A Mining Algorithm under Fuzzy Taxonomic Structures

Most conventional data-mining algorithms identify the relationships among transactions using binary values and find rules at a single concept level. Transactions with quantitative values and items with taxonomic relations are, however, commonly seen in real-world applications. Besides, the taxonomic structures may also be represented in a fuzzy way. This paper thus proposes a fuzzy multiple-level mining algorithm for extracting fuzzy association rules under given fuzzy taxonomic structures. The proposed algorithm adopts a top-down progressively deepening approach to finding large itemsets. It integrates fuzzy-set concepts, data-mining technologies and multiple-level fuzzy taxonomy to find fuzzy association rules from given transaction data sets. Each item uses only the linguistic term with the maximum cardinality in later mining processes, thus making the number of fuzzy regions to be processed the same as the number of the original items. The algorithm therefore focuses on the most important linguistic terms for reduced time complexit

Au@Nb@HₓK₁₋ₓNbO₃ nanopeapods with near-infrared active plasmonic hot-electron injection for water splitting

Full-spectrum utilization of diffusive solar energy by a photocatalyst for environmental remediation and fuel generation has long been pursued. In contrast to tremendous efforts in the UV-to-VIS light regime of the solar spectrum, the NIR and IR areas have been barely addressed although they represent about 50% of the solar flux. Here we put forward a biomimetic photocatalyst blueprint that emulates the growth pattern of a natural plant—a peapod—to address this issue. This design is exemplified via unidirectionally seeding core-shell Au@Nb nanoparticles in the cavity of semiconducting H x K1−xNbO3 nanoscrolls. The biomimicry of this nanopeapod (NPP) configuration promotes near-field plasmon–plasmon coupling between bimetallic Au@Nb nanoantennas (the peas), endowing the UV-active H x K1−xNbO3 semiconductor (the pods) with strong VIS and NIR light harvesting abilities. Moreover, the characteristic 3D metal-semiconductor junction of the Au@Nb@H x K1−xNbO3 NPPs favors the transfer of plasmonic hot carriers to trigger dye photodegradation and water photoelectrolysis as proofs-of-concept. Such broadband solar spectral response renders the Au@Nb@H x K1−xNbO3 NPPs highly promising for widespread photoactive devices

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan

PurposeTo compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs).MethodsA retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected. The datasets were divided into UECT (unenhanced computed tomography) and CECT (enhanced computed tomography) for analysis and modelling. Radiomics model and 3D CNN model were used to differentiate TETs from non-TET PMTs (including cyst, malignant germ cell tumor, lymphoma and teratoma). The macro F1-score and receiver operating characteristic (ROC) analysis were performed to evaluate the prediction models.ResultIn the UECT dataset, there were 297 patients with TETs and 79 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 83.95%, ROC-AUC = 0.9117) had better performance than the 3D CNN model (macro F1-score = 75.54%, ROC-AUC = 0.9015). In the CECT dataset, there were 296 patients with TETs and 77 patients with other PMTs. The performance of radiomic analysis with machine learning model using LightGBM with Extra Tree (macro F1-Score = 85.65%, ROC-AUC = 0.9464) had better performance than the 3D CNN model (macro F1-score = 81.01%, ROC-AUC = 0.9275).ConclusionOur study revealed that the individualized prediction model integrating clinical information and radiomic features using machine learning demonstrated better predictive performance in the differentiation of TETs from other PMTs at chest CT scan than 3D CNN model

When Cytokinin, a Plant Hormone, Meets the Adenosine A2A Receptor: A Novel Neuroprotectant and Lead for Treating Neurodegenerative Disorders?

It is well known that cytokinins are a class of phytohormones that promote cell division in plant roots and shoots. However, their targets, biological functions, and implications in mammalian systems have rarely been examined. In this study, we show that one cytokinin, zeatin riboside, can prevent pheochromocytoma (PC12) cells from serum deprivation-induced apoptosis by acting on the adenosine A2A receptor (A2A-R), which was blocked by an A2A-R antagonist and a protein kinase A (PKA) inhibitor, demonstrating the functional ability of zeatin riboside by mediating through A2A-R signaling event. Since the A2A-R was implicated as a therapeutic target in treating Huntington’s disease (HD), a cellular model of HD was applied by transfecting mutant huntingtin in PC12 cells. By using filter retardation assay and confocal microscopy we found that zeatin riboside reversed mutant huntingtin (Htt)-induced protein aggregations and proteasome deactivation through A2A-R signaling. PKA inhibitor blocked zeatin riboside-induced suppression of mutant Htt aggregations. In addition, PKA activated proteasome activity and reduced mutant Htt protein aggregations. However, a proteasome inhibitor blocked both zeatin riboside-and PKA activator-mediated suppression of mutant Htt aggregations, confirming mediation of the A2A-R/PKA/proteasome pathway. Taken together, zeatin riboside might have therapeutic potential as a novel neuroprotectant and a lead for treating neurodegenerative disorders

