surveyed, 43 students with evening chronotype (19 with ADHD symptoms) performed laboratory attention tasks and were queried about fatigue during morning and evening sessions.
Students with ADHD symptoms demonstrated a greater decrement in sustained attentional vigilance when abstaining from stimulants and asked to perform cognitive tests at times misaligned with natural circadian rhythms in arousal compared to their non-ADHD counterparts with the same chronotype. While individuals with ADHD symptoms had slower reaction-times during sustained attention tasks in the morning session compared to those without symptoms, there was no significant group difference in working memory performance, even though both groups made more errors in the morning session compared to the evening session.
These findings suggest that evening chronotype students with ADHD symptoms are at a greater disadvantage when having to perform sustained attention tasks at times that are not aligned to their circadian rhythm compared to their neuro-typical peers. The implications of this finding may be useful for the provision of disability accommodations to college age students with ADHD when they are expected to perform tasks requiring sustained attention at times misaligned with their circadian rhythms.
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