Experimental and Numerical Analysis of a Sustainable Farming Compartment with Evaporative Cooling System

The United Arab Emirates (UAE) relies on groundwater as well as desalinated water which are very expensive and energy-concentrated. Despite the lack of water resources, only 54% of wastewater was recycled in the UAE in 2016. In this study, a Sustainable Farming Compartment (SFC) with an evaporative cooling system is investigated as an alternative to reusing wastewater and the optimal design is identified experimentally and numerically. First, the applicability of the SFC was examined to reduce the ambient temperature in the system. A prototype SFC was tested in the environmentally constrained laboratory and field site considering an extreme climate condition (with high temperature and humidity) in Abu Dhabi to evaluate the temperature drop and humidity change of the SFC. The experimental results showed that the temperature of the SFC significantly decreases by 7–15 C when the initial relative humidity is 50%. For validation, an energy modeling using dynamic numerical simulations was performed that shows statistically good agreement with the experimental results. Based on the parametric studies of the system components, the optimal cooling performance of the system in terms of locations of inlet and outlet, the variation of Reynolds number was evaluated. The study suggested an optimized design for the SFC with an evaporative cooling system

Energy-efficient Knowledge Distillation for Spiking Neural Networks

Spiking neural networks (SNNs) have been gaining interest as energy-efficient alternatives of conventional artificial neural networks (ANNs) due to their event-driven computation. Considering the future deployment of SNN models to constrained neuromorphic devices, many studies have applied techniques originally used for ANN model compression, such as network quantization, pruning, and knowledge distillation, to SNNs. Among them, existing works on knowledge distillation reported accuracy improvements of student SNN model. However, analysis on energy efficiency, which is also an important feature of SNN, was absent. In this paper, we thoroughly analyze the performance of the distilled SNN model in terms of accuracy and energy efficiency. In the process, we observe a substantial increase in the number of spikes, leading to energy inefficiency, when using the conventional knowledge distillation methods. Based on this analysis, to achieve energy efficiency, we propose a novel knowledge distillation method with heterogeneous temperature parameters. We evaluate our method on two different datasets and show that the resulting SNN student satisfies both accuracy improvement and reduction of the number of spikes. On MNIST dataset, our proposed student SNN achieves up to 0.09% higher accuracy and produces 65% less spikes compared to the student SNN trained with conventional knowledge distillation method. We also compare the results with other SNN compression techniques and training methods

Methane as an effective hydrogen source for single-layer graphene synthesis on Cu foil by plasma enhanced chemical vapor deposition

A single-layer graphene is synthesized on Cu foil in the absence of H2 flow by plasma enhanced chemical vapor deposition (PECVD). In lieu of an explicit H2 flow, hydrogen species are produced during methane decomposition process into their active species (CHx<4), assisted by the plasma. Notably, the early stage of growth depends strongly on the plasma power. The resulting grain size (the nucleation density) has a maximum (minimum) at 50 W and saturates when the plasma power is higher than 120 W because hydrogen partial pressures are effectively tuned by a simple control of the plasma power. Raman spectroscopy and transport measurements show that decomposed methane alone can provide sufficient amount of hydrogen species for high-quality graphene synthesis by PECVD.Comment: 22 pages, 6 figure

Spatial Distribution of Intracluster Light versus Dark Matter in Horizon Run 5

One intriguing approach for studying the dynamical evolution of galaxy clusters is to compare the spatial distributions among various components, such as dark matter, member galaxies, gas, and intracluster light (ICL). Utilizing the recently introduced Weighted Overlap Coefficient (WOC) \citep{2022ApJS..261...28Y}, we analyze the spatial distributions of components within 174 galaxy clusters ($M_{\rm tot}> 5 \times 10^{13} M_{\odot}$, $z=0.625$) at varying dynamical states in the cosmological hydrodynamical simulation Horizon Run 5. We observe that the distributions of gas and the combination of ICL with the brightest cluster galaxy (BCG) closely resembles the dark matter distribution, particularly in more relaxed clusters, characterized by the half-mass epoch. The similarity in spatial distribution between dark matter and BCG+ICL mimics the changes in the dynamical state of clusters during a major merger. Notably, at redshifts $>$ 1, BCG+ICL traced dark matter more accurately than the gas. Additionally, we examined the one-dimensional radial profiles of each component, which show that the BCG+ICL is a sensitive component revealing the dynamical state of clusters. We propose a new method that can approximately recover the dark matter profile by scaling the BCG+ICL radial profile. Furthermore, we find a recipe for tracing dark matter in unrelaxed clusters by including the most massive satellite galaxies together with BCG+ICL distribution. Combining the BCG+ICL and the gas distribution enhances the dark matter tracing ability. Our results imply that the BCG+ICL distribution is an effective tracer for the dark matter distribution, and the similarity of spatial distribution may be a useful probe of the dynamical state of a cluster.Comment: 23 pages, 12 figures, accepted for publication in Ap