Constraints on the cosmic expansion history from GWTC-3

We use 47 gravitational-wave sources from the Third LIGO-Virgo-KAGRA Gravitational-Wave Transient Catalog (GWTC-3) to estimate the Hubble parameter $H(z)$, including its current value, the Hubble constant $H_0$. Each gravitational-wave (GW) signal provides the luminosity distance to the source and we estimate the corresponding redshift using two methods: the redshifted masses and a galaxy catalog. Using the binary black hole (BBH) redshifted masses, we simultaneously infer the source mass distribution and $H(z)$. The source mass distribution displays a peak around $34\, {\rm M_\odot}$, followed by a drop-off. Assuming this mass scale does not evolve with redshift results in a $H(z)$ measurement, yielding $H_0=68^{+12}_{-7} {\rm km\,s^{-1}\,Mpc^{-1}}$ ($68\%$ credible interval) when combined with the $H_0$ measurement from GW170817 and its electromagnetic counterpart. This represents an improvement of 17% with respect to the $H_0$ estimate from GWTC-1. The second method associates each GW event with its probable host galaxy in the catalog GLADE+, statistically marginalizing over the redshifts of each event's potential hosts. Assuming a fixed BBH population, we estimate a value of $H_0=68^{+8}_{-6} {\rm km\,s^{-1}\,Mpc^{-1}}$ with the galaxy catalog method, an improvement of 42% with respect to our GWTC-1 result and 20% with respect to recent $H_0$ studies using GWTC-2 events. However, we show that this result is strongly impacted by assumptions about the BBH source mass distribution; the only event which is not strongly impacted by such assumptions (and is thus informative about $H_0$) is the well-localized event GW190814

Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data

Results are presented for a semi-coherent search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1, using a hidden Markov model (HMM) to allow for spin wandering. This search improves on previous HMM-based searches of Laser Interferometer Gravitational-wave Observatory (LIGO) data by including the orbital period in the search template grid, and by analyzing data from the latest (third) observing run (O3). In the frequency range searched, from 60 to 500 Hz, we find no evidence of gravitational radiation. This is the most sensitive search for Scorpius X-1 using a HMM to date. For the most sensitive sub-band, starting at $256.06$Hz, we report an upper limit on gravitational wave strain (at $95 \%$ confidence) of $h_{0}^{95\%}=6.16\times10^{-26}$, assuming the orbital inclination angle takes its electromagnetically restricted value $\iota=44^{\circ}$. The upper limits on gravitational wave strain reported here are on average a factor of $\sim 3$ lower than in the O2 HMM search. This is the first Scorpius X-1 HMM search with upper limits that reach below the indirect torque-balance limit for certain sub-bands, assuming $\iota=44^{\circ}$

Search for continuous gravitational wave emission from the Milky Way center in O3 LIGO--Virgo data

We present a directed search for continuous gravitational wave (CW) signals emitted by spinning neutron stars located in the inner parsecs of the Galactic Center (GC). Compelling evidence for the presence of a numerous population of neutron stars has been reported in the literature, turning this region into a very interesting place to look for CWs. In this search, data from the full O3 LIGO--Virgo run in the detector frequency band $[10,2000]\rm~Hz$ have been used. No significant detection was found and 95$\%$ confidence level upper limits on the signal strain amplitude were computed, over the full search band, with the deepest limit of about $7.6\times 10^{-26}$ at $\simeq 142\rm~Hz$. These results are significantly more constraining than those reported in previous searches. We use these limits to put constraints on the fiducial neutron star ellipticity and r-mode amplitude. These limits can be also translated into constraints in the black hole mass -- boson mass plane for a hypothetical population of boson clouds around spinning black holes located in the GC.Comment: 25 pages, 5 figure