The use of instant messaging (IM) application is very communal among smartphone users, as it delivers ease in interaction and communication. The speed at which technologies, growth, and expansion of networks infrastru...
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There are many object-oriented software quality measurement techniques. One of them is CK metric. This paper utilizes CK metrics to measure qualities per version of an open source software namely Statcato. Measurement...
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In a very recent accomplishment, the two-dimensional form of Biphenylene network (BPN) has been successfully fabricated [Fan et al., Science, 372, 852-856 (2021)]. Motivated by this exciting experimental result on 2D ...
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Nanophotonics has garnered intensive attention due to its unique capabilities in molding the flow of light in the subwavelength regime. Metasurfaces (MSs) and photonic integrated circuits (PICs) enable the realization...
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We report an additional degree of control of THz transients in Fe/X spintronic emitters grown on GaAs(001). We ascribe the field-independent enhancement of the THz amplitude to specific chemical bonding at the epitaxi...
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ISBN:
(纸本)9781943580910
We report an additional degree of control of THz transients in Fe/X spintronic emitters grown on GaAs(001). We ascribe the field-independent enhancement of the THz amplitude to specific chemical bonding at the epitaxial Fe/GaAs(001) interface.
Background Brain microstructure, as measured by diffusion MR imaging (dMRI), is an early biomarker of Alzheimer’s disease (AD) and has been previously demonstrated to predict whole brain atrophy and cognition. The ne...
Background Brain microstructure, as measured by diffusion MR imaging (dMRI), is an early biomarker of Alzheimer’s disease (AD) and has been previously demonstrated to predict whole brain atrophy and cognition. The network-based neurodegeneration hypothesis posits that the onset of AD occurs within key vulnerable regions, whose network connectivity guides the spread of atrophy into new regions. Graph convolutional network (GCN) models can mimic this spread through its convolution process. Here we present a GCN-based model to predict future individual nodal atrophy and disease progression across the AD spectrum using structural connectome. Method We analyzed 371 participants with baseline dMRI scans (154 cognitively normal (CN), 161 mild cognitive impairment (MCI), 56 AD) and longitudinal T1 scans (2.7±1.2 years) from the ADNI study. To predict annual nodal atrophy rates (126 nodes) from baseline structural connectivity (SC), we constructed a two-layer GCN followed by multilayer perceptron (GCN-MLP). Five-fold nested cross-validation and Optuna were used for hyperparameter tuning. We applied the trained GCN-MLP model to predict future disease progression via transfer learning. GNNExplainer was used to identify the predictive SC features for atrophy or cognition. The GCN-MLP model was validated in another independent dataset from Singapore (MACC) with 226 participants (61 CN, 112 MCI, 53 AD, follow-up period of T1 scans (3.1±1.3 years)) using transfer learning. Result The proposed GCN-MLP model predicted the annual rate of regional atrophy at the individual level in the main (R = 0.5407±0.0480; MAE = 0.0013±0.0001; EV = 0.2930±0.0516) and validation (R = 0.5323±0.0564; MAE = 0.0009±0.0001; EV = 0.2808±0.0559) datasets (Table 1; Figure 1). Graph edge SC of the target network contributed most to the atrophy prediction of its own network (Figure 2A&C). Nodal feature SC in hippocampus, striatum, and temporal network were major predictors of atrophy progression across all 1
Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (...
Artesian well is one of the major efforts to obtain water source for fulfilling water demands in Eroniti Conservation park, Ponjong, Yogyakarta by drilling deep into several soil layers. Vertical Electrical Sounding (VES) method is the most common approach to determine the existence of groundwater. The method probes layers of rock below the ground surface based on their electrical properties, since the electrical resistivity of each layer is theoretically different. This study aims to utilize the VES approach for investigating the properties of the rock layers in the area to explore groundwater sources. We install six different VES points in the observation area using Schlumberger electrode configuration. The methodology of the work consists of three steps: the planning of the placement of the sounding points, the measurement step performed by a unit of IRIS SYSCAL Resistivity meter, and the data analysis and interpretation. Employing the resistivity analysis, we conclude that the observed region consists of Mediterranean soil as a result of weathering of limestone as well as lithology of the limestone. Furthermore, there are two types of aquifer found in the area: a perched aquifer found 27 meters below the ground surface of VES point 1 and a confined aquifer 166 meters below the ground surface of VES point 2 and 6.
Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamical Resource Allocation (MOEA/D-DRA) is one of the most successful decomposition based multiobjective algorithm. Its main feature is a mechanism...
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Multi-Objective Evolutionary Algorithm based on Decomposition with Dynamical Resource Allocation (MOEA/D-DRA) is one of the most successful decomposition based multiobjective algorithm. Its main feature is a mechanism to allocate different computational effort proportional to the difficult of each subproblem. Despite its success, MOEA/D-DRA has a large set of parameters and operators, whose selection could be a difficult task. This paper aims at improving the performance of MOEA/D-DRA by means of a hyper-heuristic using two parameter/operator selection phases: one off-line strongly based on Iterated Race Automatic Algorithm Configuration (Irace) and another one (online) based on the Upper Confidence Bound (UCB) technique. The proposed approach is compared with the original MOEA/D-DRA, NSGAII and IBEA over 51 instances of 7 well known benchmarks (CEC 2009, GLT, LZ09, MOP, DTLZ, ZDT and WFG). Results show that Irace and UCB are interesting methods to support the hyper-heuristic functioning when selecting parameters/operators of MOEA/D-DRA in the addressed problems.
This work presents a preliminary study of a LMR-based gas sensor. Results of the device subjected to annealing process show a stable and repetitive response that is required for the utilization in gas sensing applicat...
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The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintr...
The mechanism of THz generation in ferromagnet/metal (F/M) bilayers has been typically ascribed to the inverse spin Hall effect (ISHE). Here, we fabricated Pt/Fe/Cr/Fe/Pt multilayers containing two back-to-back spintronic THz emitters separated by a thin (tCr≤ 3nm) wedge-shaped Cr spacer. In such an arrangement, magnetization alignment of the two Fe films can be controlled by the interplay between Cr-mediated interlayer exchange coupling (IEC) and an external magnetic field. This in turn results in a strong variation of the THz amplitudeA, withA↑↓reaching up to 14 timesA↑↑(arrows indicate the relative alignment of the magnetization of the two magnetic layers). This observed functionality is ascribed to the interference of THz transients generated by two closely spaced THz emitters. Moreover, the magnetic field dependenceA(H) shows a strong asymmetry that points to an additional performance modulation of the THz emitter via IEC and multilayer design.
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