The mid-infrared view of red sequence galaxies in Abell 2218 with <i>AKARI</i>

We present the AKARI Infrared Camera (IRC) imaging observation of early-type galaxies (ETGs) in A2218 at z ~ 0.175. Mid-infrared (MIR) emission from ETGs traces circumstellar dust emission from asymptotic giant branch (AGB) stars or/and residual star formation. Including the unique imaging capability at 11 and 15 μm, our AKARI data provide an effective way to investigate MIR properties of ETGs in the cluster environment. Among our flux-limited sample of 22 red sequence ETGs with precise dynamical and line strength measurements (less than 18 mag at 3 μm), we find that at least 41% have MIR-excess emission. The N3 – S11 versus N3 (3 and 11 μm) color-magnitude relation shows the expected blue sequence, but the MIR-excess galaxies add a red wing to the relation especially at the fainter end. A spectral energy distribution analysis reveals that the dust emission from AGB stars is the most likely cause of the MIR excess, with a low level of star formation being the next possible explanation. The MIR-excess galaxies show a wide spread of N3 – S11 colors, implying a significant spread (2-11 Gyr) in the estimated mean ages of stellar populations. We study the environmental dependence of MIR-excess ETGs over an area out to a half virial radius (~1 Mpc). We find that the MIR-excess ETGs are preferentially located in the outer region. From this evidence, we suggest that the fainter, MIR-excess ETGs have just joined the red sequence, possibly due to the infall and subsequent morphological/spectral transformation induced by the cluster environment

Photometric Selection of Unobscured QSOs in the Ecliptic Poles: KMTNet in the South Field and Pan-STARRS in the North Field

We search for quasi-stellar objects (QSOs) in a wide area of the south ecliptic pole (SEP) field, which has been and will continue to be intensively explored through various space missions. For this purpose, we obtain deep broadband optical images of the SEP field covering an area of $\sim$$14.5\times14.5$ deg$^2$ with the Korea Microlensing Telescope Network. The 5$\sigma$ detection limits for point sources in the $BVRI$ bands are estimated to be $\sim$22.59, 22.60, 22.98, and 21.85 mag, respectively. Utilizing data from Wide-field Infrared Survey Explorer, unobscured QSO candidates are selected among the optically point-like sources using the mid-infrared (MIR) and optical-MIR colors. To further refine our selection and eliminate any contamination not adequately removed by the color-based selection, we perform the spectral energy distribution fitting with archival photometric data ranging from optical to MIR. As a result, we identify a total of 2,383 unobscured QSO candidates in the SEP field. We also apply a similar method to the north ecliptic pole field using the Pan-STARRS data and obtain a similar result of identifying 2,427 candidates. The differential number count per area of our QSO candidates is in good agreement with those measured from spectroscopically confirmed ones in other fields. Finally, we compare the results with the literature and discuss how this work will be implicated in future studies, especially with the upcoming space missions.Comment: 14 pages, 9 figures, accepted for publication in ApJ

Spatial Distribution of Intracluster Light versus Dark Matter in Horizon Run 5

One intriguing approach for studying the dynamical evolution of galaxy clusters is to compare the spatial distributions among various components such as dark matter, member galaxies, gas, and intracluster light (ICL). Utilizing the recently introduced weighted overlap coefficient (WOC), we analyze the spatial distributions of components within 174 galaxy clusters (M tot > 5 × 1013 M ⊙, z = 0.625) at varying dynamical states in the cosmological hydrodynamical simulation Horizon Run 5. We observe that the distributions of gas and the combination of ICL with the brightest cluster galaxy (BCG) closely resembles the dark matter distribution, particularly in more relaxed clusters, characterized by the half-mass epoch. The similarity in spatial distribution between dark matter and BCG+ICL mimics the changes in the dynamical state of clusters during a major merger. Notably, at redshifts >1, BCG+ICL traced dark matter more accurately than the gas. Additionally, we examined the one-dimensional radial profiles of each component, which show that the BCG+ICL is a sensitive component revealing the dynamical state of clusters. We propose a new method that can approximately recover the dark matter profile by scaling the BCG+ICL radial profile. Furthermore, we find a recipe for tracing dark matter in unrelaxed clusters by including the most massive satellite galaxies together with the BCG+ICL distribution. Combining the BCG+ICL and the gas distribution enhances the dark matter tracing ability. Our results imply that the BCG+ICL distribution is an effective tracer for the dark matter distribution, and the similarity of the spatial distribution may be a useful probe of the dynamical state of a cluster