Hierarchical Coherent Phonons in a Superatomic Semiconductor

The coupling of phonons to electrons and other phonons plays a defining role in material properties, such as charge and energy transport, light emission, and superconductivity. In atomic solids, phonons are delocalized over the 3D lattice, in contrast to molecular solids where localized vibrations dominate. Here, a hierarchical semiconductor that expands the phonon space by combining localized 0D modes with delocalized 2D and 3D modes is described. This material consists of superatomic building blocks (Re₆Se₈) covalently linked into 2D sheets that are stacked into a layered van der Waals lattice. Using transient reflectance spectroscopy, three types of coherent phonons are identified: localized 0D breathing modes of isolated superatom, 2D synchronized twisting of superatoms in layers, and 3D acoustic interlayer deformation. These phonons are coupled to the electronic degrees of freedom to varying extents. The presence of local phonon modes in an extended crystal opens the door to controlling material properties from hierarchical phonon engineering.     

A web-based 3D ontology navigation system for spinal disease diagnosis

The Journal of Supercomputing - This paper presents a web-based three-dimensional (3D) navigation system for a spinal disease ontology using a 3D virtual human spine. The 3D navigation system...     

An effective security measures for nuclear power plant using big data analysis approach

The Journal of Supercomputing - Among the many hacking attempts carried out against information systems for the past few years, cyber-attacks that could lead to a national-level threat included...     

Automated delineation of non-small cell lung cancer: A step toward quantitative reasoning in medical decision science

Quantitative reasoning in medical decision science relies on the delineation of pathological objects. For example, evidence-based clinical decisions regarding lung diseases require the segmentation of nodules, tumors, or cancers. Non-small cell lung cancer (NSCLC) tends to be large sized, irregularly shaped, and grows against surrounding structures imposing challenges in the segmentation, even for expert clinicians. An automated delineation tool based on spatial analysis was developed and studied on 25 sets of computed tomography scans of NSCLC. Manual and automated delineations were compared, and the proposed method exhibited robustness in terms of the tumor size (5.32–18.24 mm), shape (spherical or irregular), contouring (lobulated, spiculated, or cavitated), localization (solitary, pleural, mediastinal, endobronchial, or tagging), and laterality (left or right lobe) with accuracy between 80% and 99%. Small discrepancies observed between the manual and automated delineations may arise from the variability in the practitioners' definitions of region of interest or imaging artifacts that reduced the tissue resolution.     

Decorative near-infrared transmission filters featuring high-efficiency and angular-insensitivity employing 1D photonic crystals

We present a new scheme for visibly-opaque but near-infrared-transmitting filters involving 7 layers based on one-dimensional ternary photonic crystals, with capabilities in reaching nearly 100% transmission efficiency in the near-infrared region. Different decorative reflection colors can be created by adding additional three layers while maintaining the near-infrared transmission performance. In addition, our proposed structural colors show great angular insensitivity up to ±60° for both transverse electric and transverse magnetic polarizations, which are highly desired in various fields. The facile strategy described here involves a simple deposition method for the fabrication, thereby having great potential in diverse applications such as image sensors, anti-counterfeit tag, and optical measurement systems.

     

Regional-scale rice-yield estimation using stacked auto-encoder with climatic and MODIS data: a case study of South Korea

In South Korea, rice is the most important grain crop that it is crucial to develop yield estimation model for supporting sustainable agriculture and national food security. The main objectives of this paper are (1) to propose a Deep Learning (DL) algorithm, the Stacked Sparse Auto-encoder (SSAE), for rice-yield estimation using climatic and Moderate Resolution Imaging Spectroradiometer (MODIS) data; (2) to choose scenarios showing the best combined performance in terms of length of crop season (before and after harvest) and aggregation periods (7, 10, 15, and 30 days) of climatic data; and (3) to analyse the results in both the temporal and spatial perspectives. In this procedure, the SSAE model was built around the study objectives and compared with the artificial neural network (ANN) model for evaluation of its performance. According to the results, the combined 15-day-aggregated climatic data (between June and August) and MODIS data were selected as the optimal feature set for rice-yield estimation in the study area, Jeolla-do; the SSAE model outperformed ANN, showing root mean square error (RMSE) and RMSE% of 33.09 kg(10a)^?1 (5.21 kg(10a)^?1lower than ANN) and 6.89% (1.14% lower than ANN). Throughout the experiments, the rice-yield-estimation potentiality of a DL algorithm, namely the SSAE, was substantiated.     

Effect of UV-C irradiation on inactivation of Aspergillus flavus and Aspergillus parasiticus and quality parameters of roasted coffee bean (Coffea arabica L.)

ABSTRACT

This study investigated the antifungal effect of ultraviolet-C (UV-C) against Aspergillus flavus and Aspergillus parasiticus on roasted coffee beans. Also, any changes in the quality of the roasted coffee beans were measured after UV-C irradiation. As UV-C irradiation time increased (0–2 h), the number of surviving A. flavus and A. parasiticus spores significantly (P < .05) decreased. The reduction values of A. flavus in round part, crack part, and whole roasted coffee beans were 2.16, 0.71, and 1.58 log₁₀ CFU g^?1, respectively, and the reduction values of A. parasiticus in round part, crack part, and whole roasted coffee beans were 1.03, 0.37, and 0.72 log₁₀ CFU g^?1, respectively, after 2 h of UV-C irradiation. Field emission scanning electron microscopy showed that the morphology of A. flavus and A. parasiticus spores included expanded wrinkles that were deformed by UV-C irradiation. The Hunter colours were significantly reduced (P < .05). There was no significant change (P > .05) in moisture content, but the pH was significantly decreased (P < .05). Most of the sensory parameters did not change, but there was a significant difference (P < .05) in flavour. Based on this study, 2 h of UV-C irradiation was effective in reducing 90% of A. flavus, but it was not effective against A. parasiticus present on roasted coffee beans. Also, Hunter colour, pH, and sensory parameters (flavour) were changed by UV-C irradiation.